Site Identification and Development for an Electrical Energy Facility

Abstract

A method selecting a location for a new generator or energy storage facility involves creating a computational model of an electrical grid 10 having network elements representing existing generators 1

Description

The present invention concerns the identification and development of sites for energy generation facilities. A major focus for reducing reliance on fossil fuels for electrical energy generation is the development of utility scale solar PV and Battery Energy Storage Systems (BESS) projects which, once constructed, will export power to transmission and distribution grids for sale in the electricity marketplace. As electricity generation is continually decentralized away from traditional generation centres, the direction of power flows on the grid are changing and it is becoming an increasingly complex problem to accommodate new solar, wind, BESS and High-Voltage Direct Current (HVDC) projects. Identifying where such projects can be implemented is an issue. Whilst certain software applications exist already for the computational modelling of distributed generation networks, such tools typically only allow analysis of the behaviour of an existing network. An example is provided by LIS2019372346, which discloses a power management system which models power generation from intermittent power sources (i.e. renewable energy) and power demands. Also, US2014025351 discloses a method for modelling the stress acting on a local grid under various conditions. Some scenarios include modelling the import / export scenarios for calculating local demand. However such tools are of limited value in assessing the viability of a variety of different options for potential new solar and BESS projects. Certain other software tools exist for determining optimal placement of renewable energy generation facilities based on weather conditions, i.e. to maximise the renewable energy potential. Furthermore, LIS2015372641 discloses a method for determining the optimal placement for a renewable power plant based upon variables including weather and local power demand. However, it has been found by the inventors that the capacity of electricity grids to accommodate the injection or absorption of power from facilities is a key aspect of the development process and ultimately of project success. The large pipelines of planned solar, wind, BESS and High-Voltage Direct Current (HVDC) interconnection projects mean that grid capacity is becoming an increasingly finite resource and identifying prospective locations where capacity is available with respect to existing grid infrastructure / assets is critical to the successful implementation of new projects. Accordingly, it is an aim of the invention to provide systems and methods by which suitable sites for renewable energy generation and / or energy storage facilities can be identified and developed for implementation. Statements of Invention According to an aspect of the invention there is a method comprising: creating a computational model of an electrical grid having a plurality of existing network elements representing generators, loads, transformers, power lines and nodes at which a plurality of the network elements are connected; running a power system network simulation using the computational model in which each network element has an associated voltage and the generators and loads each have an associated power capacity; wherein running the power system network simulation comprises: applying a new power source to the computational model; simulating whether the new power source causes one or more operational threshold for each of the existing network elements to be exceeded; and, repeating the simulating for the new power source for a plurality of different conditions of the computational model in which a different existing network element is inoperative. The method may comprise a method of identifying, assessing, approving or implementing changes to an electrical grid. The method may comprise a method of identifying, assessing, approving or implementing a new power source for the electrical grid, such as a new generator or energy storage facility. The new power source may comprise a renewable energy generation facility such as a solar, wind, tidal or other generation facility, e.g. including multiple individual generators in the form of a renewable energy farm. The method may allow one or more location of a new power source to be identified, assessed, approved or implemented. The location may be a geographical location and / or a location relative to existing network elements. The invention may allow the impact of a new power source on existing infrastructure and / or assets of the electrical grid to be explored. It will be appreciated that this represents a highly complex, multi-dimensional simulation that allows identification of potential sites for new power facilities with reference to existing infrastructure that has not been hitherto possible. The computational model may comprise a number, N, of network elements. Running the power system network simulation may comprise re-running the simulation for the new power source for a variety of different N-1 scenarios (e.g. exploring the impact of different existing network elements being inoperative). The method may comprise re-running the simulation for the new power source for a majority or all of the possible N-1 scenarios for the computational model, or a portion / subset thereof. The method may thus comprise testing multiple potential / credible network scenarios, e.g. to ensure the results presented are appropriately conservative. This may include N-1 contingency scenarios where network elements are removed from service to represent planned and / or unplanned outages. In some instances, N-2 contingency scenarios may be used. The method may comprise re-running the simulation for any / all possible N-1 scenarios within a predetermined vicinity of the new power source within the computational model. The predetermined vicinity my be determined by a spacing from the new power source in terms of a number of intervening elements. The method may comprise re-running the simulation for the new power source for some, a majority, or all of the possible N-1 scenarios for a specific element type (e.g. transformers, power lines, nodes, etc). The invention may allow interrogation or stress testing of the electrical grid for a new power source facility, e.g. in the form of a new renewable generation facility or energy storage facility on the grid, which can take account of different assets being offline. Embodiments of the invention may allow simulation of different possible power capacities for a new power source. The method may comprise the step of outputting a threshold or maximum power capacity for a new power source, e.g. a power capacity that can be accommodated at a defined location within the modelled electrical grid within the operational capability of the existing network elements. Embodiments of the invention may allow simulation of different possible locations for a new power source. The method may comprise the step of outputting an approved location / node for a new power source within the modelled electrical grid, e.g. a defined location / node within the modelled electrical grid at which the capability of the existing network elements can accommodate the new power source. The method may select locations having a power capacity above a predetermined threshold based on existing network elements and may re-run the simulation for a new power source for a