Multi-objective optimization and multi-criteria evaluation framework for the design of distributed multi-energy system: A case study in industrial park

The building sector, as a major energy consumer, urgently needs cleaner and greener energy supply systems. To achieve this, a distributed multi-energy system (DMES) that incorporates energy storage and renewable energy is constructed. Moreover, a novel multi-objective optimization and multi-criteria evaluation framework is proposed for DMES design. In the optimization stage, the Maximum Rectangle Method optimizes the search range of Non-dominated Sorting Genetic Algorithm-II, while the Genetic Algorithm enhances the decision-making method for designing the single-system scheme. In the evaluation stage, the combination of Analytic Hierarchy Process, Entropy Weight Method, and Set Pair Analysis is utilized to evaluate multiple system schemes. Finally, the impact of energy prices, renewable energy, and load uncertainty on system performance is analyzed. Taking an industrial park in Jinzhong as example, the proposed DMES and its alternative systems with different operation modes are analyzed. Further, the effects of load, renewable energy and energy price on DMES are investigated. The DMES has the better comprehensive performance than the other systems, and the following electrical load (FEL) operation strategy is more suitable for the DMES. Due to the impact of renewable energy, load and energy price uncertainties on DMES performance, increasing renewable energy integration, improving load forecasting accuracy, and raising grid electricity prices would enhance the overall performance. The proposal and relevant results may provide theoretical guidance for relevant research and application in building sector.