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Decentralized coordination of the operation of residential heating units
Abstract
This work presents an approach to decentralized coordination of electro-thermal heating systems, like Combined Heat and Power systems (CHP), Heat Pumps (HP), or Electric Heating systems (EH), each equipped with thermal storage, within a group or cluster of residential buildings. The flexibility of these thermal systems can be exploited for coordinating the heating units for a higher-level objective, like balancing power fluctuations of Renewable Energy Sources (RES). In order to assess the decentralized coordination algorithm (DCA) presented in this paper, its performance is compared with that of a centralized approach. In the centralized approach, a Mixed Integer Program (MIP) is formulated and solved, obtaining the optimal schedules for each heating system within the building cluster. In the decentralized approach, an MIP is first executed for each heating system, providing a set of schedules, which all satisfy the local constraints as well as local objectives of the building. Next, one schedule per set is selected in a way that the combination of the selected schedules facilitates the higher-level objective. The results presented in this work show that the proposed DCA can in principle balance power fluctuations as global objective, while still enabling local optimization. However, the results appear to be strongly dependent on the flexibility of the local optimization.
... As a result, development and implementation of innovative, highly efficient, and environmentally friendly technologies in heat supply systems have become increasingly important. Contacted heat generators are among these emerging technologies utilizing contact energy exchange process technology [3]. ...
... A contact heat generator of a modular type CHGM, jointly patented by scientists from the Institute of Gas of the Academy of Sciences of Ukraine and Igor Sikorsky Kyiv Polytechnic Institute, was used to examine and compare the use of gaseous fuels, specifically hydrogen and natural gas ( Fig. 1) [3]. This study focused on how these fuels behave during contact energy exchange processes used for heat supply. ...
... A standard contact heat generator functions as a flow-type heat exchanger. In this system, the water is heated by direct contact with combustion products [1,3]. Due to the high efficiency of contact heat exchange in an apparatus with small dimensions, it is possible to provide high-quality cooling of combustion products and their low temperature at the outlet of the heat generator. ...
... As a result, development and implementation of innovative, highly efficient, and environmentally friendly technologies in heat supply systems have become increasingly important. Contacted heat generators are among these emerging technologies utilizing contact energy exchange process technology [3]. ...
... A contact heat generator of a modular type CHGM, jointly patented by scientists from the Institute of Gas of the Academy of Sciences of Ukraine and Igor Sikorsky Kyiv Polytechnic Institute, was used to examine and compare the use of gaseous fuels, specifically hydrogen and natural gas ( Fig. 1) [3]. This study focused on how these fuels behave during contact energy exchange processes used for heat supply. ...
... A standard contact heat generator functions as a flow-type heat exchanger. In this system, the water is heated by direct contact with combustion products [1,3]. Due to the high efficiency of contact heat exchange in an apparatus with small dimensions, it is possible to provide high-quality cooling of combustion products and their low temperature at the outlet of the heat generator. ...
This study examines the characteristics of hydrogen fuel combustion within a contact heat generator and its potential for enhancing energy efficiency and environmental sustainability in heat supply systems. This article explores critical aspects of achieving the United Nations Sustainable Development Goals 7 and 13 with a particular focus on affordable and clean energy access for all and actions on climate change. Using a mathematical model in the SOLID WORKS software environment, a simulation of thermal and aerodynamic processes in the combustion chamber of a heat generator was carried out. A comparative economic analysis based on the results of technical and economic calculations of hydrogen fuel, natural gas, and electric boilers for heating a residential cottage was conducted and showed an economically viable option. This in-depth analysis of hydrogen fuel combustion characteristics, coupled with advanced mathematical modeling and simulation tools, allows for a more accurate representation of real-world conditions, leading to more reliable and insightful results. Introduction As civilization advances, maintaining comfortable living conditions has become a necessity. Central to this comfort is the heat supply systems for buildings and structures. The transition from centralized to local and individual heat supply systems has become a focus of interest in both scientific and practical realms. A key focus of this shift involves the utilization of innovative, efficient, and eco-friendly technologies in heat supply systems, including contact heat generators which use contact energy exchange processes [1,2]. As a result, development and implementation of innovative, highly efficient, and environmentally friendly technologies in heat supply systems have become increasingly important. Contacted heat generators are among these emerging technologies utilizing contact energy exchange process technology [3]. This paper aims to explore the characteristics of hydrogen