Abstract
This paper proposes a new optimization technique that uses Particle Swarm Optimization (PSO) in residential grid-connected photovoltaic systems. The optimization technique targets the sizing of the battery storage system. With the liberation of power systems, the residential grid-connected photovoltaic system can supply power to the grid during peak hours or charge the battery during non-peak hours for later domestic use or for selling back to the grid during peak hours. However, this can only be achieved when the battery energy system in the residential photovoltaic system is optimized. The developed PSO algorithm aims at optimizing the battery capacity that will lower the operation cost of the system. The computational efficiency of the developed algorithm is demonstrated using real PV data from Strathmore University. A comparative study of a PV system with and without battery energy storage is carried out and the simulation results demonstrate that PV system with battery is more efficient when optimized with PSO.
Highlights
Nowadays electricity access plays a vital role and governments and private sector are investing in the electricity domain to ensure sustainable development
The plots are for one sample day of the year (53rd) and we can realize that the load demand entirely depends on the grid during off-peak hours (00:00 to 7:00)
If the energy consumption is kept constant and the hourly power profile is decreased by 5%, the results show that the optimal battery capacity changes from 1200Ah to 1100Ah and the annual income of the PV system owner decreases by 24%
Summary
Nowadays electricity access plays a vital role and governments and private sector are investing in the electricity domain to ensure sustainable development. One of the alternatives is integrating optimally sized energy storages into a grid-connected PV system. Authors in [9] introduced a PSO-based algorithm for optimally sizing constituents of a hybrid renewable system, aiming to maximize the energy production to cover the load at lowest cost and enhanced reliability. An improved firefly algorithm was proposed in [10] to optimally locate and size the battery energy storage system for mitigating the voltage rise in PVDG integrated distribution network. Authors in [11] proposed a two layer optimization procedure using PSO to optimize the battery size of a grid-tied PV system. Authors in [13] proposed a mechanism for minimizing the operation cost of a grid-tied system by optimizing the operation schedule of different energy sources in a residential complex energy system. Regis et al.: Optimal Battery Sizing of a Grid-Connected Residential Photovoltaic System for Cost
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