Chuiyi Meng∗
Electric vehicles, distributed power generation, output optimisation,Monarch butterfly optimisation algorithm, power system.
In the new energy power system, many electric vehicle integrations can cause load fluctuations and increase operating costs. Therefore, the output of distributed power sources in the new energy power system is optimised. The research first determines the optimisation objective, which is to minimise voltage fluctuations while minimising additional network losses. Then, a distributed power generation output optimisation model based on wind power and photovoltaics is constructed. Finally, an improved Emperor Butterfly optimisation algorithm is designed to address the model and ultimately achieve distributed power generation output optimisation in the power system. After output optimisation, the voltage fluctuation upper limit at each node was very close to the expected value. The maximum difference between the upper limit values at each node during a day and the expected value was 0.03 p.u., the minimum difference was 0 p.u., and the average difference was 0.007 p.u. After optimisation, the maximum loss at each time was 0.18 MW, the minimum loss was 0.02 MW, and the average loss was 0.10 MW. The method can effectively optimise the output of distributed power sources, thereby improving the stability and economy of the distribution network.
Important Links:
Go Back