variety of different N-1 scenarios at each of said selected locations individually. A location for a new power source in the network may comprise a node or transformer by which the new power source can be connected. The computational model may comprise a plurality of substations. The location may comprise a substation to which the new power source may be connected. The computational model and / or power flow simulation may comprise any, any combination, or all of the following data for network elements: an identifier; a voltage level (e.g. input and / or output voltage level); an impedance (e.g. and rating); generation capacity (existing or planned); location; load capacity. An available power capacity value may be determined and / or output for a plurality of the network elements of the computational model, e.g. for some or all of the network elements. An available power capacity value may be determined and / or output for network elements of one or more specified type, e.g. substation, node or transformer of the computational model of the electrical grid. An available power capacity value may be determined for each / every substation, node and / or transformer of the computational model. A list of network elements or locations and their respective power capacity value may be generated. The invention may allow identification and selection of a node, e.g. a node or substation, having sufficient power capacity for a new power source. The invention may specify a location, e.g. a node or substation, suitable for connection of a new power source of defined maximum power output. The invention may specify a power output threshold (e.g. a maximum power capacity) for a plurality of locations or all locations (e.g. nodes and / or substations) within the model. A power capacity value may be determined, measured and / or output in Megawatts (MW) of power. A minimum viable power import / export capacity may be established for a node, plurality of nodes or collectively for all nodes within a region of the electrical network, e.g. based on one or more N-1 scenarios. The method may comprise a step of checking all network elements are connected within the computational model. There may be one or more rules to determine an acceptable connection for each network element type. The method may determine / output an indication of locations in the electrical grid where the power capacity value is below a predetermined threshold. This may identify locations where the existing network elements (e.g. the exiting assets / infrastructure of the electrical grid) cannot accommodate a new power source and / or cannot accommodate one or more existing network element being inoperative. The method may comprise gathering data for the plurality of existing network elements for populating the computational model. The method may comprise inputting data for the plurality of existing network elements into the computational model. The data for the existing network elements may be gathered / input from publicly available sources. The data for the existing network elements may be gathered / input from any, any combination, or all, of: network asset information; generation capacity registers; and, electricity demand forecasts. The large pipelines of planned solar, wind, BESS and HVDC interconnection projects means that grid capacity is becoming an increasingly finite resource and identifying prospective locations where capacity is available is critical to the success of new projects. Accordingly the invention provides a technical contribution to the assessment and delivery of such projects by identifying viable locations for new facilities within the existing asset network. In some examples, the method may output an indication of proposed changes to existing network elements, e.g. to increase a power capacity value for one or more existing network element or location. Proposed changes could be ranked or scored, e.g. according to a magnitude of difficulty or cost associated with a proposed change. The running of the power system network simulation, e.g. including the repeating of the simulation for different conditions, may be automated. The process may be fully automated, e.g. to produce any of the results or outputs detailed herein with no user input required, once running of the simulation is started. This may beneficially avoid user intervention that could bring into question the validity of any findings. The computational model may take the form of generators, loads, transformers (substations) and nodes interconnected by power lines. Each end of a power line may terminate at one of the other network elements. The method may comprise a method of assessing an electrical grid or assessing modifications to an electrical grid. The running of the power system network simulation may comprise iteratively computing solutions to the power system network simulation and converging towards a final solution. Solutions may be iteratively generated for each of the plurality of different conditions, e.g. to converge to a solution for each different condition. According to a second aspect, there is provided a system corresponding to the method of the first aspect, the system comprising one or more processor comprising machine readable instructions for the control of the one or more processor to access the computational model and run the power system network simulation. The one or more processor may allow reading, inputting, creation and / or storage of the computational model. The one or more processor may run one or more software applications for creation / interrogation of the computational model and / or running the power system network simulation. The computational model may be output from a first software application and the simulation may be run using a second software application. The one or more processor may access public records to populate data fields for the computational model, e.g. automatically. According to a further aspect, there is provided a data carrier or data storage medium comprising machine readable instructions for the control of one or more computer processor to: create a computational model of an electrical grid having a plurality of existing network elements representing generators, loads, transformers, power lines and nodes at which a plurality of the network elements are connected; run a power system network simulation using the computational model in which each network element has an associated voltage and the generators and loads each have an associated power capacity; wherein running the power system network simulation comprises: applying a new power source to the computational model; simulating whether the new power source causes one or more operational threshold for each of the existing network elements to be exceeded; and, repeating the simulating for the new power source for a plurality of different conditions of the computational model in which a different existing network element is inoperative. The machine readable instructions may control the one or more processors to repeatedly add new power sources to the computational model of differing power capacity and / or at different locations within the computational model. Any optional feature defined herein as relating to any one aspect of the invention may be applied to any further aspect. It will be appreciated that any reference to an electrical grid used herein applies to a defined part or region of a wider electrical grid. It will appreciated that ‘substations’ as referred to herein may comprise any facility within the electrical network Detailed Description Workable embodiment