Thermodynamic-Based Perceived Predictive Power Control for Renewable Energy Penetrated Resident Microgrids

Wenhui Shi, Lifei Ma (), Wenxin Li, Yankai Zhu, Dongliang Nan and Yinzhang Peng
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Wenhui Shi: China Electric Power Research Institute, Beijing 100192, China
Lifei Ma: China Electric Power Planning & Engineering Institute, Beijing 100120, China
Wenxin Li: Electric Power Research Institute of State Grid Xinjiang Electric Power Company, Urumqi 830011, China
Yankai Zhu: School of Electrical and Electronic Engineering, North China Electric Power University, Beijing 102206, China
Dongliang Nan: Electric Power Research Institute of State Grid Xinjiang Electric Power Company, Urumqi 830011, China
Yinzhang Peng: Electric Power Research Institute of State Grid Xinjiang Electric Power Company, Urumqi 830011, China

Energies, 2025, vol. 18, issue 12, 1-22

Abstract: Heating, ventilation, and air conditioning (HVAC) systems and microgrids have garnered significant attention in recent research, with temperature control and renewable energy integration emerging as key focus areas in urban distribution power systems. This paper proposes a robust predictive temperature control (RPTC) method and a microgrid control strategy incorporating asymmetrical challenges, including uneven power load distribution and uncertainties in renewable outputs. The proposed method leverages a thermodynamics-based R-C model to achieve precise indoor temperature regulation under external disturbances, while a multisource disturbance compensation mechanism enhances system robustness. Additionally, an HVAC load control model is developed to enable real-time dynamic regulation of airflow, facilitating second-level load response and improved renewable energy accommodation. A symmetrical power tracking and voltage support secondary controller is also designed to accurately capture and manage the fluctuating power demands of HVAC systems for supporting operations of distribution power systems. The effectiveness of the proposed method is validated through power electronics simulations in the Matlab/Simulink/SimPowerSystems environment, demonstrating its practical applicability and superior performance.

Keywords: predictive power control; resident microgrids; HVAC systems; solar photovoltaic; energy storage (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
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