Simulation and management of electric vehicle charging infrastructure

Abstract

A facility for predicting on site electric power requirements for maintaining a fully electric fleet of vehicles in a mining operation to ensure sustainable electric operations, comprising a server comprising communications module configured to receive data and to transmit load management instructions; plurality of electrical charging stations; plurality of electric vehicles configured to be recharged by a selected electrical charging station; wherein the server comprises processor coupled with non-volatile memory, the non-volatile memory storing processing instructions that, when executed by the processor, causes the processor to simulate a total electrical power demand of the mine site due to the plurality of cabled mine equipment and the plurality of electric vehicles for each electric vehicle and each charging station within the facility over a prescribed period thereby to simulate and determine an energy storage capacity requirement of the charging stations of the facility through the prescribed period; thereby to forecast the electrical load management needs of the facility through the prescribed period.

Description

SIMULATION AND MANAGEMENT OF ELECTRIC VEHICLE CHARGING INFRASTRUCTUREField of the Invention

[0001] The present invention relates to methods and applications for simulation of and ongoing management of the power demands of a fully electric mine site for predicting on site electric power requirements for maintaining a fully electric fleet of vehicles.

[0002] The invention has been developed primarily for use in methods and systems for predicting on site electric power requirements for maintaining a fully electric fleet of vehicles in a mining operation to ensure sustainable electric operations and will be described hereinafter with reference to this application. However, it will be appreciated that the invention is not limited to this particular field of use.Background

[0003] Any discussion of the background art throughout the specification should in no way be considered as an admission that such background art is prior art, nor that such background art is widely known or forms part of the common general knowledge in the field in Australia or worldwide as at the priority date of the present application.

[0004] Those skilled in the art will appreciate that the invention described herein is susceptible to variations and modifications other than those specifically described. The invention includes all such variation and modifications. The invention also includes all of the steps, features, formulations, and compounds referred to or indicated in the specification, individually or collectively and any and all combinations of any two or more of the steps or features.

[0005] Mining has long been associated with environmental degradation, high carbon emissions and negative impacts on local communities. However, with rapid technological advancements, there are now viable solutions to mitigate these problems. That means complete electrification of mining operations. However, converting a mining operation to fully electric presents several challenges that need to be addressed for a successful transition.

[0006] Primarily, there is a need for infrastructure development to establish a robust transmission, generation and charging infrastructure crucial for electric mining operations. Mining sites are often located in remote areas with limited access to electrical grids. Building the necessary charging stations, generation and power distribution networks requires significant investment and coordination with energy providers. Developing the infrastructure to support efficient operation of cabled electric machines, high-rate charging of battery electric mobile machines and ensuring a reliable power supply are key challenges for the mine operator.

[0007] Power supply and demand requirements of a fully electric fleet of mining vehicles presents a significant challenge. There is significant variability in power demand for large electric fleets at electric mining operations which is crucial that the grid is able to supply. Electrical mining equipment requires significant amounts of electricity to operate efficiently. The existing electrical infrastructure will not be able to meet the high energy demands required for common electrical operations. Mining companies must assess the availability and reliability of electricity supply in their area. If the available electrical grid infrastructure is inadequate, the mine operator has historically been restricted with the options for upgrading the local electricity grid.

[0008] However, with the rapid improvement in battery storage technology, the installation of on-site sustainable energy systems or using energy storage solutions to ensure a reliable power supply has become available. Such equipment, however, remains expensive so there is a need to provide sufficient electric power storage and vehicle charging infrastructure to support continuous (i.e., non-stop) operations without wasted overhead electrical supply capacity.

[0009] Continuing management of the electric storage and charging infrastructure is also a significant challenge for the fully electric mine operator. Availability of mining equipment and electrical parts can be limited, especially for specialized fleet machinery and charging infrastructure. Ensuring a reliable supply chain for electrical equipment, batteries and charging infrastructure is essential to avoid extremely costly implementation delays.

[0010] If the above challenges to converting a mining operation to a fully electric fleet can be overcome, there are significant benefits that can be achieved. For example, the environmental benefits are an obvious advantage where converting the mining operation to full electricity generates a significant reduction in greenhouse gas emissions. Traditional mining equipment, such as diesel trucks and other mobile mining machines, emit carbon dioxide, nitrogen oxides and particulate matter into the air. Replacing this polluting equipment with electric alternatives will significantly reduce emissions, improve air quality and reduce the mining operation’s contribution to climate change.

[0011] Mining activities are very noisy and disturb nearby communities and wildlife. Electric mining equipment runs much quieter than diesel equipment, resulting in less noise pollution. This reduction in noise levels will help improve the quality of life for people living near the mine and reduce disruption to the local ecosystem.

[0012] As well as the environmental benefits of an electric mining operation conversion there are also significant economic benefits. Improving the environmental credentials of the mine also affects the political palatability of mining operations for necessary minerals and commoditiesrequired for manufacture of modern products, including, for example, rare earth metals necessary for the manufacture of modern computing devices and solar cells.

[0013] The primary economic benefit in a fully electric mining fleet is the cost savings obtained by decoupling the mining operation based on conventional fossil fuel (typically diesel) equipment. The initial investment in electrical mining equipment may be higher than conventional equipment, but long-term operating costs are significantly lower. Electric vehicles have fewer moving parts, making them cheaper to maintain and repair. Additionally, electricity prices are typically more stable than fluctuating fuel prices, providing mining companies with predictable and potentially lower long-term energy costs. Electric mining equipment is also more energy efficient than diesel powered equipment. Electric motors convert a large percentage of energy into useful work, reducing energy consumption and increasing productivity. This increased efficiency not only reduces operating costs, but also provides more output from the same capacity, increasing overall profitability.

[0014] Governments around the world are introducing stricter environmental regulations to reduce carbon emissions and encourage sustainable practices. By switching to all-electric mining, companies can comply with these regulations and avoid potential fines and penalties. In addition, the use of sustainable practices can enhance a company's reputation and attract environmentally friendly investors, making it more competitive in the market.

[0015] Converting mining operations to fully electric is an important step towards sustainable and responsible resource extraction. Environmental benefits, including reduced emissions, noise pollution, are essential for maintaining ecosystems and improving the well-being of local communities. In addition, the economic benefits of reduced costs, improved energy efficiency and regulatory compliance make this move feasible and financially profitable for mining companies. By using electric mining equipment, the industry can contribute to a greener future while remaining profitable. It is essential that mining companies, regulators and stakeholders collaborate and invest in this transition to ensure a sustainable and responsible mining sector for future generations.

[0016] Therefore, there is a need for systems and methods for precise predictions of the energy transmission, generation, storage and charging requirement of a fully electric feet of mining equipment to ensure that the conversion to fully electric is economically viable for the mining operator.Summary

[0017] It is an object of the present invention to overcome or ameliorate at least one or more of the disadvantages of the prior art, or to provide a useful alternative.

[0018] According to a first aspect of the invention, there is provided a facility for predicting on site electric power requirements for maintaining a fully electric fleet of vehicles in a mining operation to ensure sustainable electric operations. The facility may comprise a server comprising a communications module configured to receive data and to transmit load management instructions. The facility may further comprise a plurality of electrical charging stations; plurality of electric vehicles configured to be recharged by a selected electrical charging station. The server may comprise a processor coupled with non-volatile memory. The non-volatile memory may store processing instructions. When executed by the processor, the processing instructions may cause the processor to simulate a total electrical power demand of the mine site due to the plurality of cabled mine equipment and the plurality of electric vehicles for each electric vehicle and each charging station within the facility over a prescribed period. The processing instructions may further cause the processor to simulate and determine an energy storage capacity requirement of the charging stations of the facility through the prescribed period; thereby to forecast the electrical load management needs of the facility through the prescribed period.

[0019] According to a particular arrangement of the first aspect of the invention, there is provided a facility for predicting on site electric power requirements for maintaining a fully electric fleet of vehicles in a mining operation to ensure sustainable electric operations, the facility comprising: a server comprising a communications module configured to receive data and to transmit load management instructions; a plurality of electrical charging stations; and a plurality of electric vehicles configured to be recharged by a selected electrical charging station; wherein the server comprises a processor coupled with non-volatile memory, the non-volatile memory storing processing instructions that, when executed by the processor, causes the processor to: simulate a total electrical power demand of the mine site due to the plurality of cabled mine equipment and the plurality of electric vehicles for each electric vehicle and each charging station within the facility over a prescribed period; thereby to simulate and determine an energy storage capacity requirement of the charging stations of the facility through the prescribed period; thereby to forecast the electrical load management needs of the facility through the prescribed period.

[0020] According to a second aspect of the invention, there is provided a facility. The facility may comprise a server comprising a communications module configured to receive data and totransmit load management instructions. The facility may further comprise a plurality of electrical charging stations. The plurality of electrical charging stations may comprise charging station communication module configured for transmitting data to the server including an energy storage level of the charging station. The plurality of electrical charging stations may comprise one or more charging outlets. The facility may further comprise a plurality of cabled electrical mine machines. The facility may further comprise a plurality of electric vehicles configured to be recharged by a selected electrical charging station. Each of the plurality of electric vehicles may comprise one or more rechargeable batteries. The plurality of electric vehicles may further comprise charging cable adapted for connection to one of the one or more charging outlet. The plurality of electric vehicles may further comprise a battery charge sensor and vehicle communication module transmitting data to the server including a charge state of the one or more rechargeable batteries. The charging station communications module may be further configured to transmit queue data to the server with respect to a plurality of the electric vehicles queueing at the charging station to be recharged.

[0021] The server may further comprise a processor coupled with non-volatile memory, the non-volatile memory storing processing instructions that, when executed by the processor, causes the processor to simulate a total electrical power demand of the mine site due to the plurality of cabled mine equipment and the plurality of electric vehicles. The processing instructions may further simulate a battery discharge rate of each of the electric vehicles. The processing instructions may further simulate a received data signal from said electric vehicles indicative of a low charge state. The processing instructions may further simulate a received data signal from said charging stations indicative of a charge state of the charging station and a queue state. The processing instructions may further compute an energy consumption requirement for an electric vehicle having a low charge state to determine a travel range to choose a charging station having sufficient electrical capacity to recharge the batteries of the electric vehicle. The processing instructions may further simulate directing the electric vehicle to the chosen charging station within the travel range of the electric vehicle. The processing instructions may further simulate the energy requirements for recharging of each of the electric vehicles in a queue corresponding to each of the charging stations. The processing instructions may further repeat the simulations for each electric vehicle and each charging station within the facility over a prescribed period thereby to simulate and determine an energy storage capacity requirement of the charging stations of the facility through the prescribed period; thereby to forecast the electrical load management needs of the facility through the prescribed period.

