Coordinated flexibility scheduling for urban integrated heat and power systems by considering the temperature dynamics of heating network

The coordinated heat-electricity dispatch of the urban integrated energy system (UIES) helps to improve the system flexibility, thereby overcoming the adverse effects caused by the random fluctuations of renewable energy (RE) and promoting the penetration of RE. Among them, the dynamic characteristics of the urban heat network (UHN) are important features that need to be considered for the operating scheduling of the UIES. This paper aims to establish a flexibility scheduling model for UIES based on the dynamic characteristics of the UHN. First, the typical structure and key equipment model of the urban integrated heat and power system (UIHPS) with the dynamic characteristics of the UHN is proposed. Then, the definition and model of the UIHPS flexibility and the assessment index of the flexibility are developed. Moreover, a flexibility scheduling model for a UIHPS that considers the dynamic characteristics of a UHN is established. Finally, the validity of the proposed model is validated by case studies, and the applicability of flexibility scheduling and the effect of heat load (HL) are analyzed

Integration of Renewables in Power Systems by Multi-Energy System Interaction

This book focuses on the interaction between different energy vectors, that is, between electrical, thermal, gas, and transportation systems, with the purpose of optimizing the planning and operation of future energy systems. More and more renewable energy is integrated into the electrical system, and to optimize its usage and ensure that its full production can be hosted and utilized, the power system has to be controlled in a more flexible manner. In order not to overload the electrical distribution grids, the new large loads have to be controlled using demand response, perchance through a hierarchical control set-up where some controls are dependent on price signals from the spot and balancing markets. In addition, by performing local real-time control and coordination based on local voltage or system frequency measurements, the grid hosting limits are not violated

Optimal Scheduling of Combined Heat and Power Generation Units Using the Thermal Inertia of the Connected District Heating Grid as Energy Storage

A better integration across sectors is an essential element of 4th generation district heating and smart energy systems allowing to react to volatile renewable energy generation. This sector coupling enables to use more cost-efficient storage as storage prices differ for different forms of energy. Thermal energy for example can be stored in comparably cheap storage tanks. Besides such dedicated storage, the thermal inertia of a heating grid can be used as thermal storage as well. In this paper, a classic unit commitment optimization for scheduling of combined heat and power units not considering grid dynamics is extended to cover thermal dynamics of heating grids. First an outer approximation of the grid storage capabilities is developed. Second, a very efficient formulation for the storage dynamics of a heating grid is introduced and its capabilities are shown in a motivating case study. In this study additional savings of several thousand Euros per day are achieved using the thermal inertia of a heating grid as storage

Applicability of thermal energy storage in future district heating system - Design methodologies and performance evaluations

District heating (DH) enables efficient and economical utilization of energy resources to satisfy the heat and hot water demands in buildings and is, thereby, well-established in Northern European countries. To achieve the future renewable energy system, the current DH systems are proved to undergo transitions towards the future DH systems, with major characteristics including renewable-based heat sources, low temperature networks, lower heating demands and smart controls. An important step is the coordination of heating and electricity sectors to achieve synergies and optimal solutions for the overall energy system, which is also known as the smart energy systems. Such goal could be achieved in a cost-effective manner by the flexibilities added from short-term thermal energy storage (TES) technologies. Despite the importance of TES has been demonstrated in previous studies, giving drastic changes compared to the current systems, the practical applicability of TES in the future DH systems remains unknown. The proposed benefits of TES might deviate from expectation considering the future characteristics, such as the low storage temperature levels and short space-heating period. Furthermore, the current studies about the TES applications have mostly focused on specific case studies. The findings are of limited applicability because they cannot be easily generalized and extrapolated to other future conditions. To explore the practical challenges and optimal applications of short-term TES units in the future, a systematic design framework that considers the diverse factors from top-level targets to bottom-level implementations is developed in this study. The top-level theoretical analysis method is developed to identify the load shifting potentials and associated storage capacities for the whole energy system, by comparing and matching energy supply and demand profiles. Compared to current bottom-up detailed system models, the proposed method requires only the energy profiles, which has resulted in much shorter analysis time. The method is further validated by complex system models, and because a good agreement has been achieved, it can be applied in various scenarios to efficiently pre-study the storage potentials. Then, the design of the practical TES capacity is derived from the theoretical result by considering performance indicators during realistic operations, such as power-to-heat conversion efficiency and heat loss efficiency.On bottom-level implementations, four typical short-term TES technologies were investigated including central water tank (CWT), district heating network inertia (DHNI), domestic hot water tank (DHWT), and building thermal mass (BTM). For this purpose, an integrated bottom-level model to simulate the operation dynamics of the district heating systems and to optimize the use of the TES units is developed. Techno-economic analysis and comparisons of TES technologies were performed on a variety of scenarios, which are representatives of the main characteristics of the current middle-temperature district heating system and future low-temperature district heating system. The changes in the source side, transportation networks and end-use building demands are considered. As a result, a performance map of the TES technologies indicating the strong links between the system characteristics and optimal TES applications has been identified. Based on that, the optimal combinations of TES technologies were proposed for a LTDH system. Consequently, combining this with top-level methods, the overall potentials and roles of short-term TES were identified by a systematic design framework

