A Review of Multi-Objective Optimization-Based Site Selection for Power Plants: Principles and Methods
多目的最適化に基づく発電所の立地選定のレビュー：原理と方法 (AI 翻訳)
Liu Yang, Siteng Zhao, Peichao Gao, Xian Feng, Chengwei Guo
🤖 gxceed AI 要約
日本語
本論文は、世界的なエネルギー転換と中国の「ダブルカーボン」戦略の文脈において、多目的最適化を用いた発電所立地選定の研究を体系的にレビューする。2008年以降の研究動向、目的関数、制約条件、最適化アルゴリズムの4次元から分析フレームワークを構築し、風力発電所の立地選定が最も多いことを示した。遺伝的アルゴリズムが最も広く使用されている。
English
This paper systematically reviews research on multi-objective optimization for power plant site selection in the context of global energy transition and China's 'dual carbon' strategy. Analyzing four dimensions—research trends, objective functions, constraints, and optimization algorithms—it finds that wind farm site selection accounts for the largest proportion since 2008. Genetic algorithms are the most widely used method. The review provides a reference framework for feasibility assessment.
Unofficial AI-generated summary based on the public title and abstract. Not an official translation.
📝 gxceed 編集解説 — Why this matters
日本のGX文脈において
中国の事例ではあるが、多目的最適化による発電所立地選定の体系的なレビューは、日本の再生可能エネルギー導入促進における立地評価に示唆を与える。
In the global GX context
This review, set in China's 'dual carbon' context, offers a structured framework for multi-objective power plant siting. While China-specific, the methodological synthesis (especially for wind farms) is globally relevant for energy transition planning and spatial optimization.
👥 読者別の含意
🔬研究者:Provides a comprehensive framework for researchers working on power plant siting optimization and multi-criteria decision analysis.
🏢実務担当者:Useful for project developers and planners in assessing trade-offs between economic, environmental, and social factors in site selection.
🏛政策担当者:Can inform policy on spatial planning and renewable energy deployment strategies, particularly for wind power.
📄 Abstract（原文）
In the context of the global energy transition and China’s “double carbon” strategy, power demand continues to grow, leading to expanded power plant construction that faces challenges such as spatial resource conflicts and multi-objective trade-offs. Multi-objective optimization methods are widely used for coordinating economic, environmental, and social objectives in power plant site selection. This paper systematically reviews the application of multi-objective optimization in power plant site selection using bibliometric and classification methods. The review covers four dimensions, namely, research trends, objective functions, constraints, and optimization algorithms, thereby constructing a reference framework. The study revealed that research began in 2008, with wind farm site selection now accounting for the greatest proportion. Objective functions can be summarized into four dimensions: energy and utilization, costs or benefits, engineering feasibility, and environmental and social impacts. There are six types of constraints for optimization: economic, technical, environmental, social, resource, and spatial. Genetic algorithms and their variants are the most widely used. This framework enhances the scientific rigor of power plant site selection and supports feasibility assessment, providing methodological references for site selection for power plants.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.3390/app16136727first seen 2026-07-08 05:23:22
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