[0022] According to a particular arrangement of the second aspect of the invention, there is provided a facility, the facility comprising:a server comprising communications module configured to receive data and to transmit load management instructions; a plurality of electrical charging stations comprising: charging station communication module configured for transmitting data to the server including an energy storage level of the charging station; and a plurality of cabled electrical mine machines; a plurality of electric vehicles configured to be recharged by a selected electrical charging station, each of the plurality of electric vehicles comprising: one or more rechargeable batteries; a battery charge sensor; and vehicle communication module transmitting data to the server including a charge state of the one or more rechargeable batteries.

[0023] According to a third aspect of the invention, there is provided a method for forecasting and simulating electrical load management needs of a facility. The facility may comprise a server comprising communications module configured to receive data and to transmit load management instructions. The facility may further comprise a plurality of electrical charging stations. Each of the plurality of electrical charging stations may comprise charging station communication module configured for transmitting data to the server including an energy storage level of the charging station. Each electrical charging stations may further comprise a plurality of cabled electrical mine machines. Each electrical charging stations may further comprise a plurality of electric vehicles configured to be recharged by a selected electrical charging station. Each of the plurality of electric vehicles may comprise one or more rechargeable batteries. Each of the plurality of electric vehicles may further comprise a battery charge sensor. Each of the plurality of electric vehicles may comprise a vehicle communication module transmitting data to the server including a charge state of the one or more rechargeable batteries.

[0024] The charging station communications module may be further configured to transmit queue data to the server with respect to a plurality of the electric vehicles queueing at the charging station to be recharged.

[0025] The server may further comprise a processor coupled with non-volatile memory, the non-volatile memory storing processing instructions that, when executed by the processor, causes the processor to: simulate a total electrical power demand of the mine site due to the plurality of cabled mine equipment and the plurality of electric vehicles; simulate a battery discharge rate of each of the electric vehicles; simulate a received data signal from said electric vehicles indicative of a low charge state;simulate a received data signal from said charging stations indicative of a charge state of the charging station and a queue state; compute an energy consumption requirement for an electric vehicle having a low charge state to determine a travel range to choose a charging station having sufficient electrical capacity to recharge the batteries of the electric vehicle; simulate directing the electric vehicle to the chosen charging station within the travel range of the electric vehicle; simulate the energy requirements for recharging of each of the electric vehicles in a queue corresponding to each of the charging stations; and repeat the simulations for each electric vehicle and each charging station within the facility over a prescribed period thereby to simulate and determine an energy storage capacity requirement of the charging stations of the facility through the prescribed period; thereby to forecast the electrical load management needs of the facility through the prescribed period.

[0026] In a particular arrangement of the third aspect, there is provided method for forecasting and simulating electrical load management needs of a facility, the facility comprising: a server comprising communications module configured to receive data and to transmit load management instructions; a plurality of electrical charging stations comprising: charging station communication module configured for transmitting data to the server including an energy storage level of the charging station; and a plurality of cabled electrical mine machines; a plurality of electric vehicles configured to be recharged by a selected electrical charging station, each of the plurality of electric vehicles comprising: one or more rechargeable batteries; a battery charge sensor; and vehicle communication module transmitting data to the server including a charge state of the one or more rechargeable batteries; wherein: the charging station communications module is further configured to transmit queue data to the server with respect to a plurality of the electric vehicles queueing at the charging station to be recharged; and the server further comprises a processor coupled with non-volatile memory, the non-volatile memory storing processing instructions that, when executed by the processor, causes the processor to: simulate a total electrical power demand of the mine site due to the plurality of cabled mine equipment and the plurality of electric vehicles;simulate a battery discharge rate of each of the electric vehicles; simulate a received data signal from said electric vehicles indicative of a low charge state; simulate a received data signal from said charging stations indicative of a charge state of the charging station and a queue state; compute an energy consumption requirement for an electric vehicle having a low charge state to determine a travel range to choose a charging station having sufficient electrical capacity to recharge the batteries of the electric vehicle; simulate directing the electric vehicle to the chosen charging station within the travel range of the electric vehicle; simulate the energy requirements for recharging of each of the electric vehicles in a queue corresponding to each of the charging stations; and repeat the simulations for each electric vehicle and each charging station within the facility over a prescribed period thereby to simulate and determine an energy storage capacity requirement of the charging stations of the facility through the prescribed period; thereby to forecast the electrical load management needs of the facility through the prescribed period.

[0027] The charging station communications module may be further configured to transmit queue data to the server with respect to a plurality of the electric vehicles queueing at the charging station to be recharged.

[0028] The server may further comprises a processor coupled with non-volatile memory, the non-volatile memory storing processing instructions that, when executed by the processor, causes the processor to: simulate a total electrical power demand of the mine site due to the plurality of cabled mine equipment and the plurality of electric vehicles; simulate a battery discharge rate of each of the electric vehicles; simulate a received data signal from said electric vehicles indicative of a low charge state; simulate a received data signal from said charging stations indicative of a charge state of the charging station and a queue state; compute an energy consumption requirement for an electric vehicle having a low charge state to determine a travel range to choose a charging station having sufficient electrical capacity to recharge the batteries of the electric vehicle;simulate directing the electric vehicle to the chosen charging station within the travel range of the electric vehicle; simulate the energy requirements for recharging of each of the electric vehicles in a queue corresponding to each of the charging stations; and repeat the simulations for each electric vehicle and each charging station within the facility over a prescribed period thereby to simulate and determine an energy storage capacity requirement of the charging stations of the facility through the prescribed period; thereby to forecast the electrical load management needs of the facility through the prescribed period.

[0029] According to a fourth aspect of the invention, there is provided an apparatus for configuration and management of electric vehicle (EV) charging infrastructure in a mining operation. The apparatus may comprise a processor configured to receive input data and to execute computer program code instructions stored in a non-transitory memory. The processor, the processor, upon executing the program code instructions, may execute a method comprising the step of receiving input data related to: a plurality of cabled electrical mine machines; parameters describing one or more EV charging stations; and parameters describing one or more electric mobile mining vehicles configured to be recharged by a selected charging station, each of the electric mining vehicles comprising: one or more rechargeable batteries; a battery charge sensor; vehicle communication module configured for transmitting data to the server including a charge state of the one or more rechargeable batteries; parameters describing one or more cabled electric mine equipment; power requirements during different states; power factor to understand grid requirements; and providing the input data to the memory.

[0030] The method may comprise the further step of providing the input data to the processor configured to simulate the mining operation including the plurality of electric mobile mining machines to generate a mine operation simulation over a predetermined time period.

[0031] The method may comprise the further step of producing a recommendation for electrical power charging requirements of the mine operation simulation. The recommendation may be based on one or more of: electric vehicle charge depletion characteristics; available charge capacity of each of the charging stations; instantaneous electric vehicle queue characteristics at each of the charging stations; vehicle travel time from a working location to a charging station; and electric vehicle mining charging time.

[0032] The method may comprise the further step of producing a recommendation for electrical power requirements for cabled electrical machines based on one or more of: individual operating state of each asset in the mine; number of cabled assets in the mine.

[0033] The method may comprise the further step of utilising the mine operation simulation to validate the processor's recommendation in order to determine the characteristics of the charging infrastructure required for continuous mining operation.

[0034] According to a particular arrangement of the fourth aspect of the invention, there is provided an apparatus for configuration and management of electric vehicle (EV) charging infrastructure in a mining operation, comprising:(i) a processor configured to receive input data and to execute computer program code instructions stored in a non-transitory memory wherein the processor, upon executing the program code instructions, executes a method comprising the steps of: receiving input data related to: a plurality of cabled electrical mine machines; parameters describing one or more EV charging stations; and parameters describing one or more electric mobile mining vehicles configured to be recharged by a selected charging station, each of the electric mining vehicles comprising: one or more rechargeable batteries; a battery charge sensor; vehicle communication module configured for transmitting data to the server including a charge state of the one or more rechargeable batteries; parameters describing one or more cabled electric mine equipment; power requirements during different states; power factor to understand grid requirements; and providing the input data to the memory;(ii) providing the input data to the processor configured to simulate the mining operation including the plurality of electric mobile mining machines to generate a mine operation simulation over a predetermined time period; and(iii) producing a recommendation for electrical power charging requirements of the mine operation simulation based on one or more of: electric vehicle charge depletion characteristics; available charge capacity of each of the charging stations; instantaneous electric vehicle queue characteristics at each of the charging stations; vehicle travel time from a working location to a charging station; and electric vehicle mining charging time;(iv) producing a recommendation for electrical power requirements for cabled electrical machines based on one or more of: individual operating state of each asset in the mine; number of cabled assets in the mine;(v) utilising the mine operation simulation to validate the processor's recommendation in order to determine the characteristics of the charging infrastructure required for continuous mining operation.

[0035] One embodiment provides a computer program product for performing a method as described herein.

[0036] One embodiment provides a non-transitive carrier medium for carrying computer executable code that, when executed on a processor, causes the processor to perform a method as described herein.

[0037] One embodiment provides a system configured for performing a method as described herein.Brief Description of the Drawings

[0038] Notwithstanding any other forms which may fall within the scope of the present invention, a preferred embodiment / preferred embodiments of the invention will now be described, by way of example only, with reference to the accompanying drawings in which:

[0039] Figure 1 shows an example mine facility 100 utilising electric power fleet vehicles;

[0040] Figure 2 shows an example Mine Plan simulation system configured for simulation of the mine facility according to a Mine Plan;

[0041] Figure 3A shows a simplified flow chart of mine operations carried out by haul trucks in operation of the mine facility;

[0042] Figure 3B shows a simplified flow chart of mine operations carried out by cabled mine equipment of the mine facility;

[0043] Figure 4A is a graph of Mine Plan vs Simulated tonnes delivered by the simulated Mine Plan;

[0044] Figure 4B is a graph of simulated average charging station queue and travel times to charging station;

[0045] Figure 4C is a graph of simulated Peak Power vs Average Power required by the mine facility; and

[0046] Figure 5 shows a block diagram that illustrates an example computer system with which an embodiment may be implemented.

