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Electrical vehicles (EVs) are among the fastest‐growing electrical loads that change both temporally and spatially at distribution networks. Moreover, the existence of uncertain parameters, such as EVs as well as domestic loads in power networks, poses serious operational challenges for them. Accordingly, stochastic studies of system performance ar...
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Electrical vehicles (EVs) are among the fastest-growing electrical loads that change both temporally and spatially on distribution networks. The large-scale integration of EVs equipped with power electronic-based chargers into distribution networks, to meet new electrical load demands, can cause instability and power quality issues. Moreover, the a...
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... Furthermore, uncertainties about some input data, such as active and reactive load demands, as well as the unpredictable behavior of EV owners create unparalleled reliability and security issues to the overall distribution network. Therefore, probabilistic studies with a high degree of precision and tractable algorithms are necessary for the evaluation of uncertain behavior toward output variables of power system safety and balance operation [243]. ...
The increase in energy consumption, environmental pollution issues, and low-carbon agenda has grown the research area of demand side management (DSM). DSM programs provide feasible solutions and significantly enhance the efficiency and sustainability of electrical distribution systems. This paper classifies and discusses the broad definition of demand-side management based on the comprehensive literature study considering demand response and energy efficiency. The implementation of Artificial Intelligence (AI) algorithms in demand-side management applications has been employed in many studies to help researchers make optimal decisions and achieve predictions by analyzing the massive amount of historical data. Owing to its simplicity and consistent performance in fast convergence time, Particle Swarm Optimization (PSO) is widely used as a part of the swarm AI algorithm and has become a prominent technique in the optimization process to exploit the full benefit of the demand-side program. The variants of PSO have been developed in the past years to overcome the limitations of the original PSO and solve the high complexity and uncertainty in the DSM optimization process. The proposed PSO-based algorithm can optimize consumers’ consumption curves, reducing the peak demand and hence minimizing the electricity cost when integrated with the DR programs or EE measures. The research works of the PSO algorithm in DSM have seen an increasing trend in the past decade. Therefore, this paper reviewed the application of the PSO-based algorithm in DSM fields with some constraints and discussed the challenges from the previous work. The potential for new opportunities is identified so that PSO methods can be developed for future research.
