Optimal Sizing of Battery Energy Storage for a Grid-Connected Microgrid Subjected to Wind Uncertainties

Abstract

In this paper, based on stochastic optimization methods, a technique for optimal sizing of battery energy storage systems (BESSs) under wind uncertainties is provided. Due to considerably greater penetration of renewable energy sources, BESSs are becoming vital elements in microgrids. Integrating renewable energy sources in a power system together with a BESS enhances the efficiency of the power system by enhancing its accessibility and decreasing its operating and maintenance costs. Furthermore, the microgrid-connected BESS should be optimally sized to provide the required energy and minimize total investment and operation expenses. A constrained optimization problem is solved using an optimization technique to optimize a storage system. This problem of optimization may be deterministic or probabilistic. In case of optimizing the size of a BESS connected to a system containing renewable energy sources, solving a probabilistic optimization problem is more effective because it is not possible to accurately determine the forecast of their output power. In this paper, using the stochastic programming technique to discover the optimum size of a BESS to connect to a grid-connected microgrid comprising wind power generation, a probabilistic optimization problem is solved. A comparison is then produced to demonstrate that solving the problem using stochastic programming provides better outcomes and to demonstrate that the reliability of the microgrid improves after it is connected to a storage system. The simulation findings demonstrate the efficacy of the optimum sizing methodology proposed.

Optimal sizing of battery energy storage to enable offshore wind farm black start operation

“…Several methods are used to find the ideal size of the BESS. The optimal size could be found through the usage of an economic indicator when the size minimizes the total investment and operating costs, or a technical indicator when the size satisfies minimum technical requirements regardless of the cost of the BESS [9], [10]. An overview about the different methods and techniques to determine the optimal size of BESS is taken from [9], and here summarized:…”

“…The BESS size can be estimated directly from the synthesis scenarios or use the scenarios as input to another method. For example, reference [10] uses a probabilistic method to generate scenarios and use them as input for a stochastic optimization problem. 2) Analytical methods: They are used in a wide range of services in power systems.…”

Impacts of grid‐scale battery systems on power system operation, case of Baltic region

“…[76,92,93]. The reliability of the electrical grid is endangered by the high penetration of such volatile energy sources, causing problems in balancing supply and demand, voltage instability and power quality [94]. Decentralised energy generation mitigates problems in transmission grids, for example, reduced line losses, but can induce new problems in distribution grids, such as overvoltages, and requires new operation strategies [95].…”

“…System operators, utility companies, electricity consumers [111][112][113][114] Energy cost optimisation Also known as energy arbitrage or storing power purchased at off-peak times and selling it on-peak Utility companies, electricity consumers [78,79,94,97,[115][116][117][118][119][120] Increased distributed generation self-consumption…”

A Flexible Operation and Sizing of Battery Energy Storage System Based on Butterfly Optimization Algorithm

“…The optimal size of the battery and energy scheduling of an isolated microgrid was investigated in [28] using the firefly optimization algorithm. Furthermore, the optimal BESS for gridconnected microgrids subject to wind uncertainties has been investigated in [29] using stochastic programming.…”