Combined heat and power scheduling: Utilizing building‐level thermal inertia for short‐term thermal energy storage in district heat system

Abstract

A major limitation to integrating wind power in electric power system (EPS) is the massive generation capacity of the highpenetration inflexible combined heat and power (CHP) units in district heating system (DHS). A heat and power optimal dispatch is established in this study to exploit building-level thermal inertia as a form of short-term thermal energy storage (TES) to unlock the flexibility of CHP units. This proposed short-term building TES can provide storage potential by utilizing small variations in indoor temperature under the proposed dispatch control model to control the storage capacity in the dispatch process. A linear optimization operational model is run to integrate energy systems by balancing heat and power demands over multiple time periods with CHP units, wind power, short-term building TES, and district-level heating network (DHN) storage capacity. A two-stage decomposition-coordination iteration algorithm is proposed to solve this optimization program. The simulation results are analyzed to determine the potential benefits of this short-term TES in terms of economics, wind power integration, and the flexibility of CHP units. . His research fields are power quality, power system operation and control, power system relaying, distributed generation and renewable energy, and power system stability.

Generalized Additive Modeling of Building Inertia Thermal Energy Storage for Integration Into Smart Grid Control

“…Only few works have considered the integration into more sophisticated predictive optimization-based control schemes, providing MILP models for the building's SoE [3], [6], [19]. Zhang and Luo [19] propose a full formulation for utilizing BITES in an integrated energy system with combined heat and power plants (CHP) and show in simulation studies how the provided flexibility can decrease curtailment of wind power plants.…”

District Heating Challenges for the UK

“…By the 1990s, published works had a far greater technical focus, including one of the first linear optimizations of DH [38], which considered the costs of electricity and heating at different times across the year and suggested an operating schedule to minimize the operating costs. This method is still used today and features in many recent publications [39][40][41]; however, it is almost exclusively focused on a cost optimization and has little consideration for operational constraints or targets, such as carbon emissions. By the 1990s, carbon emissions were being acknowledged as a significant concern, and yet even now, CHP operating strategies rarely target carbon footprint minimization, so continued use of this methodology demonstrates a persistent disconnect between political and environmental motivations and technical advancements.…”

Edge Intelligent Perception Method for Power Grid Icing Condition Based on Multi-Scale Feature Fusion Target Detection and Model Quantization

“…However, the cloud computing model can not guarantee the reliable transmission, real-time analysis and recognition of insulator icing monitoring image in bad weather. But with the development of power Internet of things and the transformation of energy digitization (Shen et al, 2017;Haoyong et al, 2019), millions of power edge intelligent devices such as power sensors, state sensors and intelligent video monitoring system are connected to the power Internet of things, resulting in massive heterogeneous data (Zhang and Luo, 2018;Shen et al, 2020b;Nie et al, 2020;Ying et al, 2020). The traditional centralized data processing mode centered on cloud computing shows the problem of insufficient real-time, especially for the ice monitoring system with poor transmission conditions, the edge intelligent technology with edge computing as the core has been widely concerned.…”