fuel combustion within a contact heat generator and its potential for enhancing energy efficiency and environmental sustainability in heat supply systems. The novelty of this research lies in the comprehensive investigation of hydrogen fuel combustion within contact heat generators, and its potential to significantly enhance energy efficiency and environmental sustainability in heat supply systems. While previous studies have explored the merits of local heat supply alternatives and contact energy exchange processes, there is limited research on the practical application of hydrogen fuel as a primary energy source in contact heat generators. A mathematical model using the SOLIDWORKS software framework was used to simulate the combustion chamber's thermal and aerodynamic processes. The use of hydrogen for heating has been a topic of extensive research and debate among scientists, policymakers, and industry stakeholders [4]. While hydrogen holds promise as a low-carbon energy source, its application in home heating has been met with mixed reviews. For example, the potential of transitioning from centralized energy systems to distributed energy sources in large cities has been explored in Poland. The study suggests that residential buildings with good solar conditions could be fitted with photovoltaic (PV) installations. These installations could power lighting, electrical appliances, and micro and small-scale heat pumps. The development of micro-scale PV systems could rapidly and efficiently translate centralized energy systems into
... Typical studies on the decentralized architecture for DSF management in a residential community are reviewed here. Molitor et al. [119] proposed a two-step decentralized coordination method for household heating systems in a residential district consisting of 66 apartments. In the first step, a series of optimal or near-optimal schedules were determined for each heat system in each apartment. ...
... -Linear programming (LP) [50]; -Mixed integer linear programming (MILP) [28,54,77,116,119,121]; ...
The management of demand-side flexibility plays a key role in reliable integration of intermittent renewable energy sources into residential microgrids. Residential microgrid is a dynamic and complex cyber-physical system, which consists of multiple cooperative, non-cooperative and even conflicting entities. Random and separate demand-side management of the multiple entities may have detrimental effects on the grid reliability like the peak “rebound” issue and on the economic benefits for both utilities and consumers. Harmonized coordination, not merely unorganized cooperation, among cooperative entities and negotiation among non-cooperative entities based on information sharing are therefore needed to achieve the neighborhood-level optimal solutions in a residential microgrid. This paper comprehensively reviews the state-of-the-art classification, technologies, architectures, and techniques for neighborhood-level coordination and negotiation in residential microgrids. Various types of coordination and negotiation behaviors are first categorized. The technologies, i.e., demand-side flexible resources involved in coordination and negotiation, are then summarized and introduced, including flexible loads, storage, and distributed generations. The typical architectures for coordination and negotiation are then classified into centralized, decentralized, hierarchical distributed, and non-hierarchical distributed architecture. Last, the major coordination and negotiation techniques, including multi-agent system, optimization and game theory, are reviewed and summarized. The challenges and opportunities for each technique are identified and critically discussed.
... Hence, this work presents a novel agent-based control 65 approach for a cluster of electro-thermal heating devices in place of DERs that considers both the local objectives of DERs and a general SLO. We expand the two-level concept presented in [12] by the feature to operate fully decentralized based on a MAS, without any central agent being 70 required. Each agent is equally eligible of scheduling one electro-thermal heating device in the cluster. ...
... The thermal energy generated 145 by the heating device covers the thermal demand of the BES and can be stored (red color in Fig 3). swtchOn t,n + swtchOff t,n subject to (4) to (12) for one specific n ∈ [1..N ] ...
The ongoing decentralization of the electrical power system encompasses the installation of residential electrical loads and generators, such as electro-thermal heating devices. Clusters of these devices in combination with thermal storage can play a significant role in future power system control as they introduce load and generation flexibility into the system. Hence, control concepts which are attractive for both power system level and end user side are required. This work proposes a novel decentralized scheduling approach for electro-thermal heating devices based on a multi-agent system architecture. As a major novelty, the approach addresses both of the aforementioned appeals on two levels without central control. First, local planning with individual objectives is performed. Second, the heating devices cooperate to find the combination of local plans serving best a given energy system objective. This approach is fully decentralized and has a strong end user involvement. The performance of the proposed approach related to end user and system level objectives is compared to that of centralized approaches. Simulation results show that the new method can successfully satisfy end user objectives and provide energy fluctuation balancing. Finally, drawbacks compared to centralized scheduling are analyzed.
