Research on demand management of hybrid energy storage system in industrial park based on variational mode decomposition and Wigner–Ville distribution

Abstract In the industrial park microgrids, the curves of industrial load and photovoltaic output are unstable and unadjustable. The implementation of energy storage system (ESS) has proven successful in tackling these issues. Compared with the single-type battery energy storage (SBES), the hybrid energy storage system (HESS) is composed by energy-type energy storage and power-type energy storage, which can effectively improve the controllability and schedulability of renewable energy generation. The governments of most countries have implemented a two-part time-of-use tariff mechanism for industrial users. In this context, the paper proposes a solution for the reasonable low-cost configuration and operation of HESS in industrial parks. First of all, this paper creatively combines the Variational Mode Decomposition and Wigner–Ville Distribution (VMD-WVD) algorithm to break down the net load of the industrial park system, and installs the super-capacitors and lithium batteries to smooth the high frequency and low frequency components of the original net load. Secondly, this paper establishes a two-stage monthly and day-ahead optimization model, which is solved by the Chaos Particle Swarm Optimization (CPSO) algorithm. The monthly HESS capacity optimization configuration model is to minimize the total installation cost. And the day-ahead scheduling model maximizes the net income of life cycle, which further improves the user's peak-to-valley arbitrage. The results show that, compared with SBES, the installation of HESS can better achieve peak shaving and reduce grid connection fluctuations. Besides, the installation of HESS can greatly reduce the electricity cost and the basic electricity cost of industrial parks, so that it can save industrial users' production costs.