A Review of Multi-Objective Optimization-Based Site Selection for Power Plants: Principles and Methods
Source abstract
Abstract
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.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Wind Energy Research and Development · Social Acceptance of Renewable Energy · Hybrid Renewable Energy Systems
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
State Grid Electric Power Engineering Research Institute Co., Ltd., Beijing 100069, China
Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
Funding
Science and Technology Project of the Headquarters of State Grid Corporation of China
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