Model predictive control scheme for investigating demand side flexibility in Singapore

Sarmad Hanif, Dante F. Recalde Melo, Mehdi Maasoumy, Tobias Massier, T. Hamacher, T. Reindl
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引用次数: 12

Abstract

Recently, power systems have experienced various changes, the most important one being the increase in the share of highly variable renewable energy supply (RES). To counteract the variability of RES, provision of flexibility from the demand side seems to be a viable option. In this paper, the heating, ventilation and air conditioning (HVAC) system, mostly installed in medium to large sized office buildings, is selected to provide demand side flexibility. A model predictive control (MPC) scheme in a receding horizon environment is deployed to provide an economic operation of the building, while respecting comfort constraints of dwellers. Furthermore, robustness is introduced in the MPC scheme to participate in both the energy and reserve market. Simulations are performed to demonstrate the performance of the developed controller under various price signals. In doing so, the controller is also evaluated with respect to its sensitivity towards economical and technical constraints. The National Electricity Market of Singapore (NEMS) is used as a case study and the most important parameters governing the challenges for integrating demand side flexibility in the grid are pointed out.
研究新加坡需求侧灵活性的模型预测控制方案
近年来,电力系统经历了各种变化,其中最重要的是高可变可再生能源供应(RES)份额的增加。为了抵消可再生能源的可变性,从需求方提供灵活性似乎是一个可行的选择。本文选择暖通空调(HVAC)系统,以提供需求侧的灵活性,主要安装在大中型写字楼中。在后退地平线环境中采用模型预测控制(MPC)方案,以提供建筑的经济运行,同时尊重居住者的舒适度约束。此外,在MPC方案中引入鲁棒性,使其同时参与能源市场和储备市场。通过仿真验证了所开发的控制器在各种价格信号下的性能。在此过程中,还评估了控制器对经济和技术限制的敏感性。本文以新加坡国家电力市场(NEMS)为例,指出了控制电网需求侧灵活性整合挑战的最重要参数。
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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