[0047] In the drawings, like structures are referred to by like numerals throughout the several views. The drawings shown are not necessarily to scale, with emphasis instead generally being placed upon illustrating the principles of the present invention.Definitions

[0048] The following definitions are provided as general definitions and should in no way limit the scope of the present invention to those terms alone, but are put forth for a better understanding of the following description.

[0049] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by those of ordinary skill in the art to which the invention belongs. It will be further understood that terms used herein should be interpreted as having a meaning that is consistent with their meaning in the context of this specification and the relevant art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein. For the purposes of the present invention, additional terms are defined below. Furthermore, all definitions, as defined and used herein, should be understood to control over dictionary definitions, definitions in documents incorporated by reference, and / or ordinary meanings of the defined terms unless there is doubt as to the meaning of a particular term, in which case the common dictionary definition and / or common usage of the term will prevail.

[0050] For the purposes of the present invention, the following terms are defined below.

[0051] The articles “a” and “an” are used herein to refer to one or to more than one (i.e., to at least one) of the grammatical object of the article. By way of example, “an element’ refers to one element or more than one element.

[0052] The term “about’ is used herein to refer to quantities that vary by as much as 30%, preferably by as much as 20%, and more preferably by as much as 10% to a reference quantity. The use of the word “about’ to qualify a number is merely an express indication that the number is not to be construed as a precise value.

[0053] Throughout this specification, unless the context requires otherwise, the words “comprise”, “comprises!’ and “comprising" will be understood to imply the inclusion of a stated step or element or group of steps or elements but not the exclusion of any other step or element or group of steps or elements.

[0054] Any one of the terms “including or “which includes’’ or “that includes’’ as used herein is also an open term that also means including at least the elements / features that follow the term, but not excluding others. Thus, “including’ is synonymous with and means “comprising”.

[0055] In the claims, as well as in the summary above and the description below, all transitional phrases such as “comprising’, “including", “carrying", “having’, “containing’, “involving’, “holding’, “composed of’, and the like are to be understood to be open-ended, i.e., to mean “including but not limited to". Only the transitional phrases “consisting of’ and “consisting essentially of’ alone shall be closed or semi-closed transitional phrases, respectively.

[0056] Even though particular combinations of features are recited in the claims and / or disclosed in the specification, these combinations are not intended to limit the disclosure of possible implementations. In fact, many of these features may be combined in ways not specifically recited in the claims and / or disclosed in the specification. Although each dependent claim listed below may directly depend on only one claim, the disclosure of possible implementations includes each dependent claim in combination with every other claim in the claim set.

[0057] Although any methods and materials similar or equivalent to those described herein can be used in the practice or testing of the present invention, preferred methods and materials are described. It will be appreciated that the methods, apparatus and systems described herein may be implemented in a variety of ways and for a variety of purposes. The description here is by way of example only.

[0058] The various methods or processes outlined herein may be coded as software that is executable on one or more processors that employ any one of a variety of operating systems or platforms. Additionally, such software may be written using any of a number of suitable programming languages and / or programming or scripting tools, and also may be compiled as executable machine language code or intermediate code that is executed on a framework or virtual machine.

[0059] In this respect, various inventive concepts may be embodied as a computer readable storage medium (or multiple computer readable storage media) (e.g., a computer memory, one or more floppy discs, compact discs, optical discs, magnetic tapes, flash memories, circuit configurations in field programmable gate arrays (FPGAs) or other semiconductor devices, or other non-transitory medium or tangible computer storage medium) encoded with one or more programs that, when executed on one or more computers or other processors, perform methods that implement the various embodiments of the invention discussed above. The computer readable medium or media can be transportable, such that the program or programs storedthereon can be loaded onto one or more different computers or other processors to implement various aspects of the present invention as discussed above.

[0060] The terms “prograrri’ or “software” are used herein in a generic sense to refer to any type of computer code or set of computer-executable instructions that can be employed to program a computer or other processor to implement various aspects of embodiments as discussed above. Additionally, it should be appreciated that according to one aspect, one or more computer programs that when executed perform methods of the present invention need not reside on a single computer or processor, but may be distributed in a modular fashion amongst a number of different computers or processors to implement various aspects of the present invention.

[0061] Computer-executable instructions may be in many forms, such as program modules, executed by one or more computers or other devices. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types. Typically, the functionality of the program modules may be combined or distributed as desired in various embodiments.

[0062] Also, data structures may be stored in computer-readable media in any suitable form. For simplicity of illustration, data structures may be shown to have fields that are related through location in the data structure. Such relationships may likewise be achieved by assigning storage for the fields with locations in a computer-readable medium that convey relationship between the fields. However, any suitable mechanism may be used to establish a relationship between information in fields of a data structure, including through the use of pointers, tags or other mechanisms that establish relationship between data elements.

[0063] Also, various inventive concepts may be embodied as one or more methods, of which an example has been provided. The acts performed as part of the method may be ordered in any suitable way. Accordingly, embodiments may be constructed in which acts are performed in an order different than illustrated, which may include performing some acts simultaneously, even though shown as sequential acts in illustrative embodiments.

[0064] The phrase "and / or’, as used herein in the specification and in the claims, should be understood to mean “either or both" of the elements so conjoined, i.e., elements that are conjunctively present in some cases and disjunctively present in other cases. Multiple elements listed with “and / or’ should be construed in the same fashion, i.e., "one or more" of the elements so conjoined. Other elements may optionally be present other than the elements specifically identified by the “and / oi" clause, whether related or unrelated to those elements specifically identified. Thus, as a non-limiting example, a reference to “A and / or B’, when used in conjunction with open-ended language such as “comprising^’ can refer, in one embodiment, to A only(optionally including elements other than B); in another embodiment, to B only (optionally including elements other than A) ; in yet another embodiment, to both A and B (optionally including other elements); etc.

[0065] As used herein in the specification and in the claims, “or” should be understood to have the same meaning as “and / or” as defined above. For example, when separating items in a list, “or” or “and / oi” shall be interpreted as being inclusive, i.e., the inclusion of at least one, but also including more than one, of a number or list of elements, and, optionally, additional unlisted items. Only terms clearly indicated to the contrary, such as “only one of’ or “exactly one of’, or, when used in the claims, “consisting of’ will refer to the inclusion of exactly one element of a number or list of elements. In general, the term “of’ as used herein shall only be interpreted as indicating exclusive alternatives (i.e., ’’one or the other but not both”) when preceded by terms of exclusivity, such as “eithef’, “one of, “only one of, or “exactly one of. “Consisting essentially of, when used in the claims, shall have its ordinary meaning as used in the field of patent law.

[0066] As used herein in the specification and in the claims, the phrase “at least one”, in reference to a list of one or more elements, should be understood to mean at least one element selected from any one or more of the elements in the list of elements, but not necessarily including at least one of each and every element specifically listed within the list of elements and not excluding any combinations of elements in the list of elements. This definition also allows that elements may optionally be present other than the elements specifically identified within the list of elements to which the phrase “at least one” refers, whether related or unrelated to those elements specifically identified. Thus, as a non-limiting example, “at least one of A and B’ (or, equivalently, “at least one of A or B’, or, equivalently “at least one of A and / or B’) can refer, in one embodiment, to at least one, optionally including more than one, A, with no B present (and optionally including elements other than B); in another embodiment, to at least one, optionally including more than one, B, with no A present (and optionally including elements other than A); in yet another embodiment, to at least one, optionally including more than one, A, and at least one, optionally including more than one, B (and optionally including other elements); etc.

[0067] For the purpose of this specification, where method steps are described in sequence, the sequence does not necessarily mean that the steps are to be carried out in chronological order in that sequence, unless there is no other logical manner of interpreting the sequence.

[0068] In addition, where features or aspects of the invention are described in terms of Markush groups, those skilled in the art will recognise that the invention is also thereby described in terms of any individual member or subgroup of members of the Markush group.Detailed Description

[0069] Modifications and variations such as would be apparent to the skilled addressee are considered to fall within the scope of the present invention. The present invention is not to be limited in scope by any of the specific embodiments described herein. These embodiments are intended for the purpose of exemplification only. Functionally equivalent products, formulations and methods are clearly within the scope of the invention as described herein. It will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the spirit and scope of the invention as defined by the appended claims.

[0070] Example embodiments are provided so that this disclosure will be thorough, and will fully convey the scope to those who are skilled in the art. Numerous specific details are set forth such as examples of specific components, devices, and methods, to provide a thorough understanding of embodiments of the present disclosure. It will be apparent to those skilled in the art that specific details need not be employed, that example embodiments may be embodied in many different forms and that neither should be construed to limit the scope of the disclosure. In some example embodiments, well-known processes, well-known device structures, and well-known technologies are not described in detail.

[0071] Such variations are not to be regarded as a departure from the disclosure, and all such modifications are intended to be included within the scope of the disclosure.

[0072] The method steps, processes, and operations described herein are not to be construed as necessarily requiring their performance in the particular order discussed or illustrated, unless specifically identified as an order of performance. It is also to be understood that additional or alternative steps may be employed.

[0073] This disclosure focuses on how to design and manage the infrastructure of a mine site for electric vehicle (EV) charging and operation of cabled electric machines in a way that minimises the total annualised cost of investment and postpones upgrades to electric infrastructure while maintaining the energy needed for electric vehicles, particularly in the context of a mining facility comprising an electric vehicle workforce, particularly mine trucks for transporting mined ore within the mine site and beyond.

[0074] The systems disclosed herein aim to mitigate the issues discussed above in managing an electric vehicle fleet by developing a software solution that configures and controls the EV charging infrastructure and operation of cabled electric machines. Depending on the charging requirements and customer behaviour in a particular application — a school, business, residential building, public facility, or other — the system software configures and suggests a unique EVcharging infrastructure suitable to supply the electric charging needs to the electric vehicle fleet of the mine facility and enables accurate planning of on-site electric charging and storage requirements necessary for continuous mine operations.

