Adaptive Model-Based Receding Horizon Control of Interconnected Renewable-Based Power Micro-grids for Effective Control and Optimal Power Exchanges

PETER ANUOLUWAPO GBADEGA, A. K. Saha
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引用次数: 13

Abstract

This paper proposes an Adaptive Model-based Receding Horizon Control Scheme (AMRHCS), which allows taking into consideration the uncertainty power production of renewable energy resources, demand response, the variance of real-time electricity price, load demand and as well as respecting the special constraints for optimal performance and economic benefits of the micro-grids. The essence of this study is to propose a control scheme for the interconnected power microgrids so as to minimize the operating costs of the individual micro-grid, the power purchased by each micro-grid, the pollutant gas emissions, energy procured from the host grid and from the other micro-grids. Therefore, in order for these objectives to be achieved, an adaptive MPC controller is utilized to locate the best patterns for power exchange and state of energy storage system among micro-grids. More so, to investigate the optimal control action of the interconnected power micro-grids under the proposed control framework, we iteratively formulated a finite horizon Mixed Integer Linear Programming (MILP) problem. The MATLAB simulation results demonstrated the superiority of the proposed control technique in terms of excellent performance and economic benefits of the micro-grids.
基于自适应模型的互联可再生电力微电网后退水平控制,实现有效控制和最优电力交换
本文提出了一种考虑可再生能源发电的不确定性、需求响应、实时电价变化和负荷需求,并尊重微电网最优性能和经济效益的特殊约束的基于自适应模型的后退地平线控制方案(AMRHCS)。本研究的实质是提出一种互联微电网的控制方案,以使单个微电网的运行成本、每个微电网的购电成本、污染物气体排放、从主电网和其他微电网获取的能量最小化。因此,为了实现这些目标,利用自适应MPC控制器来定位微电网间电力交换和储能系统状态的最佳模式。此外,为了研究在该控制框架下互联微电网的最优控制行为,我们迭代地构造了一个有限水平混合整数线性规划(MILP)问题。MATLAB仿真结果表明,所提出的控制技术在微电网的优良性能和经济效益方面具有优越性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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