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Research on economic benefits of “source, storage and load” in a multi-energy complementary combined cooling-heating-electricity system

机译:多能互补合并冷却加热电力系统“源,储存和载荷”经济效益研究

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In order to solve the randomness and volatility of new energy power generation, promote the local consumption of renewable energy, and maximize the economic efficiency of CCHP system, this paper combines the schedulable resources of energy production, energy storage and energy consumption into a “source storage” system, which can meet the demand of power supply, heating and cooling at the same time. The objective function is to minimize the daily operation cost of the cold heat electric hybrid energy system, and the power balance and equipment capacity of the system are constrained. Using the established mathematical model of the system framework, the particle swarm optimization algorithm is used to improve the CCHP programming model to obtain the adaptation curve and the hourly output of the optimal operation of the equipment with the maximum economic benefit. The operation and maintenance costs of the two modes are analyzed in depth. The results show that the optimization of “source storage and load” system not only improves the reliability of energy supply, but also reduces the cost of operation and maintenance and improves the economic benefits of the system.
机译:为了解决新能源发电的随机性和波动性,促进可再生能源的局部消耗,并最大限度地提高CCHP系统的经济效率,将能源生产,能量储存和能源消耗的可持续资源集成为“源”存储“系统,可以同时满足电源,加热和冷却的需求。目标函数是最小化冷热电动混合能量系统的日常运营成本,系统的功率平衡和设备容量受到约束。使用系统框架的已建立的数学模型,粒子群优化算法用于改进CCHP编程模型,以获得适应曲线和具有最大经济效益的设备的最佳运行的每小时输出。两种模式的操作和维护成本深入分析。结果表明,“源存储和负载”系统的优化不仅提高了能源供应的可靠性,而且还降低了运行和维护成本,提高了系统的经济效益。

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