Optimal Hybrid Energy Storage System Planning of Community Multi-Energy System Based on Two-Stage Stochastic Programming

Abstract

The multi-energy system (MES) provides a good environment for the local consumption of renewable energy such as wind and solar power because of its high operational flexibility. In the MES, the hybrid energy storage system (HESS) composed of the battery and thermal storage tank plays an important role in enhancing reliability, economics, and operational flexibility. Hence, determining the optimal size of HESS in the MES is a critical problem but has not received enough attention. In light of this problem, this paper focuses on the optimal HESS planning problem in the community MES (CMES) under diverse uncertainties. Firstly, a two-stage stochastic planning model is proposed for the CMES to coordinate the optimal long-term HESS allocation and the short-term system operation. The thermal inertia in the heating network, space heating demand, and domestic hot water demand is utilized to reduce both the planning and operational cost. Secondly, a deterministic equivalence is proposed for the two-stage planning model to convert it into a mixed-integer linear programming model, which is then solved by off-the-shelf solvers. Finally, simulation results verify the effectiveness of the proposed method. The results reveal that the HESS can enhance the operational flexibility of the CMES but only needs a very few investment costs and prove that the thermal inertia in the CMES can reduce the investment cost of HESS, the fuel, and the operational maintenance cost.INDEX TERMS Battery, community multi-energy system, hybrid energy storage system, mixed-integer linear programming, operational flexibility, renewable energy, thermal storage tank, two-stage stochastic programming, uncertainty.

Optimal configuration of energy storage considering flexibility requirements and operational risks in a power system

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Flexibility Exploitation With Nonlinear Integrated Demand Response for Multi-Energy System Against Load Estimation Mistake

“…An operational result of a real-life residential microgrid was presented in [5], and showed a significant annual energy cost reduction. The work in [6] proposed a two-stage optimal planning and dispatching method for the combined electricity, thermal, and cooling microgrid system. The first stage was to select the optimal equipment capacity, and the second stage was to solve the optimal dispatch problem.…”

Distributionally Robust Capacity Configuration for Energy Storage in Microgrid Considering Renewable Utilization

“…Stochastic programming uses random variables to describe uncertain information and optimizes the scheduling scheme with the smallest expected cost. Shen et al (2021) proved that thermal inertia in multi-energy systems can reduce the investment cost of hybrid energy storage systems. Jooshaki et al (2020) proposed a stochastic model for expansion planning of multi-level distribution systems to improve network flexibility through optimal installation of energy storage systems.…”