基于碳达峰,碳中和的背景及大型港口清洁能源资源富有的特点,提出一种建立在大型港口这一特定场景上的多种清洁能源联合供给系统,建立整合风能、太阳能、氢能、储能及市电的大型港口多能联供系统模型。基于某港口春季典型日实测数据,在是否计及柔性负荷两种模型下,以降低港口电力成本为目标,采用粒子群优化（PSO）算法对各种能源及柔性负荷的调配以优化联供模型。结果表明：两种模型通过对系统的优化达到对电力削峰填谷、降本增效的作用,与仅使用市电供能相比,电力成本分别降低32.60%、37.73%;清洁能源使用占比分别提高55.46%、58.54%,验证了大型港口多能联供系统的可行性与实用性。
Abstract
Based on the background of “Carbon Peak, Carbon Neutral” and the richness of clean energy resources in large ports, a multi-clean energy integrated supply system is proposed for large ports, and a model of multi-energy integrated supply system for large ports that combines wind energy, photovoltaic energy, hydrogen energy, energy storage, and utility power is established. According to the measured data of a port on the typical day in spring, the particle swarm optimization （PSO） algorithm is adopted to optimize the integrated supply model by deploying various energy sources and flexible loads with the goal of reducing the power cost of the port under the two models with or without flexible loads. The results show that the two models achieves the effect of peak shaving, valley filling, cost reduction and efficiency improvement through the optimization of the system. Compared with the power supply from the utility only, the costs of electricity of the two models are reduced by 32.60% and 37.73%, respectively. The percentages of the using clean energy are increased by 55.46% and 58.54% respectively, which verifies the feasibility and practicability of the integrated supply system for large ports.
关键词
港口码头 /
清洁能源 /
电力调度 /
柔性负荷 /
优化调度 /
多能联供系统
Key words
port and harbor /
clean energy /
power dispatching /
flexible load /
optimal dispatch /
multi-energy combined supply system
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基金
山东省重大科技创新工程项目（2021SFGC0601）
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