考虑一次能源不确定性的火电厂运行优化降额问题的混合整数线性规划方法

Nur Fauziyah, N. Hariyanto
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引用次数: 0

摘要

电力在一个国家的经济发展和人民生活中起着重要的作用。随着人口的增加,对电力的需求也在增加,导致电力供应短缺的问题,从而导致巨大的经济损失。需要考虑的重要问题是用于发电的一次能源,特别是煤,火电厂的一次能源之一,煤的可用性会导致火电厂运行的非最优调度,从而导致降额问题。本文提出了一种将机组调度和经济调度、煤炭转运、配煤和库存问题的算法相结合的新算法,该算法将基于Python编程语言的Pyomo与混合整数线性规划(MILP)方法相结合来实现。利用该算法根据煤炭库存情况确定电厂的最佳送煤时间和维护时间。结果表明,该算法的引入使电厂运行成本降低了5.57%,达到了最优水平。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Mixed-Integer Linear Programming (MILP) Approach for Solving Derating Problems in Optimization of Thermal Power Plants Operation Considering Primary Energy Uncertainty
Electricity has an important role in economic development and people’s lives in a country. As the population increases, so does the demand for electricity, resulting in the problem of shortages of electricity supply which leads to huge economic losses. The important problem to be considered is the primary energy used to produce electricity, especially coal, one of the primary energies of thermal power plants where coal availability has a contribution to the non-optimal scheduling of thermal power plants operation which causes the derating problems. This paper proposes a new algorithm with combining algorithms of unit commitment and economic dispatch, coal transshipment, coal blending and inventory problems which will be implemented using Pyomo based on Python programming language with Mixed Integer Linear Programming (MILP) approach. The new algorithm is used to determine the optimal time for coal delivery and maintenance of power plants according to coal inventory. The results showed that the addition of this new algorithm provides 5.57% cheaper and more optimal power plants operation cost.
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