Method and apparatus to determine arrangement for photovoltaic installation

Abstract

An apparatus and method for determining an optimised arrangement of a photovoltaic system for a geographic area are provided. Load data and solar irradiation data for the geographic area, and arrangements of pre-existing photovoltaic panels and potential arrangements for one or more additional photovoltaic panels, are acquired (201). Photovoltaic parameters are determined (202) based upon the arrangements of pre-existing photovoltaic panels and the potential arrangements for additional photovoltaic panels. Power consumption patterns based on the load data, and photovoltaic generation patterns based on the solar irradiation data, are determined (203). An objective function is determined (204) to meet load requirements with photovoltaic placement. The optimised arrangement of the photovoltaic system is determined (205) using the objective function and the photovoltaic parameters.

Description

[0001] Method and Apparatus to Determine Arrangement for Photovoltaic Installation

[0002] Field

[0003] Aspects of the present disclosure relate to photovoltaic generation, and the determination of an optimised arrangement for photovoltaic installation.

[0004] Background

[0005] Photovoltaic (PV) generation can at least partially cover loads in a geographic area with locally produced energy, reducing imports from the grid, as well as costs, and the associated carbon footprint.

[0006] However, PV generation patterns can be significantly misaligned with load patterns along the time axis. For example, with south-facing PV panels in a residential neighbourhood, PV generation could be stronger during midday, whereas the consumption is lower at that time, when many residents are at work or school. The loads increase in the late afternoon, at a time when PV generation for south-facing PV panels declines.

[0007] Thus, on one hand, west-facing panels might be better aligned with consumption patterns, but the overall PV generation for a panel with a west-facing orientation is smaller compared to a similar panel with a south-facing orientation. On the other hand, a south-facing panel generates more power, but at a time when it is less needed. Surplus power would need to be stored in a battery energy storage system (BESS), and utilized later to cut the peak demand for example.

[0008] Local PV generation is a key mechanism to provide green, sustainable power and to fight global warming. However, PV installation (e.g., orientation and location) at individual sites such as a home may be performed in a greedy and independent fashion, being suboptimal at a larger scale such as a microgrid or a substation area. Aspects herein overcome the aforementioned challenges, amongst others.

[0009] Summary

[0010] In a first exemplary aspect, there is provided a method of determining an optimised arrangement of a photovoltaic system for a geographic area, wherein the photovoltaic system comprises one or more photovoltaic panels, the method comprising: acquiring load data for the geographic area, solar irradiation data for the geographic area, arrangements of one or more pre-existing photovoltaic panels in the geographic area, and potential arrangements for one or more additional photovoltaic panels in the geographic area; determining photovoltaic parameters based upon the arrangements of preexisting photovoltaic panels and the potential arrangements for one or more additional photovoltaic panels; determining one or more power consumption patterns based on the load data, and one or more photovoltaic generation patterns based on the solar irradiation data; determining, based upon the one or more power consumption patterns and the one or more photovoltaic generation patterns, an objective function to meet load requirements with photovoltaic placement; determining the optimised arrangement of the photovoltaic system using the objective function and the photovoltaic parameters, wherein the optimised arrangement comprises an arrangement for photovoltaic panels to be installed in the geographic area to meet the load requirements; outputting the optimised arrangement of the photovoltaic system.

[0011] Optionally, the photovoltaic parameters comprise one or more of locations of the one or more pre-existing photovoltaic panels in the geographic area, orientations of the one or more pre-existing photovoltaic panels, and photovoltaic capacity of the one or more pre-existing photovoltaic panels.

[0012] Optionally, the photovoltaic parameters comprise one or more of potential locations for the one or more additional photovoltaic panels in the geographic area, potential orientations for the one or more additional photovoltaic panels, and potential photovoltaic capacity for the one or more additional photovoltaic panels.

[0013] Optionally, the photovoltaic parameters comprise one or more of location constraints for the one or more additional photovoltaic panels in the geographic area, orientation constraints for the one or more additional photovoltaic panels, and photovoltaic capacity constraints for the one or more additional photovoltaic panels.

[0014] Optionally, the load data comprises historic load data that comprises energy usage data from one or more substations for the geographic area as a function of time.

[0015] Optionally, the load data comprises energy meter data from one or more entities in the geographic area as a function of time.

[0016] Optionally, the solar irradiation data is historic solar irradiation that comprises solar irradiation as a function of time for the geographic area.

[0017] Optionally, the method further comprises: acquiring a pre-existing battery energy storage capacity for the geographic area; the photovoltaic parameters further comprise a required additional battery capacity for storing energy generated by photovoltaic panels; and the optimised arrangement further comprises an optimised battery energy storage capacity based upon the objective function and the photovoltaic parameters. Optionally, the one or more photovoltaic generation patterns comprise patterns of photovoltaic generation as a function of time for each potential combination of location, orientation and photovoltaic capacity for photovoltaic panels in the geographic area, based on the solar irradiation data.

