Gravitational search algorithm optimization algorithm for grid distributed energy storage resource pool regulation matching load peak–valley and operation constraints - Zhichao Lin; Busheng Luo; Yingmin Wang; Lingfei Xie; Xiangyang Su; Gang Chen; Yuting Huang (Discover Internet of Things)
Abstract The precise regulation of distributed energy storage resource pools can enhance the capacity to stabilize the peak-valley load difference of the power grid, mitigate load fluctuations, ensure efficient utilization of renewable energy, and reduce power grid losses. Consequently, this study investigates the GSA optimization algorithm for regulating distributed energy storage resource pools in the power grid, which can address load peaks and valleys while adhering to operational constraints. The objective function is defined as the load peak-valley difference, load variance, renewable energy utilization rate, and grid losses. The operational constraints encompass aspects such as power storage, operation, voltage, and load reduction limitations. Following the construction of a distributed energy storage resource pool regulation model, the GSA optimization algorithm is employed to solve it, identify the global optimal solution from the optimal regulation solution set, and achieve the regulation of the energy storage resource pool. The results demonstrate that after applying the algorithm, the average peak-valley difference and load variance of the power grid are 1.27 kW and 0.088 kW2, respectively. The average utilization rate and loss of renewable energy are 99.085% and 114.809 kW, respectively. This method effectively reduces the peak load of the power grid, addresses the issue of low valley load, and significantly reduces load fluctuations while maintaining low losses and high utilization of renewable energy, thereby ensuring stable operation of the power grid.