of the invention are described in further detail below by way of example only with respect to the accompanying drawings, of which: Fig. 1 shows an example schematic of an electrical power grid; Fig. 2 shows an example graphical representation of a computational model of a portion of an existing electrical grid; Fig. 3 shows an example graphical representation of the computational model of Fig. 2 with a simulated new power source; Fig. 4 shows an example graphical representation of the computational model of Fig. 3 under stress testing with an element of the computational model out of service; and Fig. 5 shows an overview of a wider process in which the invention may be used for electrical grid capacity planning. In general terms, the disclosure herein concerns a bespoke method, system and associated simulation software for creating mathematical / computational models of electrical grid network regions and then simulates power flows for those regions over a wide range of operating scenarios to identify locations / areas where grid constraints exist and / or areas where available capacity exists for a new power source. This provides valuable visibility of the utilisation of grid assets and enables facility development activities in specific locations within the vicinity of viable connection points for a defined, new power source to the existing grid. Fig. 1 is provided as an outline of the general makeup of the electrical grid 10. Power sources can take the form of power plants 12, renewable energy facilities 14 and / or energy storage facilities 16. Power plants 12 and other generators may connect into an extra high voltage AC transmission network 18 (e.g. at 275 or 400 kW in the UK) via a step-up transformer 20. A distribution network 22 supplies end users 24, including domestic, commercial and industrial users. Transformers 26 are used to step down and up voltages between power sources, transmission, distribution and end users. Certain power sources may be connected via transformers 26 into the distribution network 22 which may operate at high voltage (e.g. at 11, 33 or 132 kV) but lower than the transmission network 18. DC power sources such as solar generators / farms, BESS and HVDC facilities may connect into the distribution 22 or transmission 18 networks via DC to AC inverters 28. The assets are connected by overhead or underground power lines. Although not shown for simplicity in Fig. 1 it will be appreciated that the grid comprises numerous junctions / branches at substations which may or may not also house transformers. As such the electrical grid comprises a vast number of assets operating at different voltage levels, all of which have maximum operating thresholds, e.g. in terms of voltage, power, temperature, amongst other operating parameters. There is proposed below a method of modelling the electrical grid to be able to propose and develop viable sites for new power sources within the complexity of the existing asset register. The process followed by working embodiments will be described blow in further detail with respect to the stages of: electricity grid model generation; simulation of power flows on the electricity grid model, including stress testing of the model and results output; - site selection, development and implementation of electrical generation or energy storage facility. Electrical Grid Model Generation The software application developed to create the computational model can convert publicly available network asset data, e.g. obtained from Distribution Network Operators (DNOs), to mathematical models for the network elements. The primary elements of the electricity grids to be modelled are: Nodes: nodes represent points in the network where multiple elements are connected to single electrical point, i.e. an electrical substation node. The elements connected at a substation node can include lines, cables, transformers, loads and / or generators. A substation may be represented by more than one node in the network model if there are multiple operational voltage levels present within the real-world substation (e.g. 132 kV and 33 kV). Overhead Lines and Underground Cables: These network elements are referred to as ‘branches’ and must be connected to a minimum of two substation nodes. These network branches have electrical characteristics which include operating voltage, length and resistance to the flow of electrical power. Transformers: These network elements transfer power between voltage levels (e.g. from 132 kV to 33 kV) and should therefore be connected to a minimum of two substation nodes with differing operating voltage levels. To model transformers, additional electrical data (e.g. maximum power rating) is required. Transformers are typically located within substation compounds. Network Loads: Network loads are modelled in substations and represent aggregated user demands, which draw power from the electricity grid at that substation, e.g. including residential, commercial and industrial electricity consumers. Generators: The term generator refers to any power plant which injects power into the electricity grid including, but not limited to, wind farms, solar farms, gas power stations, coal power stations, nuclear power stations and biogas power stations. Power sources in the form of BESS systems and High Voltage Direct Current (HVDC) Interconnectors are also included in this category and any reference to ‘generators’ herein may also be construed as a reference to ‘power sources’ more generally. Generators are connected to the network within substations, at a node / bus or at a defined distance along a branch which corresponds to the generator’s geographical location and physical connection point. The above definitions of the network elements include certain requirements for each element to be satisfied within the model. The software application developed to create the computational model can also perform checks of each and every network element against those requirements / rules to ensure the computational model is operable. The key inputs to the computational model are: network asset information, generation capacity registers, and electricity demand forecasts. A benefit of the current approach is that the mathematical / computational model can be populated using publicly available data published by distribution and transmission network operators. In the context of the UK network, distribution refers to voltage levels of 33 kV and 132 kV while transmission refers to voltage levels of 275 kV and 400 kV. An exception to this is Scotland where 132 kV network assets are considered transmission. In different countries, different thresholds may apply for distribution and transmission voltage levels. In the data sources detailed below: • The Long-Term Development Statement (LTDS) is a data source maintained by each Distribution Network Operator which contains equipment data, including electrical characteristics, for network assets. 