[0075] Mine scale energy storage technologies are not yet operationally or economically proven in mining for many reasons including those discussed above but primarily due to the technical difficulties in having sufficient charging and electric storage capabilities available on site, to eliminate any downtime where any of the electric vehicles in the fleet are not underutilised at any time (i.e., when they are not either charging, waiting in a queue at a charging station to be charged, travelling to or from a charging station, or engaged in an active mine operation such as transporting ore, or finally waiting in a queue to be actively engaged in a mine operation). Additionally, the mine facility should not have excess over-capacity of electric charging or storage capabilities as this adds to unnecessary cost to the mine facility is in building, maintaining, and charging such excess capacity which we decrease the economic viability of converting the mine facility to an all-electric workforce.

[0076] Forecasting mobility behaviour, including battery state of charge, and coordinating the design and control of the charging stations with other facility loads, distributed energy resources (DERs), like solar photovoltaics and stationary energy storage, are crucial to the intelligent planning, designing, and controlling of EV charging infrastructure. The systems and methods disclosed herein evaluate mine facility peak power needs on the basis of the fixed (cabled) and mobile electric mine equipment on site, using mathematical models. In other embodiments, the systems and methods can also, optionally, use convex optimisation, machine learning techniques for simulation and optimisation of the power expenditure exhibited by the mine facility.

[0077] Crucially, this approach uses statistical techniques to integrate robustness to unknown generation and loads. Infrastructure decisions are very vulnerable, in the absence of a strong plan, to both undersized and overly aggressive control solutions that lead to excessively costly operational performance. Also, critically to the economic viability of transitioning the mine facility fleet to all-electric is the need to understand the electric power and charging requirements of the fleet across short intraday time scales rather than over longer e.g., monthly time scales where the peak energy requirements can exceed the long-term averages which would result in unacceptable downtime of the electric charging infrastructure.

[0078] Figure 1 shows an example mine facility 100 comprising a mine site boundary 101 , and active mine face 103, in the present arrangement, being worked by a plurality of cabled electric drill machinery 104. Drill machinery 104 are connected to an electric energy supply (not shown) by cables 104a. The mine facility further comprises a plurality of electric vehicle charging stations 110 adapted to charge / recharge a fleet of electric mine vehicles including mine extractionequipment e.g., dig units 111 , and a plurality of ore transport haul trucks 113. Haul trucks 113 are loaded with ore from mine face 103 by dig units 111 and transport the ore to an ore storage facility 120 which may be off-site beyond mine boundary 101 prior to transportation to an ore processing facility.

[0079] Mine planning in crucial for economic operation of the mine facility and such Mine Plans are often prepared for time periods of 5 or 10 years or more. Preparation of the Mine Plan is a complex technical problem as every aspect of the mine operation must be accounted for on relevant time scales, and includes energy requirements for all aspect of the mine operation. A mine facility which includes an electric vehicle fleet provides additional technical difficulties in ensuring adequate energy storage and supply capabilities, without carrying an oversupply which significantly decreases the mine energy efficiency. The technical requirements for charging / recharging electric vehicles to ensure minimal fleet downtime are particularly more demanding than fossil fuel (e.g., diesel) fleet vehicles due to the storage ang charging infrastructure required. Energy requirements in the Mine Plan of a facility which does not include an electric fleet can be adequately forecast using a monthly fuel need average. However, for an electric fleet the energy needs of the fleet must be forecast with much greater precision on much smaller time scales, hourly at a minimum, ideally to minute or sub-minute resolution to capture the high peak power requirements of the mine site which occur by the minute and can be averaged over at hourly resolution such that the simulation would not accurately predict the maximum peak requirements of the site.

[0080] Therefore, there is a great technical need to provide an accurate simulation of the mine fleet operations including each task of each vehicle in the fleet and the energy discharge characteristics of such operations such that any individual vehicle maintains sufficient charge to complete an operation with enough remaining charge to travel to a charging station for recharging before returning to active mine operations. The Mine Plan then must be able to provide sufficient charging stations 110 on-site to support the entire electric fleet and each charging stations must be located to minimise the travel time for each vehicle (e.g., haul truck 113) to reach a nearest charging station. Critical parameters of the charging stations include power delivery rate to accurate simulate the time which a vehicle remains ‘on-charge’ at the station, but also monitoring and tracking of a vehicle queue waiting in line to be charged. Such vehicle queue metrics are critical for efficient mine operation so that when a haul truck requires charging, it can be directed to a particular charging station 110 on-site based on factors such as: available travel range based on current battery charge level, distance to each available charger; and the current queue at each charger. The combination of these factors results in an instruction to the vehicle about which charger to travel time in which to minimise the time until the vehicle can be fully recharged and able to return to mine operations.

[0081] In addition to battery operated electric vehicles, the Mine Plan for each mine site also must accommodate the electrical needs of cabled electric equipment. To integrate cabled electric dig units into the Mine Plan an understanding is needed of the potential instantaneous electric power that could be called on as the dig units enter different dig cycle states independently of each other. The loading state draws the most power, combining this with the power draw from the truck chargers and drills is essential to understanding the peak power that a mining operation may be required to draw.

[0082] Figure 2 shows an example Mine Plan simulation system 200 configured for simulation of the mine facility 100 according to the Mine Plan in order to be able to accurately simulate power and energy requirements of the Mine Plan, accounting for various operating and idle states of charging stations and mobile mining machines to model power requirements and storage needs of the mine facility.

[0083] The technical problem that is being solved by this simulation system 200 is to gain an understanding of possible power variation that might occur by following the Mine Plan for a particular mine facility. A technical simulation solution to the Mine Plan is essential to provide sufficient electric power resources to the mine site to be able to meet the Mine Plan objectives. Without simulation system 200, the best that current Mine Plans could do would be to provide an average power requirement for the planning period. If the mine site were to be configured based on such currently available methods to design the power transmission, supply, and storage to meet the average values, it would be impossible to actually achieve the Mine Plan objectives. For example, if assumptions about power requirements were made without simulation of the energy requirements of the mine site are highly likely to be seriously over- or under-sized, providing significant economic inefficiencies such that the mine facility would not be commercially viable. Decarbonisation efforts for a mine facility is a mu Iti-billion-dollar investment, so it is not acceptable to make such assumptions and decisions without highly specific simulations.

[0084] The simulation system 200 described herein can be used to inform power system design by understanding the energy consumption, charge and dissipation requirements of the cabled and battery electric mobile mining fleet.

[0085] To address this technical need, apparatus 200 for configuration and management of electric vehicle (EV) charging infrastructure in a mining operation is configured to generate a simulation of the mine facility 100 according to the Mine Plan input data stored in a database 210. Apparatus 200 comprises one or more processors 203 configured to receive input data from one or more databases 209, 210 and to execute computer program code instructions stored in a non-transitory memory 207 wherein the processor 203, upon executing the program code instructions, executes a method to simulate the Mine Plan stored in database 210, and inparticular to simulate the energy capacity required to satisfy the goals of the Mine Plan for a particular mine facility. Processor 203 receives input data related to:• parameters describing one or more cabled electric mobile mining machines;• parameters describing one or more EV charging stations;• parameters describing one or more electric mining vehicles configured to be recharged by a selected charging station, each of the electric mining vehicles comprising: o one or more rechargeable batteries; o a battery charge sensor; and o vehicle communication module configured for transmitting data to the server including a charge state of the one or more rechargeable batteries.

[0086] The input data provided to processor 203 which is configured to simulate the mining operation according to the Mine Plan and including the plurality of electric mining vehicles to generate a mine operation simulation over a predetermined time period.

[0087] Processor 203 is configured to simulate the Mine Plan for the mine facility and to generate a recommendation for electrical power demand requirements of the mine operation simulation based on one or more of:• Cabled electric mining machine power consumption;• Battery electric vehicle charge depletion characteristics;• available charge capacity of each of the charging stations; instantaneous electric vehicle queue characteristics at each of the charging stations;• Vehicle travel time from a working location to a charging station; and• Electric vehicle mining charging time;

[0088] The Mine Plan simulation is output to Output Display 220 for execution by a user to implement the simulation recommendations and to validate the recommendations of simulation apparatus 200 in order to determine the characteristics of the charging infrastructure required for continuous mining operation.

[0089] System 200 includes a simulation module 201 comprising one or more processors 203 connected to a bus 205. Non-transitory memory 207 is provided for storage of computer code instructions to be executed by the processors 203 to provide the Mine Plane simulation. Input / output interface 206 is provided so that processors 203 can read input data from Mine Plane Input Data database 210 into non-transitory memory 207 for use in preparing the Mine Plan simulation. Processors 203 on completion of the Mine Plan simulation proved output data via input / output module 206 to Output Display 220. Output Display 220 may be configured to performdata analytics and visualization to help a user understand and interpret the data output from simulation module 201. In particular arrangements, the simulation module 201 may comprise a web interface that also process the results to make it easier for the user to comprehend the data and make decisions on implementing the Mine Plan according to the output simulation provided by simulation module 201 .

[0090] Mine Plant / Facility Input Data database 210 may comprise electric vehicle mobility data over a period of time such as arrival and departure (plug-in, plug-out) time, State-of-Charge (SoC) upon arrival at the charging station, required SoC upon departure, interchange time and cost, impatience time and cost, electric vehicle model (battery size), as well as other inputs such as the nature of the charging rate at various time during a charge cycle, facility operation hours, facility load profile, available stored energy onsite, etc. SoC refers to the percentage of charge present in the battery of the electric vehicle when presented to the charger.

[0091] The Mine Plan Input Database may further comprise cabled mine equipment operational data. Such cable mine equipment may include, at least, electric drills, excavators, front end loaders and other ancillary electrically powered equipment such as graders, watercarts, dozers, floats and service trucks.

[0092] Output data displayed on Output Display 220 may comprise detailed mine power and energy demand data at the activity level as well as aggregated charging demand profile (max, min), aggregated charging energy demand profile (max, min), and statistical variance for parameters for the above profiles (max, min), as well as facility loads and on-site electrical generation data such as facility load profile (variance), onsite generation profile (variance) and energy generation installation size, etc. In specific arrangements, simulation module 201 provides the above data at each vehicle level that will be used to optimise the Mine Plan operation results, i.e. , processors 203 may be configured to optimise at the aggregated level by aggregating the demand of all electric fleet vehicles associated with the mine facility or at an individual vehicle level.

