Utilization of energy storage systems in congestion management of transmission networks with incentive-based approach for investors
| Autor: | Ali Karimi, Nader Tarashandeh |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
Mathematical optimization
Renewable Energy Sustainability and the Environment Computer science 020209 energy Energy Engineering and Power Technology 02 engineering and technology 021001 nanoscience & nanotechnology Investment (macroeconomics) Energy storage Electric power system Incentive Electric power transmission Transmission (telecommunications) Hydroelectricity Genetic algorithm 0202 electrical engineering electronic engineering information engineering Electrical and Electronic Engineering 0210 nano-technology |
| Zdroj: | Journal of Energy Storage. 33:102034 |
| ISSN: | 2352-152X |
| Popis: | Electricity demand growth and other factors in the power system have increased the probability of congestion occurrence in power transmission lines. In recent years, there is more tendency for energy storage systems (ESSs) due to their high applications in the power system. One of these applications is the capability to relieve congestion. One of the main challenges of using ESSs is the high investment cost. In this paper, for expansion planning problem, a multi-objective optimization framework to relieve transmission congestion is proposed, combined with the use of new lines and ESSs. In the proposed framework, the viewpoint of the system operator and ESSs owner are simultaneously considered. Furthermore, an incentive-based approach for the investment of ESSs is suggested. The proposed method is implemented on the IEEE-RTS 24-bus system using pumped-storage hydro power plant (PSHP) and compressed-air energy storage (CAES) systems. The simulation results include a set of non-dominated optimal solutions that are obtained using the multi-objective genetic algorithm NSGA-II. The results provide optimal locations for new lines and ESSs and demonstrate the effectiveness of the incentive-based approach for selecting the best solution. |
| Databáze: | OpenAIRE |
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