Optimal hybrid participation of customers in a smart micro-grid based on day-ahead electrical market

作者:Heydar Chamandoust

摘要

One of main challenges in the many countries with attention to growth people in the world is sustainable consumption and production of energy to improve environmental and economic issues by smart energy systems. In this paper, a multi-objective function model is developed to supply the demand of a smart micro-grid (SMG) with the aim of minimizing first) the operation cost, second) the emission pollution, and third) the deviation between the original demand curve and its desired level in the day-ahead time period. The third proposed objective function is a new strategy which can be used by the SMG operators to manage the demand consumption through responsible customers (RCs) with shiftable loads. Moreover, a number of consumers can participate in the energy management problem of the system through curtailing the demand as a reserve. The proposed objective functions are optimized to obtain the non-dominated solutions using the epsilon-constraint method. Then, the best solution is selected using combined fuzzy and Weighted sum approaches. To evaluate the effectiveness of the proposed model and its solution approach, it is applied on a test system considering four different case studies. The emission pollution and operation cost in the first case (base case) are 8832.24 kg and $692,930.2. In second case and with the participation of reserve, the reduction of the operation cost and the emission are equal to 6.03% and 7.98% than first case. With the participation of the demand shifting strategy in third case, operation cost and the emission are decreased by 20.2% and 19.89% according to base case. Finally, in fourth case and with participation of reserve and demand shifting strategy, the operation cost and the emission pollution are reduced by 26.5% and 38.1% in comparison with the base case.

论文关键词:Multi-objective functions, Smart micro-grid, Reserve, Epsilon-constraint method, Weighted sum approach

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论文官网地址:https://doi.org/10.1007/s10462-022-10154-z