[0093] Figure 3A provides a simplified flow chart 300 of mine operations carried out by haul trucks 113 in operation of the mine and which need to be incorporated into the Mine Plan, including loading / unloading operations 301 which are simulated by simulation module 201. At completion of each load / unload operation 301 the vehicle is queried 303 for the SoC state to determine if a charge cycle is required, for example, at about 10% of the maximum charge. If sufficient charge remains, the vehicle is returned 305 to a global loading queue for reassignment to a new dig unit. If the SoC is insufficient for a further load / unload cycle, the vehicle is assigned a charger and instructed to proceed to the selected charging station for recharging 307. Once charged, the vehicle is returned 305 to the queue for reassignment to a new dig unit.

[0094] Figure 3B provides a simplified flow chart 350 of mine operations in respect of cabled electric machines, for example, as part of the loading / unloading operations 301 of Figure 3A, whereby the dig units responsible for extracting material at a source location and for loading the material onto the mine trucks, are preferably fixed (cabled) electrically powered units. Method 350 includes randomly selecting 351 a transaction type, weighted by quantity of type, where the transaction types may be broadly described as a movement type including, for example:• Expit Ore - which is ore that is from the pit;• Expit Waste - waste from the pit;• Rehandle Ore - ore which is picked up from a stockpile, or more accurately ore that has been previously excavated at least once previously and is now being moved again (his is very often ore that has been stockpiled near the crusher and is now being loaded from these stockpiles and being sent to the crusher);• Rehandle Waste - waste which is picked up from a stockpile.

[0095] The method then searches 353 for the first valid dig location source, which could be wither an expit dig block or a stockpile, that satisfies to conditions of: the dig unit is allowed to use this source, the source has material to move, the source has the selected transaction type, and that there is no dig unit yet on this source. A truck from the global truck queue is identified 355 that is allowed to use this dig unit and has haulage data available band assigned to the dig location source. The truck is then loaded 357 based on the spot time (the time that the truck takes to position itself under the dig unit ) and the load time from dig unit / truck pair metrics. The quantity of material loaded onto the assigned truck is then subtracted from the source availability. Once the first assigned truck is loaded, it is determined 359 whether there is any remaining material at the dig location source, and, if so, a new truck is found 355 and assigned to the source and the process repeats until the dig location source is exhausted. Once each dig location source is exhausted, the procedure of method 350 is repeated for each dig location and transaction type.

[0096] The Mine Plan inputs stored in database 210 are the Mine Plan physicals comprising a list of all mining movements within the Mine Plan. The plan physicals generally include information about the relative additional travel time and energy to charger. This information is generated using a script that describes every activity in the Mine Plan.

[0097] Other parameters entered into the simulation parameter files include: the Mine Plan calendar, the number of battery effective full cycles to end of battery life, truck battery capacity over time as the battery degrades, battery swap time at end of battery life, power draw from fast charger to truck battery and power draw of cabled machines for various mining activities.

[0098] Additional inputs to the simulation module 201 include the order of activities in a Mine Plan which considers many constraints, such as dewatering, bench turnover, heritage constraints,clearing rates. The simulation module 201 assumes that on a period-by-period level, the activities in the simulation will be close enough to what may occur with the level of confidence that are set out in the long term Mine Plan. Mine Plan activities are stored in Mine Plan Input Database 210 to be accessible to processors 203 of simulation module 201.

[0099] Mine Plan Input Database 210 further includes charging characteristics for each battery included in each of the mine electric vehicles. In particular arrangements, the battery charging rate is considered to be flat and constant throughout a charge. This may optionally include an assumption of different charge rate characteristics at each stage of a charging cycle, for instance different power draw rates throughout the duration of recharging the electric vehicle.

[0100] Simulation module 201 may, in particular arrangements, assume that the charging stations always charge at the highest rate available.

[0101] Particular arrangements may further assume that productive machine activity times always match those as in the Mine Plan physicals (such as travel, spotting, loading). Non-productive activity times where a vehicle is waiting in a queue at a charging station to be charged or waiting in the global loading queue for dig unit assignment are assumed to be variable depending on simulation state, however, further arrangements may include additional variation around the productive activity times to more closely align the Mine Plan simulation to real-world experience.

[0102] Particular arrangements may further assume that the power usage of the dig unit vehicles are limited to a discrete number of levels, such as, for example, idle, spotting and loading power levels. For example, for R9400 digger the power usage in each state may =be a fixed value, for instance: Loading - about 1171 kw; spotting - about 727kw; and idling - about 284kw. Further arrangements of to the Mine Plan simulation provided by simulation module 201 may include additional power levels added for different stages of spotting and loading performed by the dig unit vehicles.

[0103] As discussed briefly above, a haul truck is assigned to go to a charger after it has reached the battery energy trigger level 303 (minimum state of charge) and after it has finished a mining cycle 301 (which ends after dumping). The charger is selected 307 by looking at the available charging station 110 associated with the mine facility 100 and selecting the one with minimum of (queue + travel) time. While selecting the charging station 110 closest to the vehicle when the trigger level is activated for each individual truck 113 may appear to be ideal, it is possible and even likely, that the closest charging station 110 may not be the overall best decision for the Mine Plan simulation. For instance, if the closest charging station at the time has a large queue, it may be more efficient to instruct the haul truck 113 to a charging station 110 further away but with ashorter queue to enable the haul truck 113 to be returned to the global loading queue 305 in a shorter amount of time.

[0104] In further arrangements of Mine Plan simulation system 200, computer code instructions stored in non-transitory memory 207 may provide instructions for training a machine learning system to optimise the Mine Plan simulation. For example, the machine learning system may comprise an artificial neural network (ANN) or artificial intelligence (Al) system. The machine learning training may be executed be processors 203 to generate a Mine Plan simulation model which may be stored in non-transitory memory 207. In particular arrangements, Mine Plan simulation model may be optimised on one or more desirable output goals including, for example, minimum haul truck down time with reference to charging cycle queue times or global loading queue waiting times; or for optimisation of the number and / or location of the plurality of charging stations provided in association with the mine facility.

[0105] Once trained, the Mine Plan simulation model may be executed by processors 203 using specific mine facility configuration data stored in Mine Plan Input Database 210.

[0106] In a particular arrangement, simulation module 200 may include simulation of multiple vehicle types operating at the mine facility as well as the charging station operation. Accordingly, there is generally three types of agents to be simulated by simulation module 200: Dig units, Trucks, Chargers, Drills and Miscellaneous ancillary machines. Each of these agents have a mixture of inputs and parameters. This is simulated by the agents periodically going into a “sleep” state in which they can do no work. The sleep state works on Full Day Random Days which causes agents to work for full days or sleep for full days, with a chance of each given day being a “work day”.Dig Units

[0107] Dig units 111 are simulated to mine ore and waste from the sources listed in the input database 210, where a dig unit picks a source block 103 and sticks on it until it has been depleted. When switching source 103, the dig unit will randomly pick a transaction type weighted by the total amount of work to do for that transaction, then it will pick the next source that has that same transaction type, and for which there is currently no other dig unit at that source. These sources 103 have the same order as in the physicals file, so that dependencies between sources should roughly be obeyed.

[0108] When a dig unit 111 has no more sources 103 that it can visit, it will reconsider the list of sources 103 and, for stockpile reclamation transactions, it will allow multiple dig units 111 being at the same source 103. When even all those sources 103 have been depleted the dig units becomes “extinct” in the Mine Plan simulation.

[0109] When a dig unit 111 is at a source 103, that means that trucks 113 can be loaded there, and a dig unit 111 can spot (or load) a single truck 113 at time. When the dig unit 111 is “sleeping” (not available) it is unable to spot or load a truck 113. So, there is a global loading queue of trucks 113 that are waiting for a dig unit 111 , since trucks are assumed in the Mine Plan simulation to be able to “teleport” to dig units 111. So, when a dig unit 111 wakes up, it checks the global loading queue of idle trucks 113 and informs them that one of them can visit this dig unit 111.Charging Stations

[0110] Charging stations 110 (chargers) are only able to spot (connect plus disconnect time to charge) or charge a single truck 113 at a time, and so may have a queue of trucks 113 waiting for each charger 110 since each charger 110 is associated with an extra amount of travel time to visit it. Chargers 110 are also where battery swaps (of truck batteries at end of life) happen, however a charger 110 is able to simultaneously charge a single truck 113 and swap any number of batteries, so there is considered to be no queue for trucks 113 requiring battery swaps.

[0111] There are roughly two modes for charging a truck, fixed time and fixed rate, where both of these are affected by how many times the current battery has been charged (the ‘charge number’). The charger 110 has an efficiency that is calculated as:Charger Efficiency = Max To Battery Power / Associated Grid Power.

[0112] In fixed time, a Recharge Time is specified for the current charge number, in which case that will be used to calculate a charge rate via:Battery Power = Difference between target state of charge and current state of charge / Recharge Time

[0113] This is then limited by:Maximum power that can be supplied by charger (Max To Battery Power) which is then the charge rate that will be used in the Mine Plan simulation.

[0114] In fixed rate mode, the battery power is simply the smaller of the maximum rate of power that the truck battery can accept or the maximum rate of power that the charger can supply.

[0115] When the charger is “sleeping” (not available), it is unable to spot or charge any trucks, it is also unable to swap any batteries. If a battery is mid-swap when the charger goes to sleep (not available), the battery swap is paused and will resume when the charger has awoken.

[0116] Particular arrangements of the Mine Plan simulation include a global charge queue of trucks 113 that were unable to find a charger 110 they can use, and so, when a charger 110 wakes up, it will check this global charge queue to priorities those trucks 113 that have been waiting in the global charge queue the longest.T rucks

[0117] When a truck 113 wakes up from sleeping (not available), it finds a dig unit 111 at an active source 103 to visit or enters an idle state. If it finds a dig unit 111 then, in the Mine Plan simulation, it will “teleport” to that dig unit 111 , spot at it, get loaded at it, drive to the payload's destination 120, spot at the dump, perform the dump, and then travel back to the source 103 where it was loaded from.

[0118] Then the truck 103 considers its state of charge, and if it needs to recharge it will try to find a charger it can visit. If it fails to find one, it “turns off” and enters an idle state until it can. Otherwise, it “teleports” into the charging queue of a charger 110, and when it is its turn, it will spot at the charger 110, charge and then travel the extra distance associated with visiting that charger 110 while traveling from that source 103 to its next destination.

