Economic Dispatch of PV-Integrated Power System with Optimally Sized Battery Energy Storage System using Particle Swarm Optimization
AbstractRapid escalation of fuel prices, depletion of fossil fuel reserves and environmental concerns have compelled power system operators to incorporate the Renewable Energy (RE) resources for example solar in the energy mix to meet the demand. Although the renewable energy resources are valuable and cost effective, they are unpredictable in nature and are dependent on weather conditions. The market for solar energy has been expanding rapidly worldwide. Solar-Photovoltaic (PV) systems generally have considerable power variations, which include voltage fluctuations and frequency variations. The intermittent power generation of a solar farm can perturb the supply and demand balance of the whole power system. Therefore, mitigating the adverse effects on the grid from an intermittent PV source has become essential for increasing the penetration level of PV systems. In the power system operations planning, the economic load dispatch of thermal generating system is one of the most important problems. Recent global inclination towards the utilization of more and more renewable energy makes this problem important than ever. Efficient and reliable planning of power system with significant penetration of these resources brings challenges due to their fluctuating and uncertain characteristics. Energy storages are emerging as a predominant sector for renewable energy applications. Recently, Battery Energy Storage System (BESS) has become a promising solution to help PV integration, due to the flexible real power control of the batteries. This research aims at conducting the economic dispatch of thermal and PV system with battery storage. The sizing methodology is optimized using Particle Swarm Optimization algorithm to minimize the cost of investment and losses incurred by the system in form of peak load shaving. The proposed methodology is tested and validated on a standard IEEE 30 bus test system.
Keywords—Battery energy storage system, Economic Dispatch, Photovoltaic, Particle swarm optimization, Renewable energy.
Jun 27, 2018
How to Cite
SEGERA, Lonah Nyaboke. Economic Dispatch of PV-Integrated Power System with Optimally Sized Battery Energy Storage System using Particle Swarm Optimization. Proceedings of Sustainable Research and Innovation Conference, [S.l.], p. 102-108, june 2018. ISSN 2079-6226. Available at: <http://sri.jkuat.ac.ke/ojs/index.php/proceedings/article/view/676>. Date accessed: 29 jan. 2020.
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.