A two-stage stochastic model for energy storage planning in a microgrid incorporating bilateral contracts and demand response program

In recent years, application of energy storage technologies in smart grids has attracted huge attention. In this paper a cog-benefit analysis is carried out to evaluate and quantify the benefit of installing an energy storage system (ESS) in a typical Microgrid (MG). The model aims to yield the optimal ESS size by finding the least cost energy scheduling over a year under an uncertain environment. Therefore, a two-stage stochastic programming (SP) is defined to address the probabilistic nature of the parameters. The moment matching method is incorporated to create samples form probability distribution functions (PDFs) as nodes of a scenario tree. Furthermore, the fast forward selection (FFS) approach is utilized for scenario reduction. Lead acid battery (LAB), flywheel (FW) and pumped hydro energy storage (PHES) are chosen as ESS candidates. Simulation results demonstrate that whether operating as islanded or grid-connected, favorable yearly cost savings are achieved by optimal ESS planning. In this regard, the scheduled load responses and signed bilateral contracts (BCs) play important roles. The effectiveness of the proposed approaches is verified through comparisons with the deterministic and common stochastic methods. Finally, a sensitivity analysis is carried out on ESS cost to examine its effect on optimal sizing.