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Newcastle University ePrintsCrossland AF, Jones D, Wade NS. Planning the location and rating of distributed energy storage in LV networks using a genetic algorithm with simulated annealing.This work is licensed under a Creative Commons Attribution-NonCommercial 3.0 Unported License ePrints -Newcastle University ePrints http://eprint.ncl.ac.ukPlanning the location and rating of distributed energy storage in LV networks using a genetic algorithm with simulated annealing International Journal of Electrical Power & Energy Systems http://dx.AbstractIn light of the expansion of domestic photovoltaic (PV) systems in the UK, there are concerns of voltage rise within LV networks. Consequently, network operators are interested in the costs and benefits of different technologies to manage their assets. This paper examines the particular case for distributed energy storage. A heuristic planning tool is developed using a genetic algorithm with simulated annealing to investigate the problem of locating and sizing energy storage within LV networks. This is applied to investigate the configuration and topologies of storage to solve voltage rise problems as a result of increased penetration of PV. Under a threshold PV penetration, it is shown that distributed storage offers a financially viable alternative to reconductoring the LV network. Further, it is shown that a configuration of single phase storage located within the customer home can solve the voltage problem using less energy than a three phase system located on the street. NomenclatureRandom number in the interval zero to one, applied in simulated annealing Capital cost of storage unit [£] Installation cost of each storage unit [£] Power cost of particular energy storage technology [£/kW] Energy cost of particular energy storage technology [£/kWh] Cost of reconductoring the network [V] Permissible depth of discharge [%] Capacity of energy storage unit [kWh] Roulette wheel fitness of solution during algorithm round Probability that solution is selected during algorithm round Rating of energy storage unit [kW] Length of time that storage operates at full power [h] Temperature, applied in simulated annealing Highest voltage in LV network when storage solution is implemented [V] Round trip efficiency of particular energy storage technology [%]Please cite this article as: Crossland, A.F., et al., Planning the location and rating of distributed energy storage in LV networks using a genetic algorithm with simulated annealing.

A method for the coordination of multiple battery energy storage systems (BESSs) is proposed for voltage control in low-voltage distribution networks (LVDNs). The main objective of this method is to solve over-voltage problems with multiple suitably sized energy storage systems. The performance of coordinated control is compared with noncoordinated control using both a real-time digital simulator and a MATLAB model of a real U.K. LVDN with a high installed capacity of solar photovoltaics. This is used to show that coordinated control is robust and effective at preventing voltage rise problems in LVDNs. The proposed coordinated control scheme is able to use the BESSs more evenly, and therefore reduces the costs of battery replacement to the storage operator in terms of both number of batteries and maintenance visits.Index Terms-Battery energy storage systems (BESSs), coordinated voltage control, distributed generation, low-voltage distribution network (LVDN), real-time digital simulator.

Domestic PV-battery systems are rarely operated in a way which specifically maximizes environmental benefit. Consequently the studies that seriously examine such systems often find that the greenhouse gas and pollutant emissions savings of rooftop PV, though still positive, are lessened by adding a domestic battery. This study shows thatby simulating a PV-battery system with a range of sizes that this need not be inevitable. A novel algorithm was designed specifically to perform 'emissions arbitrage': to charge the battery when the grid emissions intensity is low and to discharge when it is high. It was found that the CO 2 saved relative to the same system with PV only can more than pay back the CO 2 debt of manufacturing the battery. This is true as long as the UK moves away from the present-day situation where natural gas-fired generators are nearly always the marginal generator. This work underlines the importance of both the operating strategy and the interactions between the system and the entire grid, in order to maximize the environmental benefit achievable with domestic PV-battery systems.In contrast, Faria et al. (2014) [18] showed that a second-life electric vehicle battery could reduce global warming, abiotic depletion, acidification and eutrophication factors by 2% when used in a peak-shaving application in France, and 4-5% in a load-shifting application (both without PV). This is because the French grid emissions intensities change throughout the day in such a way that electricity is imported from the grid when emissions are low and exported to the grid when they are high. This 'emissions arbitrage' effect was not accounted for in the other papers mentioned, which assumed a constant grid emissions intensity.A flaw in the work of Faria et al. (2014) [18] is that they used average rather than marginal emissions intensities. If some grid-generated electricity is displaced by the injection of PV power, or indeed any other intervention, not all the generator types (nuclear, coal, biomass, etc.) would have their output reduced in the same proportion as their total generation. The reduction would occur mostly for the generator type with the highest running cost. This gives rise to the concept of marginal emissions factor (MEF, as opposed to average emissions factor, AEF). Studies have shown that using AEF rather than MEF can cause errors of up to 25% [19][20][21][22].It should also be noted that the battery operating strategies studied by Faria et al. (2014) were not designed to achieve emissions arbitrage. As such, environmental impacts were negative when those operating strategies were applied to Portugal and Poland [18]. The literature is abundant with algorithms for peak reduction, cost minimization and self-sufficiency maximization [6][7][8][9][10][11][12][13]. There is good reason for this: All these objectives are quantifiable and desired by consumers, distribution network operators, or other relevant stakeholders. However, environmental benefit is also desirable, as evidenced by survey data on opini...

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International licence Newcastle University ePrints -eprint.ncl.ac.uk Crossland AF, Anuta OH, Wade NS. A socio-technical approach to increasing the battery lifetime of off-grid photovoltaic systems applied to a case study in Rwanda.