[0018] Optionally, the one or more power consumption patterns comprise one or more patterns of electrical load for the geographic area as a function of time, and one or more patterns of peak energy demand as a function of time.

[0019] Optionally, the objective function comprises a combination of a first component and a second component, wherein: the first component is determined as a difference between the one or more patterns of electrical load and the corresponding one or more photovoltaic generation patterns as a function of time; and the second component is determined as a difference between the one or more patterns of peak energy demand and one or more patterns of available photovoltaic-generated energy at corresponding times.

[0020] Optionally, the method further comprises: acquiring historic stored energy level data comprising levels of energy stored in one or more battery energy stores as a function of time, wherein the stored energy is energy generated by the one or more photovoltaic panels and used to provide power in the geographic area; determining patterns of stored energy in the one or more battery energy stores, from the acquired historic stored energy data, as a function of time; and wherein the patterns of available photovoltaic-generated energy comprise a combination of the determined patterns of stored energy in the one or more battery energy stores, and corresponding photovoltaic generation patterns.

[0021] Optionally, the one or more power consumption patterns and / or the one or more photovoltaic generation patterns each comprise separate patterns for types of day. In a second exemplary aspect, there is provided an apparatus configured to determine an optimised arrangement of a photovoltaic system for a geographic area, wherein the photovoltaic system comprises one or more photovoltaic panels, and the apparatus comprises: a data acquisition module configured to acquire load data for the geographic area, solar irradiation data for the geographic area, arrangements of one or more pre-existing photovoltaic panels in the geographic area, and potential arrangements for one or more additional photovoltaic panels in the geographic area; a photovoltaic parameter determination module configured to determine photovoltaic parameters based upon the arrangements of pre-existing photovoltaic panels and the potential arrangements for one or more additional photovoltaic panels; a pattern determination module configured to determine one or more power consumption patterns based on the load data, and one or more photovoltaic generation patterns based on the solar irradiation data; an objective function determination module configured to determine, based upon the one or more power consumption patterns and the one or more photovoltaic generation patterns, an objective function to meet load requirements with photovoltaic placement; an optimised arrangement determination module configured to determine the optimised arrangement of the photovoltaic system using the objective function and the photovoltaic parameters, wherein the optimised arrangement comprises an arrangement for photovoltaic panels to be installed in the geographic area to meet the load requirements; and an output module configured to output the optimised arrangement of the photovoltaic system.

[0022] The second exemplary aspect can include the optional features of the first exemplary aspect. In a third exemplary aspect, there is provided a computer-readable medium comprising instructions that when executed by one or more processors cause the one or more processors to: acquire load data for the geographic area, solar irradiation data for the geographic area, arrangements of one or more pre-existing photovoltaic panels in the geographic area, and potential arrangements for one or more additional photovoltaic panels in the geographic area; determine photovoltaic parameters based upon the arrangements of preexisting photovoltaic panels and the potential arrangements for one or more additional photovoltaic panels; determine one or more power consumption patterns based on the load data, and one or more photovoltaic generation patterns based on the solar irradiation data; determine, based upon the one or more power consumption patterns and the one or more photovoltaic generation patterns, an objective function to meet load requirements with photovoltaic placement; determine the optimised arrangement of the photovoltaic system using the objective function and the photovoltaic parameters, wherein the optimised arrangement comprises an arrangement for photovoltaic panels to be installed in the geographic area to meet the load requirements; and output the optimised arrangement of the photovoltaic system.

[0023] The third exemplary aspect can include the optional features of the first exemplary aspect.

[0024] In a fourth exemplary aspect, there is provided a means for determining an optimised arrangement of a photovoltaic system for a geographic area, wherein the photovoltaic system comprises one or more photovoltaic panels, comprising: a means for acquiring load data for the geographic area, solar irradiation data for the geographic area, arrangements of one or more pre-existing photovoltaic panels in the geographic area, and potential arrangements for one or more additional photovoltaic panels in the geographic area; a means for determining photovoltaic parameters based upon the arrangements of pre-existing photovoltaic panels and the potential arrangements for one or more additional photovoltaic panels; a means for determining one or more power consumption patterns based on the load data, and one or more photovoltaic generation patterns based on the solar irradiation data; a means for determining, based upon the one or more power consumption patterns and the one or more photovoltaic generation patterns, an objective function to meet load requirements with photovoltaic placement; a means for determining the optimised arrangement of the photovoltaic system using the objective function and the photovoltaic parameters, wherein the optimised arrangement comprises an arrangement for photovoltaic panels to be installed in the geographic area to meet the load requirements; and a means for outputting the optimised arrangement of the photovoltaic system.

[0025] The fourth exemplary aspect can include the optional features of the first exemplary aspect.

[0026] Brief Description of Drawings

[0027] Examples of the disclosure are now described with reference to the drawings, in which:

[0028] Figure 1 is a block diagram of a system for determining an optimised arrangement of a PV system for a geographic area;

[0029] Figure 2 is a flow chart of a method of determining an optimised arrangement of a photovoltaic system for a geographic area; and Figure 3 is a high-level block diagram of an apparatus suitable for implementing various aspects of the disclosure.

