Research on planning optimization of integrated energy system based on the differential features of hybrid energy storage system. (1st November 2022) - Wang, Yongli; Zhang, Yuli; Xue, Lu; Liu, Chen; Song, Fuhao; Sun, Yaling; Liu, Yang; Che, Bin
Abstract: At present, it is very important to build the new power system with new energy as the mainstay. Some Regional Integrated Energy Systems (RIES) have installed renewable energy generation equipments with wind turbines and photovoltaics as the main power supply facilities. Due to the volatility in the wind turbine, photovoltaic output power and the customer's electricity load, there is energy waste in the RIES. In order to enhance the economic and renewable energy consumption rate of the park where the RIES is applied, an integrated energy system(IES) planning optimization model is constructed，which considers the mixed storage differentiation characteristics. The model expands the hybrid energy storage system(HESS) on the basis of the original RIES. A two-stage decomposition model combining wavelet packet decomposition method and power decomposition method based on discrete Fourier transform is established, in which the difference between power generation of renewable energy and customer load is decomposed. Depending with the difference in response speed of energy storage devices, the power of different frequencies is moderated. With the comprehensive energy system economy as the goal, the genetic algorithm based on elitist preservation strategy is adopted to optimize the planning model and verify the correctness of the model through simulation. The results show an improvement of 8.23 % and 23.79 % in economy and renewable energy consumption rate compared to the RIES before the HESS expansion. Highlights: The basic framework of an integrated energy system including hybrid energy storage is constructed, which is conducive to improving the overall economy and renewable energy utilization. A two-stage decomposition model of wavelet packet decomposition-discrete Fourier transform is constructed. It can help to obtain more accurate frequency division results and improve the economy of the system. Based on the existing RIES, an energy storage capacity expansion planning model considering the different energy storage response speeds is constructed. The model considers system balance constraint, equipment constraint and frequency division constraint. A genetic algorithm based on an improved elite strategy is proposed to solve the model optimally, which improves the computational efficiency. And three different scenarios are established to compare and verify the effectiveness of the IES planning and optimization model of the expanded HESS.