Cooperative planning model of renewable energy sources and energy storage units in active distribution systems: A bi-level model and Pareto analysis

Abstract

This paper proposes a multi-objective, bi-level optimization problem for cooperative planning between renewable energy sources and energy storage units in active distribution systems. The multi-objective upper level serves as the planning issues to determine the sizes, sites, and types of renewable energy sources and energy storage units. The fuzzy multi-objective lower level serves as the operation issues to formulate operation strategy and determine the schedules of energy storage units. By means of bi-level programming, the optimal operation strategy of energy storage units is incorporated into the upper level and optimized with planning issues cooperatively. Meanwhile, to address high-level uncertainties and simultaneously capture the temporal correlation related to renewable energy sources, electric vehicles, and load demands, the validity index of Davies Bouldin is adopted to develop sets of probabilistic scenarios with high quality and diversity. A hierarchical solving strategy based on modified particle swarm optimization is applied to solve the bi-level nonlinear, mixed integer optimization problem. Results and further analyses demonstrate that the proposed planning model and optimization methods have the ability to allocate renewable energy sources and energy storage units effectively for reducing costs, enhancing reliability, and promoting clean energy.