5 • The Embedded Capacity Register (ECR) is a register of existing and contracted distribution generators and includes information on each generators capacity and Point of Connection (PoC). • The Electricity Ten Year Statement (EYTS) is published by National Grid Electricity System Operator (NGESO) and contains transmission level network asset data. 10 • The Transmission Entry Capacity Register (TEC-R) is a register of existing and contracted transmission generators with data on each generator’s location and size. The following table details data inputs to the computational model: Input ID Input / Dataset Description Source 11.1 Substation Data Substation identifier code and the voltage levels which are present in each substation. LTDS 11.2 T ransformer Data Transformer identifier and associated electrical characteristic data in format including impedance, rating, and voltage level for transformers in the network region. Each transformer must be linked to two substation identifiers to represent the high voltage and low voltage side of the transformer. LTDS 11.3 Branch Data Branch identifier and associated electrical characteristic data in format including impedance, thermal rating, and voltage level. Each branch must be linked to a minimum of two substation identifiers to represent each end of the overhead line or underground cable. LTDS 11.4 Network Load Data The MW capacity, connection voltage and location of network loads. LTDS 11.5 Generator Data The MW capacity, technology, connection voltage and connection location of each existing and future (i.e. contracted to connect) generator. ECR 15 Specific data fields populated in the computational model comprise Network Type Input Data Source Distribution Substation identifiers and voltage levels LTDS Distribution Circuit impedance and rating data LTDS Distribution Transformer impedance and rating data LTDS Distribution Existed and contracted generation location and capacity ECR Distribution Network load location and capacity LTDS Transmission Substation identifiers and voltage levels ETYS Transmission Transformer impedance and rating data ETYS Transmission Circuit impedance and rating data ETYS Transmission Existed and contracted generation location and capacity TEC-R Transmission Network load location and capacity ETYS The steps of gathering the data and populating the model can be automated by a script, e.g. being undertaken by a Python script. The relevant data fields can be identified and the data extracted for insertion to the relevant field in the model. In this example, the Pandas Python library is utilised for reading data, creating dataframes and processing data. The LTDS and ETYS data, including substation code names, transformers details, circuit data, future network demand data, and future generation data is gathered and processed to ensure it is free of errors. Fig. 2 shows an example visual representation of a fully populated mathematical model 30 for a region of an electrical grid. This example grid 30 is a commonly used example in scientific literature and the industry to test new approaches and applications. It consists of nine nodes (or buses) 32 and has 4 different voltage levels (220kV,18kV,16.5kV,13.8kV respectively) applied to different sections (or grouped elements) of the modelled network. It has three generating units 34, 6 lines, three transformers 36, and three loads 38. The transformers 36 are located between the different network voltage levels. Lines 40 connect the assets to form the network. Of course in working applications of the invention, the numbers of network elements, their connections and / or voltage levels can all vary so as to model an actual region of an existing power network. In this example, the power system network models are analysed using the commercially-available DlgSILENT (RTM) PowerFactory software package, which is an industry standard software package is used to undertake the electrical power flow simulations. In order to build the network in PowerFactory, Python v3.9 is used as an interface programming language. PowerFactory enables the use of Python as an interface to run the software outside of its environment. Using a program to automate the network construction is deemed practically important given the very large quantity of network data. There are multiple stages in the model creation process. A new study case must first be created with corresponding folders for each element so that each of the network components can be added. Once the study case and associated component folders have been created, the following network building process is undertaken: 1. Circuit / branch Creation: In this stage, the software reads the branch / circuit data (including overhead lines and underground cables) and creates a network element for each one. In building each circuit element, the software runs checks to makes sure that the circuit / branch is not isolated and that it is connected to the network (e.g. branches being connected to a minimum of two substation nodes, etc.). This is achieved by searching for links with all available data for circuits, transformers, loads, generators. Once confirmed that the circuit links two locations, it will create a network element and populate it with the appropriate electrical characteristics. 2. Transformer Creation: The process for creating transformers in the network model is the same as the circuit / branch creation, with network elements selected to match the transformer type per the input data. 3. Load Connection: Once the circuits and transformers are created, the backbone of the network has been constructed. The next step is to search the substation codes for the correct location to model each network load - these are identified using the recorded substation codes in the previous circuit and transformer creation stages. If a match is found, the load will be connected to the substation code in the model. The software application reports loads without a matching substation so that they can be investigated and rectified. 4. Generation Connection: The process for connecting power sources is similar to the load connection process. However, there is a slight difference between the approaches; there is no substation code provided in the input data for the generators. Therefore, a data processing exercise is undertaken to match each generator’s geographical location with the list of substation names. If a match is found, the corresponding substation code is retrieved so that it can be searched within the recorded substation codes created from branch and transformer creation stages. If it is found in that dataset, the software connects the generation to the matching substation code. Otherwise, it will report the generation as a missing so that it can be investigated. The model generation as standard defines generation and demand to represent a case with low demand and high generation so that the network is under severe stress, thus creating the most conservative scenario for the hosting capacity analysis for a new power source. This is entirely configurable and generation and demand profiles can be adjusted as required by the user. As discussed above, the system can run checks to ensure correct connectivity between each network element in the network model, i.e. that every connection defined in the element rules is satisfied. This makes sure that no ‘islanded’ regions should exist in the network model which are electrically disconnected from the main electricity grid model. Where the computational model terminates, i.e. at its boundaries, suitable boundary conditions can be inserted as appropriate to represent a connection to the wider electrical grid. Based on the above process, it is possible to generate computational models of electricity grids which are accurate representations of the real-world network assets, assuming accurate input data and can be used to run power flow simulations of the network under varying conditions. Simulation of Power Flows using the Electricity Grid Model Once the network is created as a populated computational model, the main simulation procedure is commenced. As aforementioned, the network simulation is generally setup to represent a stressed scenario. Power flow simulations may be run for the base