Abstract
This paper presents a novel incentive-based load shedding management scheme within a microgrid environment equipped with the required IoT infrastructure. The proposed mechanism works on the principles of reverse combinatorial auction. We consider a region of multiple consumers who are willing to curtail their load in the peak hours in order to gain some incentives later. Using the properties of combinatorial auctions, the participants can bid in packages or combinations in order to maximize their and overall social welfare of the system. The winner determination problem of the proposed combinatorial auction, determined using particle swarm optimization algorithm and hybrid genetic algorithm, is also presented in this paper. The performance evaluation and stability test of the proposed scheme are simulated using MATLAB and presented in this paper. The results indicate that combinatorial auctions are an excellent choice for load shedding management where a maximum of 50 users participate.
Highlights
With the ever increasing population and growing industrial sector in the developing countries, providing a reliable energy service can be very difficult
The authors concluded that PSO works better in former problem type whereas, genetic algorithm (GA) outperform PSO when exposed to the later problem types, studies have showed that despite some strengths and shortcomings or of both of the algorithms, hybridization yields better results for many problems in comparison to the standalone GA
The paper organization is as follows: System model is presented in Section 2; Section 3 presents the overall auction process along with the winner determination process; a detailed simulation study is explained in Section 4; and Section 5 concludes the paper
Summary
With the ever increasing population and growing industrial sector in the developing countries, providing a reliable energy service can be very difficult. The device layer is further divided into two sub-layers: the first one being the thing layer to sense environment, control home appliances, and collect data and the second one being the gateway layer which controls how to establish a connection to the elements of thing layer These advancements have helped in collecting and processing data from smart and micro grids for applications of energy trading and load management. The authors concluded that PSO works better in former problem type whereas, GA outperform PSO when exposed to the later problem types, studies have showed that despite some strengths and shortcomings or of both of the algorithms, hybridization yields better results for many problems in comparison to the standalone GA or PSO [27,28,30]; hybridization of metaheuristics is common across a variety of evolutionary algorithms [31] Both these methods have been extensively used for solving combinatorial auctions’. A winner determination solution for single sided reverse combinatorial auction for energy trading applications (one buyer multiple sellers). The paper organization is as follows: System model is presented in Section 2; Section 3 presents the overall auction process along with the winner determination process; a detailed simulation study is explained in Section 4; and Section 5 concludes the paper
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