Optimization configuration and operation strategy of energy storage for microgrid considering external power transmission
Year: 2024
Type: article
Abstract: In the context of the evolving power system landscape, the proliferation of microgrid systems anchored on large-scale new energy generator sets is advancing rapidly. Nonetheless, the inherent instability of new energy generation introduces substantial unpredictability into the power transmission process, thereby escalating the challenges in power system dispatch and elevating transmission costs. To address these issues, optimizing energy storage configurations emerges as a pivotal strategy, capable of effectively mitigating the fluctuations in new energy output, bolstering the stability and reliability of external power supplies, curbing transmission expenses, and enhancing the economic feasibility of new energy power generation.This paper endeavors to devise an optimal energy storage allocation framework for microgrids, aiming to maximize transmission efficiency. An objective function tailored to this pursuit is formulated, followed by the construction of constraints that encompass system power balance, as well as the safe operational prerequisites of generators, new energy sources, energy storage units, and other integral equipment. Subsequently, a comprehensive optimal energy storage allocation model tailored specifically for microgrids is formulated.To validate and demonstrate the efficacy of this model, a simulation testbed leveraging MATLAB is established, incorporating real-world data from a designated locale. This platform facilitates the realization of optimal energy storage configuration and scheduling within the microgrid. The optimized configuration outcomes indicate a rated power capacity of 113kW and a rated energy capacity of 169kWh. This proposed model not only underscores a tangible enhancement in the economic viability of microgrids but also presents a viable blueprint for optimizing energy storage configuration and operational scheduling strategies within microgrids.
DOI: 10.54097/cr6rk364
Authors: Yuanyi Qin, Lijian Wang, Weijian Li
Language: English
Subfield: Control and Systems Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4406447023