case as established by the existing network elements (i.e. representing the current assets of the actual electrical grid). In Fig. 3, a new generation unit 34a has been added to the model 30 which serves as the unit whose capacity needs to be analysed. In this manner the addition of a new power source into the model at a specified location can be explored. The location is specified by connection to or between existing network elements. The power source 34a and / or its location can be varied to analyse the impact of a virtual or proposed new power source on the network. The power flow simulation can be run for this new scenario, e.g. different from the base case represented by the model of Fig. 2. Digsilent PowerFactory is the power system analysis software application used in this example in analysing generation, transmission, distribution and industrial systems. It is flexible to use, particularly for scripting and interfacing which helps in creating automated processes with the use of scripting tools like Python. There are similar tools for power system analyses which also support scripting such as PSS / E, and other open-source alternatives that are purely Python-based packages such as Pandapower. The process used here may apply to any such tools, or alternatives, keeping in mind that such a software application would typically be able to undertake the following tasks: open a power system model in a suitable format, e.g. using Python has the ability to run a power flow simulation using a mathematical solver which solves a set of nonlinear system of equations to identify a set of unknown variables which would be the resulting values of Power, Voltage, Current, and e.g. Reactive Power for each element and at each node in the network. The Newton-Raphson solution method is used for the mathematical solver in this example, but alternatives could also be considered. Has the ability to make changes to the model via the scripting tool (e.g: add a new generating unit, change the parameters of a line, take an element from the network out of service, etc). In order to investigate the viable export and import capacity of each substation and feeder, a list of contingencies including all the branches and transformers are created so that the capacity is measured during contingency (N-1) situations. An N-1 contingency refers to the disconnection any one piece of network equipment e.g. a line, transformer, generator or load within the computational model. The modelling of contingency events are important when measuring the export and import capacity of the grid to reflect the operational vulnerability of the electrical network This is achieved using the following stages. 1. Contingency List: This list is created by including all the circuits / elements and transformers from the grid. A scenario is created for each individual contingency and a corresponding network variation (i.e. a copy of the study case) is created for each individual contingency and scenarios. 2. Generation And Load Dispatch: For each contingency scenario, all the surrounding loads and generations are selected. The simulation software has the capability to search for a user-defined number of substations around the contingency element to find the connected loads and generators in that area, i.e. within a prescribed spacing or distance from the contingency element. Two different dispatch plans are deployed for measuring export and import capacity of the grid. To measure the export capacity, the software increases the selected generators to their maximum generation capacity and leaves the loads as they are. For measuring import capacity the software decreases the generators to their minimum generation capacity and increases the loads to their maximum level. Using these dispatch methodologies, the software ensures that the network is sufficiently stressed so that the minimum export and import capacity of the grid are measured for that contingency. This provides conservative results which in turn provide confidence that any identified network capacity exists in reality. 3. Element Checking: The user can select a defined number of substations and circuits to be assessed for export and import capacity. In order to measure the export and import capacity of feeders from the selected circuits, a dummy substation is created at the centre of each selected circuit / branch. This enables the modelling of a new solar farm, BESS or other power source connecting into the centre point of an existing line. All of the buses in the defined area, e.g. an area around the dummy substation, are then added to a list of elements to be assessed for the scenario in question. 4. Hosting Capacity Analysis: the software applies a function that measures export and import capacity at selected substations (i.e. the elements defined in step 3 above). This function connects a new generator at each selected substation and increases the generation capacity incrementally until a voltage or thermal violation occurs in the observed area. The available capacity is therefore identified as the incremental point where a new violation appears in the network model. A corresponding process is also undertaken with a load element (rather than a generation) to determine import capacity. 5. Powerflow Solution: When all the selected elements and observed areas for Hosting Capacity Analysis (HCA) are chosen, a power flow solution process must be performed so that any base case / threshold violations present in the model can be identified and resolved, [insert list of variables that are monitored as ‘base case violations]. This is done to make sure the HCA process can be run successfully as the HCA process will not start if there are existing violations in the base case. In Fig. 4, stress testing of the type described above is performed by removing a line 40a from service. Within the model, the line 40a is thus disconnected or removed from the power flow calculation. It is possible to then test how much capacity from the generation 34a is allowed before the network breaches its thermal threshold of 100% element loading capacity and / or a voltage threshold (which is measured in “per unit (p.u.)”). Voltage thresholds, e.g. for each element, may be set at 1.5 p.u respectively. In another test, the line 40a may be reinstated and another element within a suitable proximity to new power source 34a may be removed. The simulation can then be rerun under that scenario. This process may b repeated for different scenarios as many times as necessary to identify elements that could viably alter the networks ability to handle the new power source 34a. When running simulations, a task automation approach is used to maximise the use of available processing power across the available computational cores. All the created scenarios with their network variations including all the steps described for each individual scenarios are run through a task automation scheme that uses all processor cores simultaneously in parallel. This allows the analysis to be completed as quickly and efficiently as possible. In order to confirm the complexity of such simulations, it is estimated that the processing time for a single run of the system may be in the order of one to seven days. The network model is created and configured in a form that enables DigSilent PowerFactory’s internal Newton-Raphson solver technique to achieve a convergent solution i.e. the solver must be able to determine a state whereby the calculated voltages and power flows in the simulation model are in accordance with the laws of physics and electromagnetism for alternating