[0030] Detailed Description

[0031] Typically, individual homeowners can choose between multiple PV orientation options (e.g., south-facing or west-facing) and typically choose an orientation independently and in isolation from other homeowners in the neighbourhood. This is suboptimal, wasteful and costly. For example, if all homeowners in a neighbourhood face their PV panels in the same direction (e.g., south), this can create a surplus of green power at certain times of the day, and an unsatisfied demand at other times of the days. Surplus green power would be wasted or otherwise it would need to be stored within expensive battery energy storage systems.

[0032] The present disclosure provides an apparatus and method that optimises the placement of PV panels and battery energy storage capacity within an area such as neighbourhood, a microgrid, a substation area, a building, or an industrial facility. This reduces the consumption of energy imported from the grid, reduces the peak demand, and reduces the capacity of battery energy storage systems required.

[0033] In a geographical area, multiple PV panels can be installed within local topology constraints (e.g., available locations for the installation of a PV panel, with features such as orientation, slope, clearance from obstacles, and maximum available area). The apparatus and method of this disclosure provide for deciding how to place PV panels and battery energy storage capacity for the geographic area to maximize the use of locally generated green energy, reduce the peak demand, and reduce the battery energy storage capacity needed. An optimised placement and orientation of PV panels is computed, as well as an optimised BESS capacity. It optimises the alignment between PV generation patterns and load patterns throughout the day at the level of the broader geographic area (e.g., neighbourhood), increasing the consumption of locally generated green energy and reducing the peak demand.

[0034] Figure 1 depicts a block diagram of a system for determining an optimised arrangement of a PV system for a geographic area.

[0035] The geographic area can be considered as an area in which power is supplied to one or more entities such as buildings, for example a neighbourhood, hospital or industrial complex. Such geographic areas can include areas supplied by a microgrid or one or more substations.

[0036] The system comprises an apparatus 107 for determining the optimised arrangement of the PV system for the geographic area, and can comprise an output means 115 by which an optimised layout plan for additional PV panels and battery energy stores can be output.

[0037] The geographic area can have one or more existing PV panels, and one or more existing battery energy stores. The apparatus 107 is configured to determine how and where additional PV panels can be added in the geographic area to meet energy demands in the geographic area, and can also be configured to determine what additional battery energy storage capacity should be introduced to meet the energy demands.

[0038] The apparatus 107 can acquire data relating to load requirements in the geographic area, solar irradiance in the geographic area, existing PV panels in the region, and potential arrangements for additional PV panels in the region. Data relating to existing battery energy stores can also be acquired. In some examples, the acquired data can be stored in a datastore 108.

[0039] The datastore 108 can be a means (e.g., computer storage) for storing the data that is acquired by the apparatus 107. In the example of Figure 1 , the datastore 108 is integrated into apparatus 107. In some other examples, the datastore could be a separate entity to the apparatus, such as a server, cloud storage, local computer storage, or any suitable type of database in communication with the apparatus, for example by a network. The load requirement data can be historic load requirements for the geographic area that are communicated to the apparatus 107 from one or more substations 101 (also referred to as transformers) and / or one or more energy meters 102 (such as advanced metering infrastructure, AMI, meters). Such load requirement data can include date / time parameters such that the load requirement data is indicative of load requirements as a function of time. Whilst only one substation 101 , and one energy meter 102, are shown in Figure 1 , the skilled person will appreciate that this is for conciseness and that any suitable number of substations and / or energy meters can be used that is greater than one.

[0040] The solar irradiance data can be historic solar irradiance data for the geographic area. This data can relate to the amount of solar radiation impinging on the area, and from which direction, as a function of date / time. This data can be communicated to the apparatus 107 from a solar irradiance data source 103. Examples of such a solar irradiance data source include: ‘everywhere. solar’ (https: / / everywhere. solar / ), ‘Solargis’ (https: / / solargis.com / ), and ‘European Commission - Photovoltaic Geographical Information System’ (https: / / re.jrc.ec.europa.eu / pvg_tools / en / ).

[0041] The existing PV panel data can be data defining the arrangement of PV panels that are already installed in the geographic area. The arrangement of a PV panel can be considered as the location of the panel and the orientation of the panel. The arrangement can also include the PV capacity at each location. In the context of the present disclosure, PV capacity can be considered as the nominal power of the PV device, or the peak power of the PV device which is sometimes referred to as ‘kilowatt-peak’ (kWp). The existing PV panel data can be communicated to the apparatus from an existing PV panel data source 104, such as a database.

[0042] The data on potential arrangements for additional PV panels can be data defining possible arrangements in which additional PV panels can be added in the geographic area. The arrangements in which additional PV panels can be added can be considered as locations for additional PV panels in the geographic area, as well as orientations for such additional PV panels. The potential arrangements can also include potential PV capacity that could be installed at each location, as well as other topology constraints such as slope, clearance from obstacles, and maximum available area at the location. This data can be sourced by surveying the geographic area for potential locations in which PV panels can be installed (for example, on rooftops or in open spaces). The data on potential arrangements for additional PV panels can be communicated to the apparatus 107 from a potential arrangements for additional PV panels data source 105, such as a database.

