Particle swarm optimisation-based optimal photovoltaic system of hourly output power dispatch using lithium-ion batteries

Abstract

Power fluctuation of a grid-connected photovoltaic (PV) system can give unnecessary stress and impacts to the point where it is connected. To minimise the output power fluctuation, a hybrid PV system and battery energy storage (BES) system can be developed and controlled so that the total output of the system is smoothed out and dispatched on an hourly basis to the electricity grid. This paper presents an improved mitigation strategy using Lithium-ion (Li-ion) BES namely the State-of-Charge Feedback (SOC-FB) controller with the goal of minimising the output power fluctuations of the PV system while ensuring the Li-ion BES operational constraints are regulated at the desired range. To optimally control the SOC-FB controller, Particle Swarm Optimisation algorithm was used to obtain an optimal dispatch of the PV/BES system while maintaining the BES operational constraints at the desired range. A simulation study was carried out using the MATLAB/Simulink software with the simulation results showing the acceptable performance of the proposed hybrid PV/BES hourly power dispatch control strategy. The simulation results also showed that the optimal size of BES can be reduced up to 1.6% using Li-ion battery. This indicates the reasonable performance of the Li-ion batteries especially when it comes to mitigating the power fluctuations of the PV system output.

Accurate battery model parameter identification using heuristic optimization

“…The justification for selecting these three algorithms is due to their wide applicability and readily to be implemented in Matlab. These algorithms also have been proven to deliver good optimization accuracy, particularly in battery storage application in renewable energy sources [7,12,13,[21][22][23].…”

“…The simulation technique can reduce the cost of commercialization of new technology as it can 334 avoid the unnecessary procedures in testing so as avoiding the purchase of expensive measuring instruments. Simulation studies of BES control system have been extensively carried out in the past [7][8][9][10][11][12][13]. In this regard, several battery models were proposed to further evaluate and develop the BES control system.…”

The fuzzy particle swarm optimization algorithm design for dynamic positioning system under unexpected impacts

“…The fitness function is used for iterations to value the quality of all the proposed solutions to the problem in the current population. The different features of fitness function affect how easy or difficult the problem is for a PSO algorithm [21]. Suitable fitness function can be chosen according to the demand of the study.…”

An Estimation of Hydraulic Power Take-off Unit Parameters for Wave Energy Converter Device Using Non-Evolutionary NLPQL and Evolutionary GA Approaches

“…It is due to the advancement of fast computing technologies that can be reliably used. A variety of studies were performed using different types of mathematical algorithms, such as non-linear programming by quadratic Lagrangian (NLPQL) and genetic algorithm (GA), Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), Tabu Search (TS), et cetera, in order to obtain the best parameters for the design model [18][19][20][21][22][23]. For example, GA has been used to optimise the parameters of state-of-charge (SOC) controllers for battery energy storage in photovoltaic device applications [21].…”