current power systems within a maximum number of iterations of the solution technique, e.g. in the order of tens of iterations, such as 50, 80 or 100 iterations. The system generates appropriate errors to alert the user to common issues where the system fails to operate correctly, i.e. failing to iteratively converge to a solution. Once the task automation is completed for all the created scenarios, the software will extract the stored results from the simulation system for each individual scenario and save them as a suitable output file. As there are similar elements for different scenarios and contingencies, the minimum export and import capacities for each element are selected and the minimum available capacity for each location is reported. The system in this example provides output results, e.g. in .xlsx format, which provides an indication of available MW capacity values for new solar farm and storage projects at each substation on the modelled electricity grid. The software then finds the substation and circuit geographical locations based on the input data tables discussed above and their corresponding substation codes. The system can generate reports of the outcome in two separate databases, tables or the like: one for the substations and the other one for the feeders, each with their corresponding maximum export and import capacity. Site Selection and Development Figure 5 shows an overview of the steps of the process described above and how it may fit into a wider planning and facility development process. The process described herein may automatically output the results of the capacity analysis and therefore provide data on the available power capacity of the grid. Using the above process, opportunities for new power source implementation can be identified that have not been hitherto available. The approach is different from the prior art since it relies on assessments in terms of the capacity available within the existing network assets, rather than focussing initially on other factors, such as the local availability of renewable energy. A user may now define a desirous power output for an intended new power source facility and have the software return a list of viable locations for connection to the network relative to existing assets (e.g. sites / substations / buses). As an output of the simulation process, it is known what available capacity exists at each substation. It is therefore now possible to run simulations or other analysis of the available power source in the vicinity of the relevant substation to determine whether a new power source with an output falling within the determined capacity can be implemented in that vicinity. In the case of solar farms, this may include analysis of the available land and solar energy generation capacity for a given available area. The outputs of the simulation process can feed into the project origination strategy and assist in overlaying the information obtained about the locations in the electricity grid where capacity was found onto a geographical information system (GIS) tool which helps identify the physical locations on the grid where this capacity exists. That is to say, the identified network locations for power sources output from the modelling software can be correlated to geographical locations or areas, e.g. on a map. This then carries forward the results, which is the found capacity and associated locations to the next step of the site identification process which is to assess if there are any other hurdles in the found locations in terms of being viable locations for new generating units. GIS tools can then be used to identify actual sites for an intended power source / facility. This can be achieved by specifying a geographical area or boundary within which a suitable site must exist for connection to the existing grid. In the example of a renewable energy site, the GIS tools may be used to identify the generation capacity for sites over the specified geographical area. In the example of solar farms, this may be achieved by assessment of sunlight hours and the inclination of the land within the area, e.g. to identify land with a desired solar generation capacity. According to various aspects of the invention, there may be provided a site identification, selection or development method / system using the simulation process described herein. In some examples, the simulation process may result in a finding that the input / output capacity of an area of the electrical grid can be improved by upgrading one or more of the existing elements / assets. One or more further software application, process or tool may be used to assess the feasibility of solar and storage projects based on other criteria. These may comprise a GIS tool and may take the form of a site development and / or management application. Such tools may track and store details and status of identified sites so they are accessible across a team. Different jurisdictions may have different processes and different criteria for suitable site location (e.g. for practical, safety, legal reasons, etc.). As such, the software application may log jurisdiction and apply the processes and criteria relevant to that location. Data produced by the computational modelling and analysis process described herein is incorporated / imported into the site development application and the identified network points with the necessary grid capacity can be captured for detailed site searching. The relevant publicly available data for the sites can be assessed, e.g. comprising any or any combination of: key land designations (National Parks, AONBs etc) or other site use restrictions; ownership details; notable planning history on the site and / or surrounding lands; site access and / or topography. In some cases, a site visit may be required to further assess existing screening, access to site and topography. Ancillary tools used in the assessment of sites are Google Earth, Anderson Optimisation, Magic Maps, the Land Registry, Solar Media local news publications (this list is not comprehensive). The status of suitable sites can thus be logged and tracked in the site development tool, along with relevant project / status updates, e.g. including administrative steps needed to progress the site for facility deployment. Administrative steps, for example, may include whether or not an approach has been made to a landowner. If an approach has been made and the landowner agrees to progress with a site, the project will move forward in the development application to enable further functionality, or may the site data may be output from the platform to another project development application / platform. However, if a landowner does not wish to progress a site, then the site assessment / development tool may iterate its procedure to identify an alternative site for development based on the results of the network modelling process. Using the network modelling process and site selection tools, once a suitable site has been granted the permissions needed for development, the project implementation steps can begin for construction of the proposed facility. The above system therefore not only allows identification of viable sites and marrying of intended power generation to available capacity on the network, but also the further development of those sites towards a viable facility. The planned facility can then be installed at the site and connected to the electrical grid / network with a greater level of confidence that there will be no unexpected negative impacts on the existing assets and infrastructure of the network.

