基于全局优化的智能电网家庭负荷侧管理

A. Recioui
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引用次数: 4

摘要

需求侧管理(DSM)是一种使供电公司能够有效管理不断增长的电力需求和供电质量的策略。DSM项目的主要目标是改善财务绩效和客户关系。这个想法是为了鼓励消费者在高峰时段减少能源使用,或者将能源使用时间转移到非高峰时段。DSM控制着电力需求和供应之间的匹配。电力需求侧管理的另一个目标是维持电力质量,以使负荷曲线趋于平稳。在本章中,将遗传算法与需求侧管理技术相结合,寻找社区内N栋建筑的最优能源消耗调度。该问题被表述为以降低峰值负荷和最小化能源成本为目标的多目标优化问题。仿真结果表明,所采用的策略能够规划大量电气设备的日常能耗,并且在计算成本方面具有良好的性能。
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Home Load-Side Management in Smart Grids Using Global Optimization
Demand-side management (DSM) is a strategy enabling the power supplying companies to effectively manage the increasing demand for electricity and the quality of the supplied power. The main objectives of DSM programs are to improve the financial performance and customer relations. The idea is to encourage the consumer to use less energy during peak hours, or to move the time of energy use to off-peak times. The DSM controls the match between the demand and supply of electricity. Another objective of DSM is to maintain the power quality in order to level the load curves. In this chapter, a genetic algorithm is used in conjunction with demand-side management techniques to find the optimal scheduling of energy consumption inside N buildings in a neighborhood. The issue is formulated as multi-objective optimization problem aiming at reducing the peak load as well as minimizing the energy cost. The simulations reveal that the adopted strategy is able to plan the daily energy consumptions of a great number of electrical devices with good performance in terms of computational cost.
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