[0043] The data relating to existing battery energy stores can be data defining a number and / or storage capacity of battery storage units in the geographic area that are configured to store energy generated by one or more of the PV panels in the geographic area. The battery energy stores can also be referred to as battery energy storage systems. The data relating to existing battery energy stores can be communicated to the apparatus 107 from an existing battery energy store data source 106, such as a database.

[0044] The processes involved in retrieving the data from the datastore, determining the optimised layout plan for additional PV panels and battery energy stores, and outputting the optimised layout plan is discussed in more detail with regard to Figure 2.

[0045] The apparatus 107 can comprise various modules, as will be discussed in more detail with reference to Figure 2, for determining the optimised layout plan for additional PV panels and battery energy stores. These modules can include a data acquisition module 109, a photovoltaic parameter determination module 110, a pattern determination module 111 , an objective function determination module 112, an optimised arrangement determination module 113, and an output module 114. Whilst described as distinct modules, these can be embodied as a single module or groups of modules. For example, the module(s) can be realised as one or more processors executing instructions stored in computer storage.

[0046] The output means 115 can, for example, be a display or printer, or a communication channel (such as a network path or telecommunications connection) to another device. Turning to Figure 2, a flow chart is presented detailing a computer-implemented method of determining an optimised arrangement of a photovoltaic system for a geographic area, which can be executed using the apparatus of Figure 1 .

[0047] At step 201 , load data for the geographic area, solar irradiation data for the geographic area, arrangements of pre-existing photovoltaic panels in the geographic area, and potential arrangements for one or more additional photovoltaic panels in the geographic area, are acquired.

[0048] The data can be acquired by the apparatus 107, using the data acquisition module 109, and can be stored in the datastore 108. In some other arrangements, the data can be acquired by the datastore 108 (for example if the datastore is separate to the apparatus 107), and then acquired from the datastore 108 by the apparatus 107.

[0049] The load data for the geographic area can be considered historic load data of energy usage in the geographic area, and load patterns can be determined from this.

[0050] In more detail, at sub-step 201 a, acquiring the load data can comprise acquiring energy meter data from one or more entities (e.g., homes or buildings) in the geographic area as a function of time. This energy meter data can be acquired from one or more energy meters 102 (e.g., AMI meters) associated with entities in the geographic area, providing energy usage data for their respective entity in the geographic area.

[0051] In another sub-step (not shown in Figure 2), acquiring the load data can comprise acquiring energy usage data from one or more substations (or transformers) 101 for the geographic area as a function of time. This provides energy usage data for the entire geographic area served by the one or more substations 101 .

[0052] The combination of both substation data for the whole area and data on individual entities (e.g., homes) from energy meters associated with the entities is beneficial in that the PV placement and battery energy store capacity can be optimised for a single entity such as a home and also for the whole geographic area. At sub-step 201 b, the solar irradiation data for the geographic area is acquired. This data can be acquired from the solar irradiance data source 103. The solar irradiation data can be considered as historic solar irradiance data as a function of date / time. That is, the amount of light impinging on a location as a function of date / time. From this, solar irradiance patterns can be determined to provide the solar energy available at each location in the geographic area at different dates / times.

[0053] At sub-step 201 c, arrangements of pre-existing photovoltaic panels in the geographic area are acquired. This can be in the form of data acquired from the existing PV panel data source 104, as discussed earlier in this disclosure.

[0054] At sub-step 201 d, potential arrangements for one or more additional photovoltaic panels in the geographic area are acquired. This can be in the form of data acquired from the potential arrangements for additional PV panels data source 105, as discussed earlier in this disclosure.

[0055] In another sub-step (not shown in Figure 2), data relating to pre-existing battery energy stores (if present in the geographic area) can also be acquired, for example from the existing battery energy store data source 106. This data can be the pre-existing battery energy storage capacity for the geographic area, as discussed earlier in this disclosure.

[0056] At step 202, photovoltaic parameters are determined based upon the acquired data for the arrangements of pre-existing photovoltaic panels and the potential arrangements for one or more additional photovoltaic panels. The photovoltaic parameters can be defined by the photovoltaic parameter determination module 110, by accessing the data for the arrangements of pre-existing photovoltaic panels and the potential arrangements for one or more additional photovoltaic panels in the datastore 108.

[0057] The photovoltaic parameters can be considered as constraints, variables and constants that are defined for the determination of the optimised arrangement of the photovoltaic system to meet load requirements. Meeting load requirements can be considered a meeting the total load of the geographic area at a given time, or meeting a pre-defined portion of the total load of the geographic area with the remainder of the load met using energy from external sources (e.g., the grid), or providing enough PV-generated energy to minimise the energy needed from the external sources.