Claims

1. A method of selecting a location for implementation of a new power source within an electrical grid comprising:creating a computational model of an electrical grid having a plurality of existing network elements representing generators, loads, transformers, power lines and nodes at which a plurality of the network elements are connected;running a power system network simulation using the computational model in which each network element has an associated voltage and the generators and loads each have an associated power capacity;wherein running the power system network simulation comprises:applying a new power source to the computational model;simulating whether the new power source causes one or more operational threshold for each of the existing network elements to be exceeded;repeating the simulating for the new power source for a plurality of different conditions of the computational model in which a different existing network element is inoperative; and,identifying one or more elements in the model of the electrical grid to which the new power source can be connected without the one or more operational threshold for each of the network elements being exceeded upon the repeating of the simulation.

2. The method of claim 1, comprising identifying sites within a predetermined geographical vicinity of the one or more identified elements and assessing the capacity of said sites for implementation of the new power source.

3. The method of claim 1 or claim 2, comprising the step of implementing or connecting a new power source at one of the identified network elements or the identified sites.

4. The method of any preceding claim, wherein the new power source comprises a new generator or energy storage facility.

5. The method of any preceding claim, wherein the computational model comprises a number, N, of network elements and running the power system network simulationcomprises repeating the simulation for the new power source for a variety of different N-1 scenarios.

6. The method of claim 5, comprising repeating the simulation for the new power source for a majority or all of the possible N-1 scenarios for the computational model.

7. The method of claim 5, comprising repeating the simulation for the new power source for all of the possible N-1 scenarios representing outages of network elements of a specific element type and / or within a predetermined vicinity of the new power source within the computational model.

8. The method of any preceding claim comprising the step of outputting a maximum power capacity for a new power source to be connected at a network element within the modelled electrical grid.

9. The method of any preceding claim comprising repeating the simulating of the new power source at different possible locations in the computational and selecting one or more network element corresponding to a node or transformer at which there is a sufficient power capacity for the new power source.

10. The method of any preceding claim, wherein the plurality of network elements of the computational model comprise a plurality of substations and the identified network element comprises a substation to which the new power source may be connected.

11. The method of any preceding claim, wherein the computational model and / or power flow simulation comprise any, any combination, or all of the following data for network elements: an identifier; a voltage level; an impedance; generation capacity; load capacity.

12. The method of any preceding claim, wherein an available power capacity value is determined for a plurality of the network elements of the computational model and a list of the network elements and their respective power capacity value is output.

13. The method of any preceding claim, wherein a minimum viable power import / export capacity is determined for all nodes within a region of the electrical network based on the repeating of the simulation for the new power source.

14. The method of any preceding claim, comprising automatically checking all network elements are connected within the computational model by applying one or more rules to determine an acceptable connection for each network element type.

15. The method of any preceding claim, comprising gathering data for the plurality of existing network elements from publicly available sources on a wide area network and populating the computational model with said data.

16. The method of any preceding claim, wherein the data for the existing network elements is gathered from any, any combination, or all, of: network asset information; generation capacity registers; and, electricity demand forecasts.

17. The method of any preceding claim, comprising the step of determining an indication of proposed changes to existing network elements to increase a power capacity value for one or more existing network element to accommodate the new power source.

18. The method of any preceding claim, where any or all of the method steps are automated by a software application.

19. The method of any preceding claim, wherein the running of the power system network simulation comprises iteratively computing solutions to the power system network simulation and converging towards a final solution.

20. The method of any preceding claim, comprising a method of approving or implementing changes to an electrical grid by the addition of a new power source.

21. A method of modifying an existing electrical grid by addition of a new renewable energy generation facility, comprising the method of any preceding claim.

22. A system for assessing changes to an existing electrical grid, the system comprising one or more processor comprising machine readable instructions for: accessing a computational model of an electrical grid having a plurality of existing network elements representing generators, loads, transformers, power lines and nodes at which a plurality of the network elements are connected;running a power system network simulation using the computational model in which each network element has an associated voltage and the generators and loads each have an associated power capacity;wherein running the power system network simulation comprises:applying a new power source to the computational model;simulating whether the new power source causes one or more operational threshold for each of the existing network elements to be exceeded;repeating the simulating for the new power source for a plurality of different conditions of the computational model in which a different existing network element is inoperative; and,identifying one or more elements in the model of the electrical grid to which the new power source can be connected without the one or more operational threshold for each of the network elements being exceeded upon the repeating of the simulation.

23. A system according to claim 22, wherein the system outputs an indication of approval for the one or more identified elements in the model of the electrical grid for a new power source of a defined power capacity.

24. A data carrier or data storage medium comprising machine readable instructions for the control of one or more computer processor to:create a computational model of an electrical grid having a plurality of existing network elements representing generators, loads, transformers, power lines and nodes at which a plurality of the network elements are connected;run a power system network simulation using the computational model in which each network element has an associated voltage and the generators and loads each have an associated power capacity;wherein running the power system network simulation comprises:applying a new power source to the computational model;simulating whether the new power source causes one or more operational threshold for each of the existing network elements to be exceeded; and,repeating the simulating for the new power source for a plurality of different conditions of the computational model in which a different existing network element is inoperative.

25. A data carrier according to claim 24, wherein the machine readable instructions control the one or more processor to repeatedly add new power sources to the computational model of differing power capacity and / or at different locations within the computational model.AMENDMENTS TO THE CLAIMS HAVE BEEN FILED AS FOLLOWS:26Claims:

1. A method of selecting a location for implementation of a new power source within an electrical grid comprising:5 creating a computational model of an electrical grid having a plurality of existingnetwork elements representing generators, loads, transformers, power lines and nodes at which a plurality of the network elements are connected;running a power system network simulation using the computational model in which each network element has an associated voltage and the generators and loads10 each have an associated power capacity;wherein running the power system network simulation comprises:applying a new power source to the computational model;simulating whether the new power source causes one or more operational threshold for each of the existing network elements to be exceeded;15 repeating the simulating for the new power source for a plurality of differentC\l conditions of the computational model in which a different existing network£\J element is inoperative;v— identifying one or more elements in the model of the electrical grid to whichthe new power source can be connected without the one or more operational20 threshold for each of the network elements being exceeded upon the repeating ofthe simulation; and,repeating the simulating of the new power source at different possible locations in the computational and selecting one or more network element corresponding to a node or transformer at which there is a sufficient power25 capacity for the new power source.