[0119] If the truck 113 goes to sleep (not available) while in a charger's queue, it will exit the charge queue to make way for other trucks 113 and then when it wakes it will re-enter the queue of the same charging station 110. If the charger 110 goes to sleep (not available) while the truck 113 is queuing, the truck 113 will reassess the next available charging station and is simulated to teleport to another charger's queue with trucks first in the charger's queue first reallocated to preserve order.

[0120] If the truck's battery has reached end of life it will teleport to a charger and start performing a battery swap operation.

[0121] If the truck 113 does not need to charge / replace its battery, or when it has finished charging / replacing its battery, it will try to pick the next dig unit 111 for it to visit and repeats the cycle.

[0122] When the truck 113 is “sleeping” (not available), it is unable to spot or load at a dig unit 111 , nor spot or charge at a charger 110. However, the truck 113 can have its battery replaced, since the truck isn't actually running for this battery replacement operation.

[0123] The way a truck 113 picks a dig unit 111 in the Mine Plan simulation is by considering all idle dig units 111 it could visit, and that it can finish loading at before the dig unit 111 goes to sleep (not available), and then return to the source 103 before itself goes to sleep. The truck 1 13 will pick the dig unit 111 with the smallest number of truck types that are eligible to visit the digunit 111 at its current source 103. This is to prevent a situation where a source 103 that can use multiple truck types overuses all the trucks at the expense of a source 103 that is only eligible to use a smaller number of truck types.

[0124] As it is impossible to know the future, the Mine Plan simulation is configured to include consideration for interruptions, including:• Truck 113 is loading at dig unit 111 and either the truck or dig unit wants to go to sleep, which has flow on effects for the truck traveling; or• T ruck 113 is charging at a charger 110 and either the truck or charger wants to go to sleep (not available).

[0125] For these cases, the Mine Plan simulation is configured to complete the current action (loading + delivery, charging, etc..) and then sleep (not available) afterwards, while adjusting future sleep rates to try account for this.

[0126] Exceptions to these interruption states can also be included in the Mine Plan simulation, for example:• Trucks 113 undergoing a battery replacement, since these could be very long, this only depends on the charger 110 being awake, and so is simply paused while the charger 110 is asleep (not available).

[0127] Further arrangements of the Mine Plan simulation may optionally include an element of randomness in the simulation configuration. Including randomness in the Mine Plan simulation allows the simulation to be run with a different set of random numbers, to observe how the outputs of the Mine Plan simulation are affected. The random numbers are deterministic, so that, given a specific random seed and the same input parameters, the simulation output will always be the same.

[0128] The following properties of the simulation can optionally be modified by the addition of randomness to the Mine Plan simulation:• which days or parts of days the trucks / dig unit / chargers sleep for (see earlier description);• the transaction type a dig unit will next use as a source (weighted by the total amount of work to do for that transaction type).Mine Plan simulation Outputs

[0129] The Mine Plan simulation generated by simulation module 200 of the present embodiments provides highly detailed simulated data of the mine facility operations according to the Mine Plan, for example, how the power / energy demand varies in short term intervals (minutes)for one mine, see for example output visualisation of a Mine Plan vs Simulated tonnes delivered by the simulated Mine Plan shown in Figure 4A, simulated average charging station queue and travel times to charging station of Figure 4B; and simulated Peak Power vs Average Power required by the mine facility as shown in Figure 4C. The simulation data from simulation module 200 can then optionally be further processed to provide recommendations to the mine operator regarding the average and peak power load requirements for operation of the mine and enable to recommendation of necessary power generation and charging infrastructure required for operation of the mine facility.Implementation Example — Hardware Overview

[0130] According to one embodiment, the techniques described herein are implemented by at least one computing device 500. The techniques may be implemented in whole or in part using a combination of at least one server computer and / or other computing devices that are coupled using a network, such as a packet data network. The computing devices may be hard-wired to perform the techniques, or may include digital electronic devices such as at least one application-specific integrated circuit (ASIC) or field programmable gate array (FPGA) that is persistently programmed to perform the techniques, or may include at least one general purpose hardware processor programmed to perform the techniques pursuant to program instructions in firmware, memory, other storage, or a combination. Such computing devices may also combine custom hard-wired logic, ASICs, or FPGAs with custom programming to accomplish the described techniques. The computing devices may be server computers, workstations, personal computers, portable computer systems, handheld devices, mobile computing devices, wearable devices, body mounted or implantable devices, smartphones, smart appliances, internetworking devices, autonomous or semi-autonomous devices such as robots or unmanned ground or aerial vehicles, any other electronic device that incorporates hard-wired and / or program logic to implement the described techniques, one or more virtual computing machines or instances in a data centre, and / or a network of server computers and / or personal computers.

[0131] Figure 5 is a block diagram that illustrates an example computer system with which an embodiment may be implemented. In the example of Figure 5, a computer system 500 and instructions for implementing the disclosed technologies in hardware, software, or a combination of hardware and software, are represented schematically, for example as boxes and circles, at the same level of detail that is commonly used by persons of ordinary skill in the art to which this disclosure pertains for communicating about computer architecture and computer systems implementations.

[0132] Computer system 500 includes an input / output (I / O) subsystem which may include a I / O subsystem bus 504 and / or other communication mechanism(s) for communicating informationand / or instructions between the components of the computer system 500 over electronic signal paths. The I / O subsystem bus 504 may include an I / O controller 530, a memory controller and at least one I / O port. The electronic signal paths are represented schematically in the drawings, for example as lines, unidirectional arrows, or bidirectional arrows.

[0133] At least one hardware processor 502 is coupled to I / O subsystem bus 504 for processing information and instructions. Hardware processor 502 may include, for example, a general-purpose microprocessor or microcontroller and / or a special-purpose microprocessor such as an embedded system or a graphics processing unit (GPU) or a digital signal processor or ARM processor. Processor 502 may comprise an integrated arithmetic logic unit (ALU) or may be coupled to a separate ALU.

[0134] Computer system 500 includes one or more units of system memory 503, such as a main memory, which is coupled to I / O subsystem bus 504 for electronically digitally storing data and instructions to be executed by processor 502. Memory 503 may include volatile memory 506 such as various forms of random-access memory (RAM) or other dynamic storage device. RAM Memory 506 also may be used for storing temporary variables or other intermediate information during execution of instructions to be executed by processor 502. Such instructions, when stored in non-transitory computer-readable storage media accessible to processor 502, can render computer system 500 into a special-purpose machine that is customized to perform the operations specified in the instructions.

[0135] Computer system 500 further includes non-volatile memory such as read only memory (ROM) 505 or other static storage device coupled to I / O subsystem bus 504 for storing information and instructions for processor 502. The ROM 505 may include various forms of programmable ROM (PROM) such as erasable PROM (EPROM) or electrically erasable PROM (EEPROM). A unit of persistent storage 510 may include various forms of non-volatile RAM (NVRAM), such as FLASH memory, or solid-state storage, magnetic disk or optical disk such as CD-ROM or DVD-ROM, and may be coupled to I / O subsystem bus 504 for storing information and program instructions. Storage 510 is an example of a non-transitory computer-readable medium that may be used to store instructions and data which when executed by the processor 502 cause performing computer-implemented methods to execute the techniques herein.

[0136] The instructions in memory 503, ROM 508 or storage 510 may comprise one or more sets of instructions that are organized as modules, methods, objects, functions, routines, or calls. The instructions may be organized as one or more computer programs, operating system services, or application programs including mobile apps. The instructions may comprise an operating system and / or system software; one or more libraries to support multimedia, programming or other functions; data protocol instructions or stacks to implement TCP / IP, HTTPor other communication protocols; file format processing instructions to parse or render files coded using HTML, XML, JPEG, MPEG or PNG; user interface instructions to render or interpret commands for a graphical user interface (GUI), command-line interface or text user interface; application software such as an office suite, internet access applications, design and manufacturing applications, graphics applications, audio applications, software engineering applications, educational applications, games or miscellaneous applications. The instructions may implement a web server, web application server or web client. The instructions may be organized as a presentation layer, application layer and data storage layer such as a relational database system using structured query language (SQL) or no SQL, an object store, a graph database, a flat file system or other data storage.

[0137] Computer system 500 may be coupled via I / O subsystem bus 504 to at least one output device 512. In one embodiment, output device 512 is a digital computer display. Examples of a display that may be used in various embodiments include a touch screen display or a light-emitting diode (LED) display or a liquid crystal display (LCD) or an e-paper display. Computer system 500 may include other type(s) of output devices 512, alternatively or in addition to a display device. Examples of other output devices 512 include printers, ticket printers, plotters, projectors, sound cards or video cards, speakers, buzzers or piezoelectric devices or other audible devices, lamps or LED or LCD indicators, haptic devices, actuators or servos.

[0138] At least one input device 514 is coupled to I / O subsystem bus 504 for communicating signals, data, command selections or gestures to processor 502. Examples of input devices 514 include touch screens, microphones, still and video digital cameras, alphanumeric and other keys, keypads, keyboards, graphics tablets, image scanners, joysticks, clocks, switches, buttons, dials, slides, and / or various types of sensors such as force sensors, motion sensors, heat sensors, accelerometers, gyroscopes, and inertial measurement unit (IMU) sensors and / or various types of transceivers such as wireless, such as cellular or Wi-Fi, radio frequency (RF) or infrared (IR) transceivers and Global Positioning System (GPS) transceivers.

[0139] An input device 514 may be a touchpad, a mouse, a trackball, or cursor direction keys for communicating direction information and command selections to processor 502 and for controlling cursor movement on display 534. The input device may have at least two degrees of freedom in two axes, a first axis (e.g., x) and a second axis (e.g., y), that allows the device to specify positions in a plane. Another type of input device is a wired, wireless, or optical control device such as a joystick, wand, console, steering wheel, pedal, gearshift mechanism or other type of control device. Input device 514 I / O subsystem may include a combination of multiple different input devices, such as a video camera and a depth sensor.

[0140] In another embodiment, computer system 500 may comprise an internet of things (loT) device in which one or more of the output devices 512, or input devices 514 are omitted. Or, in such an embodiment, the input device 514 may comprise one or more cameras, motion detectors, thermometers, microphones, seismic detectors, other sensors or detectors, measurement devices or encoders and the output device 512 may comprise a special-purpose display such as a single-line LED or LCD display, one or more indicators, a display panel, a meter, a valve, a solenoid, an actuator or a servo.

