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Open AccessArticle

Regional Integrated Energy Site Layout Optimization Based on Improved Artificial Immune Algorithm

State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University (Baoding), Baoding 071003, China
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Energies 2020, 13(17), 4381; https://doi.org/10.3390/en13174381
Received: 1 July 2020 / Revised: 19 August 2020 / Accepted: 20 August 2020 / Published: 25 August 2020
(This article belongs to the Special Issue Integrated Energy Systems and Transportation Electrification)
Regional integrated energy site layout optimization involves multi-energy coupling, multi-data processing and multi-objective decision making, among other things. It is essentially a kind of non-convex multi-objective nonlinear programming problem, which is very difficult to solve by traditional methods. This paper proposes a decentralized optimization and comprehensive decision-making planning strategy and preprocesses the data information, so as to reduce the difficulty of solving the problem and improve operational efficiency. Three objective functions, namely the number of energy stations to be built, the coverage rate and the transmission load capacity of pipeline network, are constructed, normalized by linear weighting method, and solved by the improved p-median model to obtain the optimal value of comprehensive benefits. The artificial immune algorithm was improved from the three aspects of the initial population screening mechanism, population updating and bidirectional crossover-mutation, and its performance was preliminarily verified by test function. Finally, an improved artificial immune algorithm is used to solve and optimize the regional integrated energy site layout model. The results show that the strategies, models and methods presented in this paper are feasible and can meet the interest needs and planning objectives of different decision-makers. View Full-Text
Keywords: integrated energy; planning; improved artificial immune algorithm; multi-objective; linear weighting method integrated energy; planning; improved artificial immune algorithm; multi-objective; linear weighting method
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MDPI and ACS Style

Xu, Y.; Zhang, J. Regional Integrated Energy Site Layout Optimization Based on Improved Artificial Immune Algorithm. Energies 2020, 13, 4381. https://doi.org/10.3390/en13174381

AMA Style

Xu Y, Zhang J. Regional Integrated Energy Site Layout Optimization Based on Improved Artificial Immune Algorithm. Energies. 2020; 13(17):4381. https://doi.org/10.3390/en13174381

Chicago/Turabian Style

Xu, Yan; Zhang, Jianhao. 2020. "Regional Integrated Energy Site Layout Optimization Based on Improved Artificial Immune Algorithm" Energies 13, no. 17: 4381. https://doi.org/10.3390/en13174381

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