... Hence, apparent temperature is considered to incorporate the combined effect of relative humidity, wind and air temperature. The apparent temperature is calculated using (57) and (58) [73]. The correlation coefficient of thermal demand with respect to external ambient temperature and apparent temperature, is -0.88 and -0.89 respectively. ...
... Some scholars have also studied the thermal inertia of thermal system in the optimal operation of the electro-heat IES. Ref 18 studies the electric-heat joint scheduling strategy of the distributed and coordinated control of the thermoelectric unit, the electric heating device and the energy storage device. Ref 19 proposed a multi-time scale energy coordination optimization method considering the variability of response speed in the energy flow change of the heating system. ...
With the development of multi‐energy technology, the electric‐heat integrated energy system has become an important research direction for multi‐energy joint supply. The dynamic characteristics and energy storage capacity of heat supply network provide potential for joint dispatching of electric heating energy system. Aiming at the problem of electric‐heat joint dispatching, this paper presents an operation optimization model of electric‐heat integrated energy system considering the virtual energy storage characteristics of heat supply network. Firstly, according to the characteristics of transmission delay and user temperature fuzzy, the virtual energy storage characteristics of heat supply network are studied, and a model of the dynamic transfer of energy in the heat system was built. Then, the operation optimization model of the electric‐heat integrated energy system is established to minimize the operation cost. In order to improve the robustness of scheduling optimization results, the Monte Carlo Simulation embedded Quantum Particle Swarm Optimization algorithm is proposed to solve the model. In order to prove the validity of the proposed model, this paper selects a park (a 36 node thermal system) in the northwest region of China as a simulation case. The results show that the operation optimization method considering the virtual energy storage of heat supply network will greatly enhance the complementary potential of the electric‐heat integrated energy system and reduce the operation cost of the system.
... Some scholars have also studied the thermal inertia of thermal system in the optimal operation of the electro-heat IES. Ref [15] studies the electric heat joint scheduling strategy of the distributed and coordinated control of the thermoelectric unit, the electric heating device and the energy storage device. Ref [16] proposed a multi-time scale energy coordination optimization method considering the variability of response speed in the energy flow change of the heating system. ...
Background
With the rapid development of multi-energy technology and the wide application of electric-heat integrated energy system (IES), multi-energy network optimization has become an important research direction of multi-energy joint supply in recent years.Compared with electric energy, heat energy has the characteristics of delay in transmission time and fuzzy body temperature, which makes the heating system more flexible to participate in IES.
Methods
An operation optimization model for the electric-heat IES that takes into account the heat storage characteristics of the heating network is proposed to address the operation cost of the electric-heat IES. Firstly, the virtual energy storage characteristics of the heating network are proposed based on the characteristics of the transmission time delay of the heat system and the somatic blurring of user temperature. Then, the model of the dynamic transfer of energy in the heat system was built. Based on this, an operation optimization model of the electric-heat IES is established. And the Monte Carlo Simulation embedded Quantum Particle Swarm Optimization (MCS-QPSO) algorithm is proposed to solve the model.
Results
This paper takes a park in Northwest China as a simulation case to prove the effectiveness of the model. The analysis of the case shows that the model can optimize the output of energy supply equipment, so that the output equipment can maintain high efficiency. The mode changes the energy purchase strategy according to the price change of different energy. The results show that the proposed model can effectively utilize the virtual energy storage characteristics of the heating network to achieve energy transfer across time, thus reducing the operation cost of the IES.
Conclusions
In this paper, the operation optimization model of the electric heating IES is established based on the incubation period of the heating network and the virtual energy storage characteristics. The model can not only achieve the coordination and complementarity between the electric and thermal systems in time and space, but also improve the energy efficiency and reduce operation cost of the system.