[0058] At sub-step 202a, the constants are defined. The photovoltaic parameters can comprise constants that include one or more of locations of the pre-existing photovoltaic panels in the geographic area, orientations of the pre-existing photovoltaic panels, and photovoltaic capacity of the pre-existing photovoltaic panels. The constants can be extracted from the data of the arrangements of pre-existing photovoltaic panels in the geographic area.

[0059] At sub-step 202b, the variables are defined. The photovoltaic parameters can comprise variables that include one or more of potential locations of additional photovoltaic panels in the geographic area, potential orientations of additional photovoltaic panels, and potential photovoltaic capacity of additional photovoltaic panels. The variables can depend on the data relating to the potential arrangements for one or more additional photovoltaic panels.

[0060] The photovoltaic parameters can also comprise a parameter for a required additional battery capacity for storing energy generated by photovoltaic panels. This variable can depend on the pre-existing battery energy storage capacity for the geographic area.

[0061] The variables can include decision variables, such as if a new PV is to be installed at a given combination of a location and an orientation, how much PV capacity should be installed (if any) at that location-orientation combination. Another decision variable can indicate the additional battery energy storage capacity needed (if any).

[0062] At sub-step 202c, the constraints are defined. The photovoltaic parameters can comprise constraints that include one or more of location constraints for additional photovoltaic panels in the geographic area, orientation constraints for additional photovoltaic panels, and photovoltaic capacity constraints for additional photovoltaic panels. The constraints can also include the size and the type of PV panels at each potential location, the maximum PV capacity to install, and others such as slope, clearance from obstacles, and maximum available area at the location.

[0063] At step 203, one or more power consumption patterns are determined based on the historic load data, and one or more photovoltaic generation patterns are determined based on the historic solar irradiation data. For example, these can include aggregate daily solar irradiation patterns, power consumption patterns, and PV generation patterns for the geographic area.

[0064] The one or more power consumption patterns can be determined by the pattern determination module 111 from the acquired load data in the datastore 108.

[0065] The one or more photovoltaic generation patterns can be determined by the pattern determination module 111 from the acquired solar irradiation data in the datastore 108.

[0066] The power consumption patterns can relate to how the load in the geographic area changes as a function of time. In an example, the power consumption patterns can comprise a pattern of electrical load as a function of time for the geographic area (a load pattern) which is determined at sub-step 203a, and a pattern of peak energy demand as a function of time for the geographic area (a peak demand pattern) which is determined at sub-step 203b. A load pattern can be considered as a discretized measurement of the load (i.e. , consumption) as a function time. The peak demand patten can be considered as a form of measuring the maximum value of the load over a given time interval (e.g., one month). The peak demand pattern can be, for example, computed from the total energy drawn in a period of time (e.g., 15 minutes) with the maximum then taken over the given time interval (e.g., one month).

[0067] The photovoltaic generation patterns are determined at sub-step 203c, and can comprise patterns of photovoltaic generation as a function of time for each potential combination of location, orientation and PV capacity for PV panels in the geographic area, based on the solar irradiation data. The one or more power consumption patterns and / or the photovoltaic generation pattern can each comprise separate patterns for types of day. Types of day can correspond to combinations of one or more of the season, the day of the week, and / or weekdays / weekends. For example, the seasonality can be split into winter, spring, summer and autumn, and the days can be differentiated as weekdays and weekend days, leading to eight combinations of type of day (winter weekday, winter weekend day, spring weekday, spring weekend day, summer week day, summer weekend day, autumn weekday, autumn weekend day), with patterns determined for each type of day.

[0068] In more detail, a pattern considers a discretization of the time in a day and provides a series of values, one at each discrete timestep. For example, a load pattern gives the power consumption value at each discrete timestep. In a simple scenario for a basic definition of a pattern, there is only one value at a given timestep. However, in other scenarios there can be an uncertainty-aware notion of a pattern, where instead of one value per timestep there is an interval of possible values, with a minimum value, a maximum value, and a confidence index (likelihood that an actual value in the future will fit within that interval).

[0069] Solar irradiation data patterns (i.e., comprised in I determined from the solar irradiation data) can be utilized to compute PV generation patterns for each potential combination of a location, orientation and PV capacity. This allows for the construction and evaluation of candidate solutions as will be discussed with reference to steps 204 and 205, wherein an optimisation problem is defined (steps 204 and 205) and solved with an optimisation engine (step 205). More specifically, the optimisation engine can internally explore and evaluate candidate solutions. In a candidate solution, zero or more potential locations for new PVs can be marked to have a new PV panel installed, and zero or more such potential locations can be marked not to have a new PV panel installed. For each location marked to have a PV panel installed, its individual PV generation patten computed at step 203 can be added to the total PV generation pattern, aggregated over all existing PVs and all new locations marked to have a new PV installed in the current candidate solution being explored. The apparatus can also be configured to acquire historic stored energy level data for energy stored in battery energy store(s) in the geographic area as a function of time that is generated by the PV panels and used to provide power in the geographic area. The pattern determination module can be configured to determine patterns of stored energy in the battery energy store(s), from the acquired historic stored energy data, as a function of time. These patterns can also comprise separate patterns for types of day.

