As a part of the project, a simulator, shown in figure below, was developed in Southampton University using MATLAB GUI to investigate the impact of integration of electric vehicles (EVs) in the power system, and find out the impact of their Vehicle to Grid (V2G) operation on the performance of the power system. This simulator uses MATPOWER power flow analysis engine to simulate the impact of electric vehicles on power networks. One of the objectives of the project was to find out the charge/discharge patterns, which will be applied to batteries due to applying V2G control strategies on the system. The current simulator is capable of showing how the State of Charge (SoC) of individual vehicles change during the simulation period depending on the applied control strategy. These patterns can be easily used to test actual batteries and find out the degradation impact.
The simulator is also capable of integrating renewable wind or solar power in the network as well as analysing the impact of electric vehicles on the power system in with or without V2G scenarios.
• The control strategy respects the requirements of the car owner and the power system operator before making a decision about charging or discharging the EVs.
• The simulator is currently able to consider four control strategies: ‘Electricity price’, ‘Load levelling’ and ‘Wind power availability’, ‘Active Network Management’.
i. ‘Electricity price’: The control strategy tries to take advantage of the difference between electricity selling and buying prices to decrease the charging cost of the EVs in with V2G scenario in comparison to without V2G scenario.
ii. ‘Load levelling’: The dispatch strategy tries to level the electrical demand if the power system by charging the EV batteries during off peak time and discharging them during peak times.
iii. ‘Wind power availability’: The controller injects the available surplus wind power to the EV batteries, which are able to accept it. When the wind power generation in the system is low, the EVs can give power back to the grid to compensate the lack of wind power generation.
iv. ‘Active Network Management’: The control strategy tries to inject the surplus solar power available on a radial distribution network to EV car parks to maintain the power system constraints within acceptable limits.