... In [9], the heat storage characteristics of the heating pipeline are coordinated with the operation of the power systems, and the thermal-electric decoupling is performed to realize flexible heating for improving the consumption rate of WT. In [10], a coordinated dispatch strategy of the combined heat and power (CHP) unit, electric heating device, and electric energy storage device is presented, and the simulation results show that the thermal systems with large inertia time constant could effectively suppress the volatility of renewable energy and reduce its impacts on the power system. In [11], a calculation method for the energy storage capacity of the heating network is proposed, and the thermal inertia of the heating network is utilized to replace the energy storage for saving financial costs and coping with the uncertainty of renewable energy. ...
A large amount of wind turbine power and photovoltaic power is abandoned in many areas with abundant renewable energy due to thermal-electric coupling, inadequate local consumption capacity, and limited capacity of transmission lines, etc. To solve the above problems, a coordinated dispatching method for integrated energy systems is proposed in this paper. Firstly, the spatiotemporal characteristics of diversified loads in multiple functional areas are introduced, including the inertia and elasticity of heating/cooling loads, the spatiotemporal distribution of electric vehicles, and the optimum transmission distance of diversified loads, etc. Secondly, a coordinated dispatching model of integrated energy systems is proposed, which considers the differences of multiple functional areas and various forms of energy systems. Finally, an actual distribution system in Jianshan District, Haining, Zhejiang Province of China is investigated for demonstrating the effectiveness of the proposed model. The results illustrate that the proposed model could effectively improve the consumption rate of renewable energy and reduce the volatility of renewable energy by considering the coordination of electric vehicles, tie lines, and heating/cooling systems in multiple functional areas.
... Mixed integer programming based on the daily scheduling of individual heating systems, based on power fluctuation, are derived from their set of optimal schedules using the coordinated algorithm in [14]. This requires frequent and proper communication channel between heating systems. ...
This paper aims to unleash the potential of a heat pump (HP) and its storage system, as a flexible consumer load, in the low-voltage (LV) distribution network by introducing an autonomous controller. Steady-state analysis using DigSILENT Power Factory, a power system analysis tool, is performed to verify the proposed hypothesis. The proposed controller manages to operate the individual HP and storage within the recommended operating limits of grid voltage, by sharing flexibility within the specific network. It has the capability of sensing local key control parameters for scheduling, re-scheduling, and decision-making on the operation of individual HPs. It also takes the thermal energy comfort of individual consumers into consideration. Measurement of local parameters such as grid voltage, supply temperature and level of cold water in the storage tank defines the priority for operation of HPs based on operating delays for turning it on and off. This enhances the sharing of flexibility for proper coordination, control, and management of HP systems in LV distribution networks with mutual technical benefits. From the results, the application of the proposed controller is found to be effective to manage grid congestions and local voltage regulation, satisfying the thermal energy requirements of the customer.
... Both strategies lack an optimal scheduling, that is based on a load forecast. In comparison to optimal approaches, as in Molitor et al. (2013) and Harb et al. (2015), the degree of coordination has to be further improved. This will be done by introducing an optimized scheduling procedure to the environment in upcoming developments. ...
... The scheduling of a cluster of houses that comprises both CHPs and HPs induces a further challenge for a decentralized coordination concept as the in- 1 Non-deterministic polynomial-time hard teractions of these units result in oscillations of the solution. In [5], the authors propose a two-stage decentralized scheduling approach. Every building generates a set of feasible schedules that satisfy the local constraints which are then combined by a central coordinator to compute an optimal scheduling for the entire cluster. ...
This paper introduces a decentralized scheduling scheme for electro-thermal heating systems i.e. heat pumps and combined heat and power units. The scheduling is modeled as a mixed integer linear optimization program (MILP) and reformulated based on the Dantzig-Wolfe decomposition method. The decomposed problem is solved by means of an iterative column generation algorithm that is modified to solve MILPs. The aim is thereby to enhance the integration of renewable energy sources by matching demand and supply. The architecture is based on a cooperative multi-agent system. A centralized scheduling approach is used as a reference to assess the performance of the decentralized concept. The analysis comprises a cluster of existing residential buildings. The results show that the centralized scheduling delivers the best coordination with a limited extendability. The decentralized scheduling presents a slightly lower coordination with a great potential for scalability. Moreover, the decentralized scheduling is based on an emphasized local intelligence which allows for reducing the communication of sensible data.
... Militor et. al. [15] suggest solving mixed integer problems at DER before solving a mixed integer problem at aggregation level. These approaches however, all assume convex problems at the DER and the VPP. ...
