近零能耗建筑电池优化调度的遗传算法驱动线性规划

G. Georgiou, P. Nikolaidis, L. Lazari, P. Christodoulides
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引用次数: 3

摘要

在过去十年中,欧盟对近零能耗建筑(nzeb)和建筑集成光伏(BIPV)系统的需求不断增加。这源于与提高建筑效率有关的能源驱动法规,需要更现实和更智能的技术来加强他们的就业和整体表现。除了非零排放建筑的被动能源效率措施(如隔热、节能器具等)外,还必须建立更先进和复杂的能源管理机制,以适应和支持它们对可持续发展的重要贡献。本文以光伏建筑净能耗最小为目标,采用遗传算法驱动的线性规划方法,对光伏建筑中蓄电池的日最优调度进行了研究。所获得的结果表明,使用这种方法尽可能地保持建筑物的电网能量水平具有很高的潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Genetic Algorithm Driven Linear Programming for Battery Optimal Scheduling in nearly Zero Energy Buildings
EU has seen an increasing demand for both nearly zero energy buildings (nZEBs) and building integrated Photovoltaic (BIPV) systems in the last decade. This stems from the energy-driven regulations relating to building efficiency improvements, requiring more realistic and smarter techniques to strengthen their employment and overall performance. Apart from the passive energy-efficiency measures of nZEBs (such as thermal insulation, energy saving appliances, etc.), more advanced and sophisticated energy management mechanisms have to take place in order to accommodate and support their crucial contribution to sustainable development. This paper presents the daily optimum dispatch of a battery, in a building with PV, using Linear Programming (LP) driven by Genetic Algorithm (GA), aiming the minimization of the building’s net energy. The obtained results show that there is a high potential of using such approaches for maintaining the net grid energy levels of a building as minimum as possible.
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