[0141] When computer system 500 is a mobile computing device, input device 514 may comprise a global positioning system (GPS) receiver coupled to a GPS module that is capable of triangulating to a plurality of GPS satellites, determining and generating geo-location or position data such as latitude-longitude values for a geophysical location of the computer system 500. Output device 512 may include hardware, software, firmware and interfaces for generating position reporting packets, notifications, pulse or heartbeat signals, or other recurring data transmissions that specify a position of the computer system 500, alone or in combination with other application-specific data, directed toward host 524 or server 530.

[0142] Computer system 500 may implement the techniques described herein using customized hard-wired logic, at least one ASIC or FPGA, firmware and / or program instructions or logic which when loaded and used or executed in combination with the computer system causes or programs the computer system to operate as a special-purpose machine. According to one embodiment, the techniques herein are performed by computer system 500 in response to processor 502 executing at least one sequence of at least one instruction contained in main memory 506. Such instructions may be read into main memory 506 from another storage medium, such as storage HDD 511. Execution of the sequences of instructions contained in main memory 506 causes processor 502 to perform the process steps described herein. In alternative embodiments, hard-wired circuitry may be used in place of or in combination with software instructions.

[0143] The term “storage media” as used herein refers to any non-transitory media that store data and / or instructions that cause a machine to operation in a specific fashion. Such storage media may comprise non-volatile media and / or volatile media. Non-volatile media includes, for example, optical or magnetic disks, such as storage 510. Volatile media includes dynamic memory, such as memory 506. Common forms of storage media include, for example, a hard disk, solid state drive, flash drive, magnetic data storage medium, any optical or physical data storage medium, memory chip, or the like.

[0144] Storage media is distinct from but may be used in conjunction with transmission media. Transmission media participates in transferring information between storage media. For example, transmission media includes coaxial cables, copper wire and fiber optics, including thewires that comprise a I / O subsystem bus 504. Transmission media can also take the form of acoustic or light waves, such as those generated during radio-wave and infra-red data communications.

[0145] Various forms of media may be involved in carrying at least one sequence of at least one instruction to processor 502 for execution. For example, the instructions may initially be carried on a magnetic disk or solid-state drive of a remote computer. The remote computer can load the instructions into its dynamic memory and send the instructions over a communication link such as a fiber optic or coaxial cable or telephone line using a modem. A modem or router local to computer system 500 can receive the data on the communication link and convert the data to a format that can be read by computer system 500. For instance, a receiver such as a radio frequency antenna or an infrared detector can receive the data carried in a wireless or optical signal and appropriate circuitry can provide the data to I / O subsystem such as placing the data on I / O subsystem bus 504. I / O subsystem bus 504 carries the data to memory 506, from which processor 502 retrieves and executes the instructions. The instructions received by memory 506 may optionally be stored on storage 511 either before or after execution by processor 502.

[0146] Computer system 500 also includes a communication interface 518 coupled to I / O subsystem bus 504. Communication interface 518 provides a two-way data communication coupling to network link(s) 520 that are directly or indirectly connected to at least one communication networks, such as a network 522 or a public or private cloud on the Internet. For example, communication interface 518 may be an Ethernet networking interface, integrated-services digital network (ISDN) card, cable modem, satellite modem, or a modem to provide a data communication connection to a corresponding type of communications line, for example an Ethernet cable or a metal cable of any kind or a fiber-optic line or a telephone line. Network 522 broadly represents a local area network (LAN), wide-area network (WAN), campus network, internetwork or any combination thereof. Communication interface 518 may comprise a LAN card to provide a data communication connection to a compatible LAN, or a cellular radiotelephone interface that is wired to send or receive cellular data according to cellular radiotelephone wireless networking standards, or a satellite radio interface that is wired to send or receive digital data according to satellite wireless networking standards. In any such implementation, communication interface 518 sends and receives electrical, electromagnetic or optical signals over signal paths that carry digital data streams representing various types of information.

[0147] Network link 520 typically provides electrical, electromagnetic, or optical data communication directly or through at least one network to other data devices, using, for example, satellite, cellular, Wi-Fi, or BLUETOOTH technology. For example, network link 520 may provide a connection through a network 522 to a host computer 524.

[0148] Furthermore, network link 520 may provide a connection through network 522 or to other computing devices via internetworking devices and / or computers that are operated by an Internet Service Provider (ISP) 526. ISP 526 provides data communication services through a world-wide packet data communication network represented as internet 528. A server computer 530 may be coupled to internet 528. Server 530 broadly represents any computer, data centre, virtual machine or virtual computing instance with or without a hypervisor, or computer executing a containerized program system such as DOCKER or KUBERNETES. Server 530 may represent an electronic digital service that is implemented using more than one computer or instance and that is accessed and used by transmitting web services requests, uniform resource locator (URL) strings with parameters in HTTP payloads, API calls, app services calls, or other service calls. Computer system 500 and server 530 may form elements of a distributed computing system that includes other computers, a processing cluster, server farm or other organization of computers that cooperate to perform tasks or execute applications or services. Server 530 may comprise one or more sets of instructions that are organized as modules, methods, objects, functions, routines, or calls. The instructions may be organized as one or more computer programs, operating system services, or application programs including mobile apps. The instructions may comprise an operating system and / or system software; one or more libraries to support multimedia, programming or other functions; data protocol instructions or stacks to implement TCP / IP, HTTP or other communication protocols; file format processing instructions to parse or render files coded using HTML, XML, JPEG, MPEG or PNG; user interface instructions to render or interpret commands for a graphical user interface (GUI), command-line interface or text user interface; application software such as an office suite, internet access applications, design and manufacturing applications, graphics applications, audio applications, software engineering applications, educational applications, games or miscellaneous applications. Server 530 may comprise a web application server that hosts a presentation layer, application layer and data storage layer such as a relational database system using structured query language (SQL) or no SQL, an object store, a graph database, a flat file system or other data storage.

[0149] Computer system 500 can send messages and receive data and instructions, including program code, through the network(s), network link 520 and communication interface 518. In the Internet example, a server 530 might transmit a requested code for an application program through Internet 528, ISP 526, local network 522 and communication interface 518. The received code may be executed by processor 502 as it is received, and / or stored in storage 511 , or other non-volatile storage for later execution.

[0150] The execution of instructions as described in this section may implement a process in the form of an instance of a computer program that is being executed, and consisting of program code and its current activity. Depending on the operating system (OS), a process may be madeup of multiple threads of execution that execute instructions concurrently. In this context, a computer program is a passive collection of instructions, while a process may be the actual execution of those instructions. Several processes may be associated with the same program; for example, opening up several instances of the same program often means more than one process is being executed. Multitasking may be implemented to allow multiple processes to share processor 502. While each processor 502 or core of the processor executes a single task at a time, computer system 500 may be programmed to implement multitasking to allow each processor to switch between tasks that are being executed without having to wait for each task to finish. In an embodiment, switches may be performed when tasks perform input / output operations, when a task indicates that it can be switched, or on hardware interrupts. Time-sharing may be implemented to allow fast response for interactive user applications by rapidly performing context switches to provide the appearance of concurrent execution of multiple processes simultaneously. In an embodiment, for security and reliability, an operating system may prevent direct communication between independent processes, providing strictly mediated and controlled inter-process communication functionality.

[0151] The term “cloud computing” is generally used herein to describe a computing model which enables on-demand access to a shared pool of computing resources, such as computer networks, servers, software applications, and services, and which allows for rapid provisioning and release of resources with minimal management effort or service provider interaction.

[0152] A cloud computing environment (sometimes referred to as a cloud environment, or a cloud) can be implemented in a variety of different ways to best suit different requirements. For example, in a public cloud environment, the underlying computing infrastructure is owned by an organization that makes its cloud services available to other organizations or to the general public. In contrast, a private cloud environment is generally intended solely for use by, or within, a single organization. A community cloud is intended to be shared by several organizations within a community; while a hybrid cloud comprises two or more types of cloud (e.g., private, community, or public) that are bound together by data and application portability.

[0153] Generally, a cloud computing model enables some of those responsibilities which previously may have been provided by an organization's own information technology department, to instead be delivered as service layers within a cloud environment, for use by consumers (either within or external to the organization, according to the cloud's public / private nature). Depending on the particular implementation, the precise definition of components or features provided by or within each cloud service layer can vary, but common examples include Software as a Service (SaaS), in which consumers use software applications that are running upon a cloud infrastructure, while a SaaS provider manages or controls the underlying cloud infrastructure and applications. Platform as a Service (PaaS), in which consumers can use software programminglanguages and development tools supported by a PaaS provider to develop, deploy, and otherwise control their own applications, while the PaaS provider manages or controls other aspects of the cloud environment (i.e., everything below the run-time execution environment). Infrastructure as a Service (laaS), in which consumers can deploy and run arbitrary software applications, and / or provision processing, storage, networks, and other fundamental computing resources, while an laaS provider manages or controls the underlying physical cloud infrastructure (i.e., everything below the operating system layer). Database as a Service (DBaaS) in which consumers use a database server or Database Management System that is running upon a cloud infrastructure, while a DBaaS provider manages or controls the underlying cloud infrastructure, applications, and servers, including one or more database servers.Embodiments

[0154] Reference throughout this specification to “one embodiment”, “an embodiment”, “one arrangement” or “an arrangement” means that a particular feature, structure or characteristic described in connection with the embodiment / arrangement is included in at least one embodiment / arrangement of the present invention. Thus, appearances of the phrases “in one embodiment / arrangement” or “in an embodiment / arrangement” in various places throughout this specification are not necessarily all referring to the same embodiment / arrangement, but may. Furthermore, the particular features, structures or characteristics may be combined in any suitable manner, as would be apparent to one of ordinary skill in the art from this disclosure, in one or more embodiments / arrangements.

[0155] Similarly it should be appreciated that in the above description of example embodiments / arrangements of the invention, various features of the invention are sometimes grouped together in a single embodiment / arrangement, figure, or description thereof for the purpose of streamlining the disclosure and aiding in the understanding of one or more of the various inventive aspects. This method of disclosure, however, is not to be interpreted as reflecting an intention that the claimed invention requires more features than are expressly recited in each claim. Rather, as the following claims reflect, inventive aspects lie in less than all features of a single foregoing disclosed embodiment / arrangement. Thus, the claims following the Detailed Description are hereby expressly incorporated into this Detailed Description, with each claim standing on its own as a separate embodiment / arrangement of this invention.