Distributed energy resources (DER) offer an economically attractive alternative to traditional centralized generation. However, the unpredictable and scattered nature of DER prevents them from replac-ing traditional centralized generator capacity. Aggregating DER under a virtual power plant (VPP) addresses this issue by exposing the combined capabilities of connected DER as a single controllable entity towards the utility. In this paper we propose an architecture that supports multi-level aggregation of DER under VPPs. In this architecture, DER submit energy profiles to a VPP. The VPP may then control the DER within the boundaries defined in the energy profiles. The proposed architec-ture is hosted in an agent-based framework, Controleum, and is to be demonstrated at a primary school in Denmark, first quarter 2014.
... Within the day-ahead scheduling, the building agents communicate with an aggregator agent, negotiate and agree upon a schedule for the next day. The negotiation process is based on forecasts for generation of renewable energy and expected residents' behavior [4]. ...
This paper provides an analysis of high-resolution, fine-granularity data from the load profiles of thirty residential buildings in Upper Austria with regard to deviations from the expected profile. The standard load profile is taken as a reference curve and compared with the standard deviation of the actual data. The deviations are categorized according to the frequency of occurrence, magnitude and duration. Furthermore, dispatchable energy resources are assigned to each category, in order to link the study to the practical aspects of Smart Grids research. By means of the study results, requirements for the design of short-term control are defined.
This paper describes a distributed optimization algorithm for scheduling the operation of electro-thermal heating units, such as heat pumps (HP) or electric heaters (EH) within a day-ahead (DA) operation for covering space heating demand. Flexibility for Demand Side Management (DSM) is realized through thermal storage on building level. The distributed optimization is performed offline by using the Alternating Direction Method of Multipliers algorithm (ADMM). For the distributed optimization also a suitable architecture is adapted and described. The optimization algorithm is tested within an example city district scenario and evaluated according to defined metrics.
This paper describes a modeling and optimization of operation for small compressed-air energy systems (CAES) in the range of kW, typical of small and medium enterprises (SME) and energy intensive industry. These CAES are equipped with air storage. This paper analyzes how those systems may provide flexibility for electrical Demand Response (DR) in city districts. The paper presents first, the modeling of a CAES system. The system design, such as compressor and storage size is then performed based on the modeling results. The mixed-integer linear optimization model for using CAES is explained afterwards. The optimization is an offline day-ahead optimization for planning operation purposes. The approach is analyzed in terms of flexibility within a test case for optimizing the CAES of a typical German car repair shop.
Residential Demand Response (DR) is believed to be a feasible tool for increasing the power system operational flexibility and efficiency. In this paper, we develop a demand response methodology for residential peak load shaving. We present an optimal demand response model for scheduling the EV and storage space heating load in tandem. Realistic case studies based on Finnish household data is performed to showcase the effectiveness of the proposed methodology and the results are thoroughly compared with business as usual case. The simulation result suggests that proposed methodology can bring economic savings to the customers and reduce the peak power problem as well.
The increasing installation of volatile renewable energy sources like photovoltaics and wind enforces the need for flexibility options to match the renewable generation with the demand. One of these options is Demand Side Management (DSM) in the context of building energy systems combined with thermal storage systems. This paper discusses such concepts for DSM. A method for analyzing the flexibility that is needed to maintain the stability of the electrical grid is presented followed by the restrictions that are caused by meeting the heat demand and satisfying the comfort criteria of the residents. Approaches for simultaneously fulfilling these constraints as well as matching the flexibility needs of the electrical grid and the flexibility provided by the local building energy systems are discussed. To enhance the analysis options for the shown systems, a simulation platform that covers the electrical grid simulation, the building systems’ simulation and the control strategies is presented. This platform can be used to analyze different scenarios of building energy systems with different penetrations of renewable energy sources and different building types.
