Economic-Environmental Modeling of Energy Storage Application in Electricity Industry: Using Multi-Objective PSO Algorithm

Implementing the energy storage improves power load response, and network reliability, as well as reduces the need to build new power capacity in the electricity Using the energy storage improves responsiveness power into load, increases network reliability, and reduces the need to build new power capacity in the electricity industry. Regarding the economic- environmental benefits of using energy storage in the electricity industry, the main objective of this research is to investigate the application of electrical network’s energy storage with the aim of minimizing losses, environmental pollution, and system fuel costs. In this regard, three scenarios have been designed under the multi-objective particle swarm optimization (PSO) algorithm, which in scenario number 1, network consumption load is provided only by diesel generators. In scenario number 2, the renewable energy sources of wind and solar are added to the network, and in scenario number 3 further diesel generator and wind turbine and solar panels, energy storages are added to the network, and the PSO algorithm for optimal placement of the storage devices is performed. The results show that the most efficient result for the designed purposes can be achieved by solving the model under scenario number 3. Accordingly, the amount of network losses, fuel costs, and pollution in motion from the first scenario (base scenario) to the third scenario shows a decrease of 432 kW, 13.7 thousand dollars, and 75 kg, respectively. These results can help to optimum usage of energy storage devices in order to improve sustainability and network security, losses decreasing, and pollution decreasing in the electricity industry.