[0156] Furthermore, while some embodiments / arrangements described herein include some but not other features included in other embodiments / arrangements, combinations of features of different embodiments / arrangements are meant to be within the scope of the invention, and form different embodiments / arrangements, as would be understood by those in the art. For example,in the following claims, any of the claimed embodiments / arrangements can be used in any combination.Specific Details

[0157] In the description provided herein, numerous specific details are set forth. However, it is understood that embodiments of the invention may be practiced without these specific details. In other instances, well-known methods, structures and techniques have not been shown in detail in order not to obscure an understanding of this description.Terminology

[0158] In describing the preferred embodiment of the invention illustrated in the drawings, specific terminology will be resorted to for the sake of clarity. However, the invention is not intended to be limited to the specific terms so selected, and it is to be understood that each specific term includes all technical equivalents which operate in a similar manner to accomplish a similar technical purpose. Terms such as “forward”, “rearward”, “radially”, “peripherally”, “upwardly”, “downwardly”, and the like are used as words of convenience to provide reference points and are not to be construed as limiting terms.Different Instances of Objects

[0159] As used herein, unless otherwise specified the use of the ordinal adjectives “first”, “second”, “third”, etc., to describe a common object, merely indicate that different instances of like objects are being referred to, and are not intended to imply that the objects so described must be in a given sequence, either temporally, spatially, in ranking, or in any other manner.Comprising and Including

[0160] In the claims which follow and in the preceding description of the invention, except where the context requires otherwise due to express language or necessary implication, the word “comprise” or variations such as “comprises” or “comprising” are used in an inclusive sense, i.e., to specify the presence of the stated features but not to preclude the presence or addition of further features in various embodiments of the invention.

[0161] Any one of the terms: “including” or “which includes” or “that includes” as used herein is also an open term that also means “including at least” the elements / features that follow the term, but not excluding others. Thus, including is synonymous with and means comprising.Scope of Invention

[0162] Thus, while there has been described what are believed to be the preferred arrangements of the invention, those skilled in the art will recognize that other and further modifications may be made thereto without departing from the spirit of the invention, and it is intended to claim all such changes and modifications as fall within the scope of the invention. Functionality may be added or deleted from the block diagrams and operations may be interchanged among functional blocks. Steps may be added or deleted to methods described within the scope of the present invention.

[0163] Although the invention has been described with reference to specific examples, it will be appreciated by those skilled in the art that the invention may be embodied in many other forms.Industrial Applicability

[0164] It will be appreciated that the methods / apparatus / devices / systems described / illustrated above at least substantially provide systems and methods for precise predictions of the grid power / energy variability and charging requirement of a fully electric feet of mining equipment.

[0165] The Mine Plan simulation systems and methods described herein, and / or shown in the drawings, are presented by way of example only and are not limiting as to the scope of the invention. Unless otherwise specifically stated, individual aspects and components of the Mine Plan simulation systems and methods may be modified, or may have been substituted therefore known equivalents, or as yet unknown substitutes such as may be developed in the future or such as may be found to be acceptable substitutes in the future. The Mine Plan simulation systems and methods may also be modified for a variety of applications while remaining within the scope and spirit of the claimed invention, since the range of potential applications is great, and since it is intended that the present Mine Plan simulation systems and methods be adaptable to many such variations.

Claims

CLAIMS:1 . A facility for predicting on site electric power requirements for maintaining a fully electric fleet of vehicles in a mining operation to ensure sustainable electric operations, the facility comprising: a server comprising a communications module configured to receive data and to transmit load management instructions; a plurality of electrical charging stations; and a plurality of electric vehicles configured to be recharged by a selected electrical charging station; wherein the server comprises a processor coupled with non-volatile memory, the non-volatile memory storing processing instructions that, when executed by the processor, causes the processor to: simulate a total electrical power demand of the mine site due to the plurality of cabled mine equipment and the plurality of electric vehicles for each electric vehicle and each charging station within the facility over a prescribed period; thereby to simulate and determine an energy storage capacity requirement of the charging stations of the facility through the prescribed period; thereby to forecast the electrical load management needs of the facility through the prescribed period.

2. A facility comprising: a server comprising a communications module configured to receive data and to transmit load management instructions; a plurality of electrical charging stations comprising: charging station communication module configured for transmitting data to the server including an energy storage level of the charging station; one or more charging outlets; and a plurality of cabled electrical mine machines; a plurality of electric vehicles configured to be recharged by a selected electrical charging station, each of the plurality of electric vehicles comprising: one or more rechargeable batteries; charging cable adapted for connection to one of the one or more charging outlet; a battery charge sensor; and vehicle communication module transmitting data to the server including a charge state of the one or more rechargeable batteries; wherein:the charging station communications module is further configured to transmit queue data to the server with respect to a plurality of the electric vehicles queueing at the charging station to be recharged; and the server further comprises a processor coupled with non-volatile memory, the non-volatile memory storing processing instructions that, when executed by the processor, causes the processor to: simulate a total electrical power demand of the mine site due to the plurality of cabled mine equipment and the plurality of electric vehicles; simulate a battery discharge rate of each of the electric vehicles; simulate a received data signal from said electric vehicles indicative of a low charge state; simulate a received data signal from said charging stations indicative of a charge state of the charging station and a queue state; compute an energy consumption requirement for an electric vehicle having a low charge state to determine a travel range to choose a charging station having sufficient electrical capacity to recharge the batteries of the electric vehicle; simulate directing the electric vehicle to the chosen charging station within the travel range of the electric vehicle; simulate the energy requirements for recharging of each of the electric vehicles in a queue corresponding to each of the charging stations; and repeat the simulations for each electric vehicle and each charging station within the facility over a prescribed period thereby to simulate and determine an energy storage capacity requirement of the charging stations of the facility through the prescribed period; thereby to forecast the electrical load management needs of the facility through the prescribed period.

3. The facility as claimed in Claim 1 , wherein the mine operation simulation is created using one or more input parameters chosen from a list that includes weather, EV charging requirements, EV queue management strategy, energy cost, pricing strategy, and end-user behaviour to minimise the operating costs.

4. The facility as claimed in Claim 1 , wherein an input to the mine operation simulation comprises a database including all mining movements within a Mine Plan which describes every activity in the ine Plan.

5. The facility as claimed in any one of the preceding claims, wherein simulating the energy requirements for recharging of each of the electric vehicles includes simulating the number of battery effective full cycles to end of battery life.

6. The facility as claimed in any one of the preceding claims, wherein the simulation assuming different charge rate characteristics at each stage of a charging cycle.

7. The facility as claimed in Claim 6, wherein the charge rate characteristics are different at each stage of a charging cycle.

8. A method for forecasting and simulating electrical load management needs of a facility, the facility comprising: a server comprising communications module configured to receive data and to transmit load management instructions; a plurality of electrical charging stations comprising: charging station communication module configured for transmitting data to the server including an energy storage level of the charging station; and a plurality of cabled electrical mine machines; a plurality of electric vehicles configured to be recharged by a selected electrical charging station, each of the plurality of electric vehicles comprising: one or more rechargeable batteries; a battery charge sensor; and vehicle communication module transmitting data to the server including a charge state of the one or more rechargeable batteries; wherein: the charging station communications module is further configured to transmit queue data to the server with respect to a plurality of the electric vehicles queueing at the charging station to be recharged; and the server further comprises a processor coupled with non-volatile memory, the non-volatile memory storing processing instructions that, when executed by the processor, causes the processor to: simulate a total electrical power demand of the mine site due to the plurality of cabled mine equipment and the plurality of electric vehicles; simulate a battery discharge rate of each of the electric vehicles; simulate a received data signal from said electric vehicles indicative of a low charge state; simulate a received data signal from said charging stations indicative of a charge state of the charging station and a queue state;compute an energy consumption requirement for an electric vehicle having a low charge state to determine a travel range to choose a charging station having sufficient electrical capacity to recharge the batteries of the electric vehicle; simulate directing the electric vehicle to the chosen charging station within the travel range of the electric vehicle; simulate the energy requirements for recharging of each of the electric vehicles in a queue corresponding to each of the charging stations; and repeat the simulations for each electric vehicle and each charging station within the facility over a prescribed period thereby to simulate and determine an energy storage capacity requirement of the charging stations of the facility through the prescribed period; thereby to forecast the electrical load management needs of the facility through the prescribed period.

9. The method as claimed in Claim 8, wherein the mine operation simulation is created using one or more input parameters chosen from a list that includes: weather;EV charging requirements;EV queue management strategy; energy cost; pricing strategy; and end-user behaviour to minimise the operating costs.

10. Apparatus for configuration and management of electric vehicle (EV) charging infrastructure in a mining operation, comprising:(i) a processor configured to receive input data and to execute computer program code instructions stored in a non-transitory memory wherein the processor, upon executing the program code instructions, executes a method comprising the steps of: receiving input data related to: parameters describing one or more EV charging stations; parameters describing a plurality of cabled electrical mine machines; and parameters describing one or more electric mining vehicles configured to be recharged by a selected charging station, each of the electric mining vehicles comprising: one or more rechargeable batteries; a battery charge sensor;vehicle communication module configured for transmitting data to the server including a charge state of the one or more rechargeable batteries; parameters describing one or more cabled electric mine equipment; power requirements during different states; power factor to understand grid requirements; and providing the input data to the memory;(ii) providing the input data to the processor configured to simulate the mining operation including the plurality of electric mobile mining machines to generate a mine operation simulation over a predetermined time period;(iii) producing a recommendation for electrical power charging requirements of the mine operation simulation based on one or more of: electric vehicle charge depletion characteristics; available charge capacity of each of the charging stations; instantaneous electric vehicle queue characteristics at each of the charging stations; vehicle travel time from a working location to a charging station; and electric vehicle mining charging time;(iv) producing a recommendation for electrical power requirements for cabled electrical machines based on one or more of: individual operating state of each asset in the min; number of cabled assets in the mine; and(v) utilising the mine operation simulation to validate the processor's recommendation in order to determine the characteristics of the charging infrastructure required for continuous mining operation.

11. The apparatus as claimed in Claim 10, wherein the mine operation simulation is created using one or more input parameters chosen from a list that includes: weather;EV charging requirements;EV queue management strategy; energy cost; pricing strategy; and end-user behaviour to minimise the operating costs.

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