Model Predictive Control Design for Unlocking the Energy Flexibility of Heat Pump and Thermal Energy Storage Systems
원문 초록
Heat pump and thermal energy storage (HPTES) systems, which are widely utilized in modern buildings for providing domestic hot water, contribute to a large share of household electricity consumption. With the increasing integration of renewable energy sources (RES) into modern power grids, demand-side management (DSM) becomes crucial for balancing power generation and consumption by adjusting end users' power consumption. This paper explores an energy flexible Model Predictive Control (MPC) design for a class of HPTES systems to facilitate demand-side management. The proposed DSM strategy comprises two key components: i) flexibility assessment, and ii) flexibility exploitation. Firstly, for flexibility assessment, a tailored MPC formulation, supplemented by a set of auxiliary linear constraints, is developed to quantitatively assess the flexibility potential inherent in HPTES systems. Subsequently, in flexibility exploitation, the energy flexibility is effectively harnessed in response to feasible demand response (DR) requests, which can be formulated as a standard mixed-integer MPC problem. Numerical experiments, based on a real-world HPTES installation, are conducted to demonstrate the efficacy of the proposed design.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
Coordinated Control of Autonomous Vehicles for Traffic Density Reduction at a Signalized Junction: An MPC Approach
Model Predictive Control-Based Optimal Energy Management of Autonomous Electric Vehicles Under Cold Temperatures
HMPC-assisted Adversarial Inverse Reinforcement Learning for Smart Home Energy Management
Algorithmic Control Improves Residential Building Energy and EV Management when PV Capacity is High but Battery Capacity is Low
skfolio: Portfolio Optimization in Python
100-Day Analysis of USD/IDR Exchange Rate Dynamics Around the 2025 U.S. Presidential Inauguration
토론
이 논문과 연결된 포럼 글이 아직 없습니다.