[0070] At step 204, an objective function is determined to meet load requirements with photovoltaic placement based upon the one or more power consumption patterns and the one or more photovoltaic generation patterns.

[0071] The objective function can be determined by the objective function determination module 112.

[0072] In an example in which the aforementioned patterns are separated by types of day, an objective function can be determined for each type of day.

[0073] The objective function can be a combination of a first component and a second component. The first component and the second component can be discrete components. The objective function can be a weighted sum of the two components. Alternatively, the objective function can be a vector with two elements for a multi-objective pareto-optimal solution computation.

[0074] The first component, determined at sub-step 204a, can be a gap or difference between the one or more load patterns and the one or more corresponding photovoltaic generation patterns as a function of time.

[0075] The second component, determined at sub-step 204b, can be a difference between the one or more patterns of peak energy demand and patterns of the available PV-generated energy (i.e., the energy corresponding to power generated by a PV through conversion of solar energy to electric energy) at corresponding times. The available PV-generated energy can be the combination of energy generated by the pre-existing PV panels, as well as corresponding available stored energy in the one or more battery energy stores, as a function of time (if included in the geographic area). In other words, the patterns of available PV-generated energy can comprise a combination of the determined patterns of stored energy in the one or more battery energy stores, and corresponding photovoltaic generation patterns

[0076] That is, the first component can be computed as a gap between a load pattern and a PV generation pattern during a time interval such as one day. In a specific example, this can be achieved as follows: Compute the gap between load patterns and PV pattern with the following sub-steps: i) at discrete times aggregate the load on the entire geographic area and aggregate the PV generation on the entire geographic area; this defines the aggregated load and the aggregated PV generation patterns as (discrete) functions of time over the time interval considered (e.g., 24 hours); ii) the gap G(tz) at time is the difference between the aggregated load and the aggregated PV generation; iii) Component 1 in the objective function in the embodiment at hand is defined as

[0077] The second component relates to the peak external demand. That is, the difference between the peak consumption and the available energy generated by the PV panels in the geographic area (the sum of PV energy generated at that time, and the available PV-generated energy stored in the one or more battery energy stores at time time). In simplified example, battery storage before peak time is the accumulation of the PV surplus (vs the consumption) up to the peak time.

[0078] In some other examples, the objective function can comprise a combination of more than two components, or only one component.

[0079] At sub-step 204c, the objective function is defined as the combination of the first component and the second component.

[0080] At step 205, the optimised arrangement of the photovoltaic system is determined using the objective function and the photovoltaic parameters, wherein the optimised arrangement comprises an arrangement for photovoltaic panels to be installed in the geographic area to meet the load requirements. The optimised arrangement can be determined by the optimised arrangement determination module 113.

[0081] At sub-step 205a, the photovoltaic parameters (the aforementioned variables, constants and constraints), and the objective function, can be used to construct an optimisation problem instance.

[0082] At sub-step 205b, this optimisation problem instance can fed into an optimisation engine to solve the optimisation problem instance. Examples of such an optimisation engine can include ‘Gurobi’ and ‘CPLEX’. The optimisation engine can internally explore and evaluate candidate solutions. The candidate solutions can be determined by varying the variables such as the placement location and orientations of additional PV panels, as well as the capacity of additional PV panels, and any additional battery energy stores that are required, in the geographic area, to meet load requirements for the geographic area. The solution (i.e., the optimised arrangement) provides an optimised placement of new PV panels to be installed, and can also include additional battery capacity required, to meet load requirements. The solution can also include relocating and / or repositioning existing PV panels. In a candidate solution, zero or more potential locations for new PVs can be marked to have a new PV panel installed, and zero or more such potential locations are marked not to have a new PV panel installed.

[0083] The optimisation engine can be a domain-independent optimisation engine.

[0084] At step 206, the optimised arrangement of the photovoltaic system is output.

[0085] The optimised arrangement can be output using the output module 114.

[0086] At sub-step 206a, outputting the optimised arrangement can involve extracting the details of the new PVs (such as the location, orientation and capacity), and the additional battery energy store capacity, from the solution.

[0087] The output module can communicate the optimised arrangement to the output means, as already discussed. Using the output optimised arrangement, new PV panels and battery energy stores (if needed) can be installed in the geographic area to help meet load requirements for the geographic area.

[0088] Figure 3 depicts a high-level block diagram of an apparatus 300 suitable for implementing various aspects of the disclosure. Although illustrated in a single block, in other embodiments the apparatus 300 may also be implemented using parallel and distributed architectures. Thus, for example, various steps such as those illustrated in the methods described above by reference to Figure 2 may be executed using apparatus 300 sequentially, in parallel, or in a different order based on particular implementations. The apparatus 107 for determining the optimised arrangement of the PV system for the geographic area can be implemented in the form of apparatus 300.