2. The method of claim 1, comprising identifying sites within a predetermined geographical vicinity of the one or more identified elements and assessing the capacity of said sites for implementation of the new power source.

303. The method of claim 1 or claim 2, comprising the step of implementing or connecting a new power source at one of the identified network elements or the identified sites.35 4. The method of any preceding claim, wherein the new power source comprises anew generator or energy storage facility.(5. The method of any preceding claim, wherein the computational model comprises a number, N, of network elements and running the power system network simulation comprises repeating the simulation for the new power source for a variety of different N-1 5 scenarios.

6. The method of claim 5, comprising repeating the simulation for the new power source for a majority or all of the possible N-1 scenarios for the computational model.10 7. The method of claim 5, comprising repeating the simulation for the new powersource for all of the possible N-1 scenarios representing outages of network elements of a specific element type and / or within a predetermined vicinity of the new power source within the computational model.15 8. The method of any preceding claim comprising the step of outputting a maximumC\l power capacity for a new power source to be connected at a network element within the£\J modelled electrical grid.1—9. The method of any preceding claim, wherein the plurality of network elements of 20 the computational model comprise a plurality of substations and the identified network element comprises a substation to which the new power source may be connected.

10. The method of any preceding claim, wherein the computational model and / or power flow simulation comprise any, any combination, or all of the following data for 25 network elements: an identifier; a voltage level; an impedance; generation capacity; load capacity.

11. The method of any preceding claim, wherein an available power capacity value is determined for a plurality of the network elements of the computational model and a list of 30 the network elements and their respective power capacity value is output.

12. The method of any preceding claim, wherein a minimum viable power import / export capacity is determined for all nodes within a region of the electrical network based on the repeating of the simulation for the new power source.3513. The method of any preceding claim, comprising automatically checking all networkelements are connected within the computational model by applying one or more rules to determine an acceptable connection for each network element type.

14. The method of any preceding claim, comprising gathering data for the plurality of existing network elements from publicly available sources on a wide area network and populating the computational model with said data.

15. The method of any preceding claim, wherein the data for the existing network elements is gathered from any, any combination, or all, of: network asset information; generation capacity registers; and, electricity demand forecasts.

16. The method of any preceding claim, comprising the step of determining an indication of proposed changes to existing network elements to increase a power capacity value for one or more existing network element to accommodate the new power source.

17. The method of any preceding claim, where any or all of the method steps are automated by a software application.

18. The method of any preceding claim, wherein the running of the power system network simulation comprises iteratively computing solutions to the power system network simulation and converging towards a final solution.

19. The method of any preceding claim, comprising a method of approving or implementing changes to an electrical grid by the addition of a new power source.

20. A method of modifying an existing electrical grid by addition of a new renewable energy generation facility, comprising the method of any preceding claim.

21. A system for assessing changes to an existing electrical grid, the system comprising one or more processor comprising machine readable instructions for: accessing a computational model of an electrical grid having a plurality of existing network elements representing generators, loads, transformers, power lines and nodes at which a plurality of the network elements are connected;running a power system network simulation using the computational model in which each network element has an associated voltage and the generators and loads each have an associated power capacity;wherein running the power system network simulation comprises:applying a new power source to the computational model;simulating whether the new power source causes one or more operational threshold for each of the existing network elements to be exceeded;repeating the simulating for the new power source for a plurality of different conditions of the computational model in which a different existing network element is inoperative;identifying one or more elements in the model of the electrical grid to which the new power source can be connected without the one or more operational threshold for each of the network elements being exceeded upon the repeating of the simulation; and,repeating the simulating of the new power source at different possible locations in the computational and selecting one or more network element corresponding to a node or transformer at which there is a sufficient power capacity for the new power source.

22. A system according to claim 21, wherein the system outputs an indication of approval for the one or more identified elements in the model of the electrical grid for a new power source of a defined power capacity.

23. A data carrier or data storage medium comprising machine readable instructions for the control of one or more computer processor to:create a computational model of an electrical grid having a plurality of existing network elements representing generators, loads, transformers, power lines and nodes at which a plurality of the network elements are connected;run a power system network simulation using the computational model in which each network element has an associated voltage and the generators and loads each have an associated power capacity;wherein running the power system network simulation comprises:applying a new power source to the computational model;simulating whether the new power source causes one or more operational threshold for each of the existing network elements to be exceeded; and,repeating the simulating for the new power source for a plurality of different conditions of the computational model in which a different existing network element is inoperative; and,CMrepeating the simulating of the new power source at different possible locations in the computational and selecting one or more network element corresponding to a node or transformer at which there is a sufficient power capacity for the new power source.

24. A data carrier according to claim 23, wherein the machine readable instructions control the one or more processor to repeatedly add new power sources to the computational model of differing power capacity and / or at different locations within the computational model.

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