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Authors: Si, Shuqian | Dou, Zhenhai | Wang, Zichen | Dong, Jun

Article Type: Research Article

Abstract: CCHPs (Combined Cooling, Heating, and Power Systems) are capable of providing cold energy, heat, and electricity to users, allowing cascading utilization of energy and improving energy efficiency. The imbalance between cooling, heating, and electrical energy makes it difficult to accurately evaluate the performance of a CCHP system. Existing indices for evaluating the performance of the CCHP system do not account for the influence of time-sharing tariffs; therefore, the quantitative index of time-sharing is added and the time-sharing economic exergy efficiency of the radiator is established. Given that the electrical and thermal characteristics of the advanced absolutely hot compressed airheat storage …system (AA-CAES) can complement the CCHP system, a model of the CCHP system with AA-CAES is established, which can be used to validate the validity of the quantitative evaluation index of time-sharing. A planetary search algorithm is proposed for solving the CCHP system model to address the multi-parameter solving characteristics of the CCHP system model and the disadvantages of the existing multi-objective optimization algorithms, which are prone to local optimality and poor optimization accuracy. Simulation validation demonstrates that the time-sharing economic exergy efficiency proposed in this paper can more accurately reflect the total energy consumption of the CCHP system than the existing evaluation indices. The performance of the CCHP system can be improved by using AA-CAES as a heat storage device. Show more

Keywords: Combined cooling, heating and power system, advanced absolute hot compressed air heat storage system, integrated energy utilization ratio, time-sharing economic exergy efficiency, planetary search algorithm

DOI: 10.3233/JCM-226745

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 23, no. 4, pp. 2205-2224, 2023

Authors: Wang, Chen | Rong, Xiao | Dou, Zhenhai | Liu, Yawei | Shao, Kaiguang | Liu, Lianxin

Article Type: Research Article

Abstract: Distributed power grid integration contributes to both the reduction of greenhouse gas emissions and the protection of the environment. Nevertheless, the uncertainty and volatility associated with the production of clean renewable energy adds additional challenges to microgrid dispatch. The paper presents an adaptive mutant bird swarm algorithm and suggests a comparison mechanism based on population fitness variances and optimal values in order to overcome the shortcomings of BSA, in particular its tendency to self-correct into local optimum and slow convergence speed. First, the algorithm determines if the population is in the local optimal state. The local optimal individual is then …subjected to Cauchy mutation in order to determine the optimal value again. This improves the accuracy and speed of the BSA. Based on simulation results, the improved algorithm has higher optimization accuracy and faster optimization speed, which demonstrates the effectiveness and advancement of the algorithm proposed in this research. Show more

Keywords: Micro grid, optimal scheduling, bird swarm algorithm, adaptive mutation, distributed power

DOI: 10.3233/JCM-226338

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 22, no. 6, pp. 2279-2293, 2022