[0089] According to an example, depicted in Figure 3, apparatus 300 comprises a printed circuit board 301 on which a communication bus 302 connects a processor 303 (e.g., a central processing unit "CPU"), a random access memory 304, a storage medium 311 , possibly an interface 305 for connecting a display 306, a series of connectors 307 for connecting user interface devices or modules such as a mouse or trackpad 308 and a keyboard 304, a wireless network interface 310 and / or a wired network interface 312. Depending on the functionality required, the apparatus may implement only part of the above. Certain modules of Figure 3 may be internal or connected externally, in which case they do not necessarily form integral part of the apparatus itself. E.g. display 306 may be a display that is connected to the apparatus only under specific circumstances, or the apparatus may be controlled through another device with a display, i.e. no specific display 306 and interface 305 are required for such an apparatus.

[0090] Memory 311 contains software code which, when executed by processor 303, causes the apparatus to perform the methods described herein. In an example, a detachable storage medium 313 such as a USB stick may also be connected. For example the detachable storage medium 313 can hold the software code to be uploaded to memory 311 . The processor 303 may be any type of processor such as a general purpose central processing unit ("CPU") or a dedicated microprocessor such as an embedded microcontroller or a digital signal processor ("DSP").

[0091] In addition, apparatus 300 may also include other components typically found in computing systems, such as an operating system, queue managers, device drivers, or one or more network protocols that are stored in memory 311 and executed by the processor 303.

[0092] Although aspects herein have been described with reference to particular embodiments, it is to be understood that these embodiments are merely illustrative of the principles and applications of the present disclosure. It is therefore to be understood that numerous modifications can be made to the illustrative embodiments and that other arrangements can be devised without departing from the spirit and scope of the disclosure as determined based upon the claims and any equivalents thereof.

[0093] For example, the data disclosed herein may be stored in various types of data structures which may be accessed and manipulated by a programmable processor (e.g., CPU or FPGA) that is implemented using software, hardware, or combination thereof.

[0094] It should be appreciated by those skilled in the art that block diagrams herein represent conceptual views of illustrative circuitry embodying the principles of the disclosure. Similarly, it will be appreciated that flow charts, flow diagrams, state transition diagrams, and the like represent various processes which may be substantially implemented by circuitry.

[0095] Each described function, engine, block, step can be implemented in hardware, software, firmware, middleware, microcode, or any suitable combination thereof. If implemented in software, the functions, engines, blocks of the block diagrams and / or flowchart illustrations can be implemented by computer program instructions I software code, which may be stored or transmitted over a computer- readable medium, or loaded onto a general purpose computer, special purpose computer or other programmable processing apparatus and / or system to produce a machine, such that the computer program instructions or software code which execute on the computer or other programmable processing apparatus, create the means for implementing the functions described herein.

[0096] In the present description, block denoted as "means configured to perform ..." (a certain function) shall be understood as functional blocks comprising circuitry that is adapted for performing or configured to perform a certain function. A means being configured to perform a certain function does, hence, not imply that such means necessarily is performing said function (at a given time instant). Moreover, any entity described herein as "means", may correspond to or be implemented as "one or more modules", "one or more devices", "one or more units", etc. When provided by a processor, the functions may be provided by a single dedicated processor, by a single shared processor, or by a plurality of individual processors, some of which may be shared. Moreover, explicit use of the term "processor" or "controller" should not be construed to refer exclusively to hardware capable of executing software, and may implicitly include, without limitation, digital signal processor (DSP) hardware, network processor, application specific integrated circuit (ASIC), field programmable gate array (FPGA), read only memory (ROM) for storing software, random access memory (RAM), and non-volatile storage. Other hardware, conventional or custom, may also be included. Their function may be carried out through the operation of program logic, through dedicated logic, through the interaction of program control and dedicated logic, or even manually, the particular technique being selectable by the implementer as more specifically understood from the context.

Claims

Claims1. A method of determining an optimised arrangement of a photovoltaic system for a geographic area, wherein the photovoltaic system comprises one or more photovoltaic panels, the method comprising: acquiring load data for the geographic area, solar irradiation data for the geographic area, arrangements of one or more pre-existing photovoltaic panels in the geographic area, and potential arrangements for one or more additional photovoltaic panels in the geographic area; determining photovoltaic parameters based upon the arrangements of pre-existing photovoltaic panels and the potential arrangements for one or more additional photovoltaic panels; determining one or more power consumption patterns based on the load data, and one or more photovoltaic generation patterns based on the solar irradiation data; determining, based upon the one or more power consumption patterns and the one or more photovoltaic generation patterns, an objective function to meet load requirements with photovoltaic placement; determining the optimised arrangement of the photovoltaic system using the objective function and the photovoltaic parameters, wherein the optimised arrangement comprises an arrangement for photovoltaic panels to be installed in the geographic area to meet the load requirements; and outputting the optimised arrangement of the photovoltaic system.

2. The method of claim 1 , wherein the photovoltaic parameters comprise one or more of locations of the one or more pre-existing photovoltaic panels in the geographic area, orientations of the one or more pre-existing photovoltaic panels, and photovoltaic capacity of the one or more preexisting photovoltaic panels.

