COST-EFFECTIVE ENERGY MANAGEMENT SYSTEMS STRATEGY IN OPTIMIZATION OF PHOTOVOLTAIC FOR GRID-CONNECTED SYSTEM

Noor Ilham  Shamsuddin; Madihah  Md Rasid; Mohd Shafiq  Anuar

doi:10.11113/jurnalteknologi.v85.17688

Authors

Noor Ilham Shamsuddin School of Electrical Engineering, Faculty of Engineering, Universiti Teknologi Malaysia, 81310 UTM Johor Bharu, Johor, Malaysia
Madihah Md Rasid School of Electrical Engineering, Faculty of Engineering, Universiti Teknologi Malaysia, 81310 UTM Johor Bharu, Johor, Malaysia https://orcid.org/0000-0002-1947-1174
Mohd Shafiq Anuar PLUS Berhad (S5&S6), KM25 Lebuhraya Perling, 81200, Johor Bahru, Johor, Malaysia https://orcid.org/0000-0002-0179-3714

DOI:

https://doi.org/10.11113/jurnalteknologi.v85.17688

Keywords:

Renewable energy, PV generation, energy management system, optimization, energy storage system

Abstract

Renewable Energy Source (RES) based Distributed Generation (DG) like Photovoltaic (PV) is widely integrated into the distribution network, particularly for residential. With proper planning, the installation of optimal PV in the network is capable of minimizing the dependency on the power grid generation. However, the optimum use of solar energy has been limited by the weather and the load variation. At the particular time, the generated PV output is not fully utilized during the minimum load. The excessive generation of PV power occurs and causes an increase in the cost of electricity consumption. Therefore, the purpose of this paper is to optimize the PV size for the grid-connected system considering the Battery Energy Storage System (BESS) and the proper Energy Management System (EMS) Strategy in order to reduce the grid power consumption. BESS is introduced to store the excess PV power generated during peak hours, while the cost-effective EMS strategy is proposed to ensure the RES is fully employed. The number of PV panels is optimized using Particle Swarm Optimization (PSO) technique. The implementation of PSO in optimising PV size can reduce the number of PV panels by 21% compared to the conventional method.

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