Abstract
The problems associated with the deployment of intermittent, unpredictable and uncontrollable solar photovoltaics (PV) can be feasibly solved with battery energy storage systems (BESS), particularly in terms of optimizing the available capacity, increasing reliability and reducing system losses. Consequently, the degree of importance of BESS increases in proportion to the level of PV penetration. Nevertheless, the respective high cost of BESS imposes a huge concern and the need to establish a techno-economic solution. In this paper, we investigate the system losses and power quality issues associated with the high deployment of PV in a grid network and hence formulate BESS capacity optimization and placement methodology based on a genetic algorithm. The concept of the proposed methodology has been tested and validated on a standard IEEE 33 bus system. A brief stepwise analysis is presented to demonstrate the effectiveness and robustness of the proposed methodology in reducing the incremental system losses experienced with increased PV penetration. Furthermore, based on the proposed optimization objectives, a comparative study has also been performed to quantify the impact and effectiveness of aggregated and distributed placement of BESS. The results obtained exhibit a substantial reduction in system losses, particularly in the case of distributed BESS placement.
| Original language | English |
|---|---|
| Article number | 140 |
| Journal | Energies |
| Volume | 13 |
| Issue number | 1 |
| DOIs | |
| State | Published - 27 Dec 2019 |
Bibliographical note
Publisher Copyright:© 2019 by the authors. Licensee MDPI, Basel, Switzerland.
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
Keywords
- Battery energy storage system
- Distribution network
- Renewable energy sources
ASJC Scopus subject areas
- Renewable Energy, Sustainability and the Environment
- Fuel Technology
- Engineering (miscellaneous)
- Energy Engineering and Power Technology
- Energy (miscellaneous)
- Control and Optimization
- Electrical and Electronic Engineering
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