3. The method of any preceding claim, wherein the photovoltaic parameters comprise one or more of potential locations for the one or more additional photovoltaic panels in the geographic area, potential orientations for theone or more additional photovoltaic panels, and potential photovoltaic capacity for the one or more additional photovoltaic panels.

4. The method of any preceding claim, wherein the photovoltaic parameters comprise one or more of location constraints for the one or more additional photovoltaic panels in the geographic area, orientation constraints for the one or more additional photovoltaic panels, and photovoltaic capacity constraints for the one or more additional photovoltaic panels.

5. The method of any preceding claim, wherein the load data comprises historic load data that comprises energy usage data from one or more substations for the geographic area as a function of time.

6. The method of any preceding claim, wherein the load data comprises energy meter data from one or more entities in the geographic area as a function of time.

7. The method of any preceding claim, wherein the solar irradiation data is historic solar irradiation that comprises solar irradiation as a function of time for the geographic area.

8. The method of any preceding claim, wherein the method further comprises: acquiring a pre-existing battery energy storage capacity for the geographic area; the photovoltaic parameters further comprise a required additional battery capacity for storing energy generated by photovoltaic panels; and the optimised arrangement further comprises an optimised battery energy storage capacity based upon the objective function and the photovoltaic parameters.

9. The method of any preceding claim, wherein the one or more photovoltaic generation patterns comprise patterns of photovoltaic generation as afunction of time for each potential combination of location, orientation and photovoltaic capacity for photovoltaic panels in the geographic area, based on the solar irradiation data.

10. The method of any preceding claim, wherein the one or more power consumption patterns comprise one or more patterns of electrical load for the geographic area as a function of time, and one or more patterns of peak energy demand as a function of time.

11. The method of claim 10, wherein the objective function comprises a combination of a first component and a second component, wherein: the first component is determined as a difference between the one or more patterns of electrical load and the corresponding one or more photovoltaic generation patterns as a function of time; and the second component is determined as a difference between the one or more patterns of peak energy demand and one or more patterns of available photovoltaic-generated energy at corresponding times.

12. The method of any preceding claim, wherein the method further comprises: acquiring historic stored energy level data comprising levels of energy stored in one or more battery energy stores as a function of time, wherein the stored energy is energy generated by the one or more photovoltaic panels and used to provide power in the geographic area; determining patterns of stored energy in the one or more battery energy stores, from the acquired historic stored energy data, as a function of time; and wherein the patterns of available photovoltaic-generated energy comprise a combination of the determined patterns of stored energy in the one or more battery energy stores, and corresponding photovoltaic generation patterns.

13. The method of any preceding claim, wherein the one or more power consumption patterns and / or the one or more photovoltaic generation patterns each comprise separate patterns for types of day.

14. An apparatus configured to determine an optimised arrangement of a photovoltaic system for a geographic area, wherein the photovoltaic system comprises one or more photovoltaic panels, and the apparatus comprises: a data acquisition module configured to acquire load data for the geographic area, solar irradiation data for the geographic area, arrangements of one or more pre-existing photovoltaic panels in the geographic area, and potential arrangements for one or more additional photovoltaic panels in the geographic area; a photovoltaic parameter determination module configured to determine photovoltaic parameters based upon the arrangements of preexisting photovoltaic panels and the potential arrangements for one or more additional photovoltaic panels; a pattern determination module configured to determine one or more power consumption patterns based on the load data, and one or more photovoltaic generation patterns based on the solar irradiation data; an objective function determination module configured to determine, based upon the one or more power consumption patterns and the one or more photovoltaic generation patterns, an objective function to meet load requirements with photovoltaic placement; an optimised arrangement determination module configured to determine the optimised arrangement of the photovoltaic system using the objective function and the photovoltaic parameters, wherein the optimised arrangement comprises an arrangement for photovoltaic panels to be installed in the geographic area to meet the load requirements; and an output module configured to output the optimised arrangement of the photovoltaic system.

15. A computer-readable medium comprising instructions that when executed by one or more processors cause the one or more processors to: acquire load data for the geographic area, solar irradiation data for the geographic area, arrangements of one or more pre-existing photovoltaic panels in the geographic area, and potential arrangements for one or more additional photovoltaic panels in the geographic area; determine photovoltaic parameters based upon the arrangements of pre-existing photovoltaic panels and the potential arrangements for one or more additional photovoltaic panels; determine one or more power consumption patterns based on the load data, and one or more photovoltaic generation patterns based on the solar irradiation data; determine, based upon the one or more power consumption patterns and the one or more photovoltaic generation patterns, an objective function to meet load requirements with photovoltaic placement; determine the optimised arrangement of the photovoltaic system using the objective function and the photovoltaic parameters, wherein the optimised arrangement comprises an arrangement for photovoltaic panels to be installed in the geographic area to meet the load requirements; and output the optimised arrangement of the photovoltaic system.

Images