Optimal Planning of Multi-Carrier Energy Hub System Using Particle Swarm Optimization

Alaa Farah, H. Hassan, K. Kawabe, T. Nanahara
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引用次数: 5

Abstract

The present paper introduces a particle swarm optimization (PSO) algorithm to define the optimal combination of the energy hub infrastructures and the optimal scheduling of natural gas energy, wood chips biomass energy and electrical energy that guarantee economical operation of energy hub. Three objective functions are considered during the study: minimizing net present cost, minimizing total CO2 emission and minimizing both net present cost and CO2 emission simultaneously. Simulation results prove the effectiveness of proposed PSO to find the optimal energy hub scheduling. The results show that a natural gas turbine (NGT) is superior to biomass generation unit in reducing the total operating cost. On the other hand, biomass wood chips generator is superior to NGT in reducing total CO2 emission. The results show that using a mix of NGT and biomass generator can enhance the system performance of the energy hub by minimizing both total operating cost and CO2emissions simultaneously.
基于粒子群算法的多载波能量轮毂系统优化规划
为了保证能源枢纽的经济运行,提出了一种粒子群优化算法来确定能源枢纽基础设施的最优组合以及天然气、木屑、生物质和电能的最优调度。研究过程中考虑了三个目标函数:净当前成本最小化、总CO2排放最小化、净当前成本和CO2排放同时最小化。仿真结果证明了该算法在寻找最优能源枢纽调度问题上的有效性。结果表明,天然气发电机组在降低总运行成本方面优于生物质发电机组。另一方面,生物质木屑发生器在减少二氧化碳总排放量方面优于NGT。结果表明,混合使用NGT和生物质发电机可以同时降低总运行成本和二氧化碳排放,从而提高能源枢纽的系统性能。
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