Microgrid is taken as the future Smart Grid, and can work as a local energy provider to domestic buildings and reduce energy expenses. To further lower the cost, a Smart Homes idea is suggested. Smart Homes of the future will include automation systems and could provide lower energy consumption costs and comfortable and secure living environment to end users. If the energy consumption tasks across multiple homes can be scheduled based on the users' requirement, the energy cost and peak demand could be reduced. In this paper the optimal scheduling of smart homes' energy consumption is presented using mixed-integer linear programming. In order to minimize a one-day forecasted energy consumption cost, operation and electricity consumption tasks are scheduled based on different electricity tariffs, electricity task time window and forecasted renewable energy output. A case study of thirty homes with their own microgrid indicates the possibility of cost saving and asset utilization increase.
Managing demand for electrical energy allows generation facilities to be run more efficiently. Current systems allow for management between large industrial consumers. There is, however, an increasing trend to decentralize energy resource management and push it to the level of individual households, or even appliances. In this work we investigate the suitability of using adaptive clustering to improve the scalability of decentralized energy resource management systems by appropriately partitioning resources. We review the area of distributed energy resource management and propose a simple yet realistic model to study the problem. Simulations using this model show that straightforward clustering and distributed planning methods allow systems to scale, but may be limited to only a few hundred- thousand appliances. Results indicate that there is an opportunity to apply adaptive clustering techniques in order to discover more advanced grouping criteria that would enable groups to change as appliances' behavior changes. The simulations further suggest that even an extremely limited exchange of information between clusters can greatly improve management solutions.
This paper introduces and discusses a methodology to model and assess the impact of distributed electro-thermal technologies such as Distributed Combined Heat and Power (DCHP) and Electric Heat Pump (EHP) on LV distribution networks. Modelling of load and generation for both electricity and heat is carried out as the starting point of the analysis. In this way, it is possible to capture the relevant interactions between the two energy vectors. A fractal algorithm is then used to generate generic large-scale networks with different topologies and characteristics that can resemble real networks. Different metrics are used to quantify the impact of the considered technologies, with emphasis on thermal and voltage limits. Case studies carried out for typical urban and rural areas in the UK and for different scenarios exemplify the developed methodology and illustrate the main drivers for impact and trends in the different cases.
This paper presents the concept of Dual Demand Side Management (2DSM) as an evolution of the conventional Demand Side Management concept. 2DSM accounts at the same time on one hand for the local needs, i.e. energy efficiency of the building stock as well as optimization of the local distribution grid and on the other hand for the challenges of the higher level electrical grid arising from the integration of renewable and alternative energy sources. The proposed concept shows the possibilities originating from the interaction of local district heating, heat storage and micro grid technology. Finally the paper shows the development and testing processes required for designing complex multi-domain systems.
An analysis of seven different technologies is presented. The technologies integrate fluctuating renewable energy sources (RES) such as wind power production into the electricity supply, and the Danish energy system is used as a case. Comprehensive hour-by-hour energy system analyses are conducted of a complete system meeting electricity, heat and transport demands, and including RES, power plants, and combined heat and power production (CHP) for district heating and transport technologies. In conclusion, the most fuel-efficient and least-cost technologies are identified through energy system and feasibility analyses. Large-scale heat pumps prove to be especially promising as they efficiently reduce the production of excess electricity. Flexible electricity demand and electric boilers are low-cost solutions, but their improvement of fuel efficiency is rather limited. Battery electric vehicles constitute the most promising transport integration technology compared with hydrogen fuel cell vehicles (HFCVs). The costs of integrating RES with electrolysers for HFCVs, CHP and micro fuel cell CHP are reduced significantly with more than 50% of RES.
Introduction Characteristics of a Constrained Problem Random Search Methods Complex Method Sequential Linear Programming Basic Approach in the Methods of Feasible Directions Zoutendijk's Method of Feasible Directions Rosen's Gradient Projection Method Generalized Reduced Gradient Method Sequential Quadratic Programming Transformation Techniques Basic Approach of the Penalty Function Method Interior Penalty Function Method Convex Programming Problem Exterior Penalty Function Method Extrapolation Techniques in the Interior Penalty Function Method Extended Interior Penalty Function Methods Penalty Function Method for Problems with Mixed Equality and Inequality Constraints Penalty Function Method for Parametric Constraints Augmented Lagrange Multiplier Method Checking the Convergence of Constrained Optimization Problems Test Problems MATLAB Solution of Constrained Optimization Problems References and Bibliography Review Questions Problems
Household Energy Consumption by End-use in the EU-27
- European Environment