Aggregate Model of District Heating Network for Integrated Energy Dispatch: A Physically Informed Data-Driven Approach

The district heating network (DHN) is essential in enhancing the operational flexibility of integrated energy systems (IES). Yet, it is hard to obtain an accurate and concise DHN model for the operation owing to complicated network features and imperfect measurement. Considering this, this paper proposes a physically informed data-driven aggregate model (AGM) for DHN, providing a concise description of the source-load relationship of DHN without exposing network details. First, we derive the analytical relationship between the state variables of the source and load nodes of DHN, offering a physical fundament for the AGM. Second, we propose a physics-informed estimator for AGM that is robust to low-quality measurement, in which the physical constraints associated with the parameter normalization and sparsity are embedded to improve the accuracy and robustness. Finally, we propose a physics-enhanced algorithm to solve the nonlinear estimator with non-closed constraints efficiently. Simulation results verify the effectiveness of the proposed method

On the Design of a Novel Solid Oxide Fuel Cell Combined Cooling, Heating and Power System for UK Residential Needs

Combined cooling, heating and power (CCHP) systems have become a topic of increasing research interest especially now that they may offer substantial improvements for conservation of fuel and electrical power in the domestic residential sector. However, only a few of the fuel cell (FC)-based CCHP systems have considered the inclusion of other power sources as part of their design with respect to diverse criteria for system optimisation. Most of the research undertaken thus far has focused on the performance improvement of CCHP systems when operated as a single energy source and has not considered the operation when connected to the electrical power distribution grid or under dynamic load conditions. The aim of this research project is to design a solid oxide fuel cell (SOFC)-based CCHP hybrid system that maximises system efficiency and minimises emissions and system costs in an objective manner with minimal operator and customer intervention. A new system structure has been designed to improve the flexibility of the system such that its functioning is closer to practical applications in both island and grid-connected modes, and still returns optimised performance with no need for system redesign or reconfiguration. A novel combination of grey relationship analysis (GRA) linked to an entropy weighting approach has been developed to evaluate the sizing values of fuel cells, heat exchangers and absorption chillers to improve the technical, economic and environmental system performance and reduce subjectivity and inaccuracy that could be imported through reliance on subjective human judgement. A new algorithm, denoted as the multi-objective particle swarm optimisation (MOPSO)-GRA has been designed to reduce local optimisation problem caused by standard MOPSO algorithms. The proposed system has been verified with published experimental results and comparative analysis has been carried out to verify the advance and the new algorithms. The main conclusion is that the optimum design of the SOFC-based CCHP hybrid system delivers optimised performance in terms of efficiency, operation and through life economy as well as environmental impact that gives a high degree of flexible compatibility within the energy supply environment in the UK

Optimal Scheduling of Combined Heat and Power Generation Considering Heating Grid Dynamics

As the share of renewable generation increases in electric grids, the traditionally heat driven operation of combined heat and power plants (CHPs) reaches its limits. Thermal storage is required for a flexible operation of CHPs. This work proposes three novel methods to use a heating grid as thermal storage by exploiting its thermal dynamics. These include the first approach proving global optimality, a novel linear formulation of grid dynamics and an easily real world applicable approach