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• W4375866683 abstract "Supply-and-demand-side resource management and demand-side load management (DSLM) are important techniques for addressing power system uncertainties. Demand-side load management allows the load profile to be reshaped to reduce the peak demand and overall cost. Many demand-side load management problems have been solved using different demand response programmesprograms as well as conventional numeric and metaheuristic methods. However, it can be applied only toonly to a limited number of devices of certain types. Of the six direct load control demand response techniques for demand-side load management, the performance of the day-ahead load-shifting and flexible load curve DSLM techniques are compared in this study. These techniques can be used for a larger number of devices of more types. The demand-side load management problem is formulated as a minimization problem to achieve peak demand reduction and cost minimization. Novel metaheuristic optimizers are used to perform demand-side load management, and comparative analysis is conducted for the cost and peak load reduction. The simulation results are verified using the fmincon function of MATLAB. The simulation results indicate that the aforementioned algorithms can be applied to a larger number of devices of more types to achieve considerable savings by minimizing the cost and peak load demand. Moreover, the load-shifting demand-side load management technique is more beneficial from the system operator’s perspective than from the customer’s perspective. In contrast, the flexible load curve demand-side load management technique is more beneficial from the customer’s perspective." @default.
• W4375866683 created "2023-05-10" @default.
• W4375866683 creator A5023464131 @default.
• W4375866683 creator A5062438748 @default.
• W4375866683 date "2023-05-07" @default.
• W4375866683 modified "2023-09-29" @default.
• W4375866683 title "Novel Metaheuristic Optimizers Based Load Shifting and Flexible Load Curve Techniques for Demand-side Load Management" @default.
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• W4375866683 doi "https://doi.org/10.1080/23080477.2023.2208398" @default.
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