Search

Lowering the exergy content of heat required for heating purposes decreases the primary energy consumption. District heating systems are often an important link between facilities that generate heat with low exergy content and consumers. Exergetic efficiency of heat distribution is an important performance criterion in heat supply to consumers. It can serve as a criterion for optimization, towards a more sustainable distribution-network design and operation. This paper presents a methodology for an exergy-based distribution-network analysis in a district heating system. Criteria for performance evaluations are defined. They can be used to evaluate heat supply to different points in the network, or individual system components. A case study is performed on an existing district heating system. Energetic and exergetic efficiencies of supply lines are analyzed. Exergy destructions and exergy losses are studied. Large differences in efficiency of heat supply to different points in the network are discovered. Over-dimensioned parameters of the distribution network are investigated.

Effective fault detection and isolation can improve the safety, reliability and efficiency of the district heating system. In order to detect and locate the sensor, actuator and component faults in the district heating system with faster response speed and higher accuracy, a two-level fault detection and isolation scheme, consisting of upper-level classifier for system faults and lower-level classifier for sub-faults, is developed based on convolutional neural networks. In consideration of the difficulty of obtaining the operation data of a real district heating system under various faulty states, a test benchmark model of an integrated energy based district heating system is built from the system level, which contains the renewable energy based water boilers, transmission networks, and heat load substations to examine the effectiveness of the proposed scheme. To improve the model reality, the dynamics of sensors and actuators, models of heat exchangers, and thermal inertia are considered in the district heating system, and Gaussian noises are added in the raw data signals. Nine kinds of system faults including sensor, actuator, component faults, along with three sub-fault types of bias, drift, complete failure, are investigated in the benchmark system. The performance of the proposed two-level fault detection and isolation scheme is evaluated under different data windows and Gaussian noises in the district heating system, and is compared with other data-driven methods including k-nearest neighbor, random forest and back propagation neural networks. Experimental results show that the two-level fault detection and isolation scheme can detect the faults in the district heating system accurately and robustly, and the proposed scheme has the potential to become an effective solution to real-time monitoring of faults in the district heating system.

Utilization of the renewable resources in district heating systems can reduce the use of fossil fuels, operating costs and protect the environment. In this study, an integrated hybrid system consisting of concentrating photovoltaic/thermal collectors (PV/T), geothermal (GSHP) and absorption (AHP) heat pumps is considered for district heating. The thermodynamic performance of the system at various conditions is explored through detailed simulations. A modified thermo-ecological cost (TEC) method is used to optimize the structure of the PV/T by considering contributions of different flows. The results show that a higher solar irradiance level and a higher PV coverage ratio have a positive impact on the thermal performance of the hybrid system. The TEC-based optimization shows that a 66% PV coverage ratio of PV/T yields a minimum thermo-ecological heating cost of 6.86 J/J, which is slightly lower than cost with a conventional method. Based on the sensitivity analysis, other key parameters except the operating time and the PV coverage ratio have a negative influence on the economic performance of the district heating system, because of the increasing cumulative exergy consumption of the GSHP or PV/T.

As part of the energy structure transition, a key focus in district heating systems is the load distribution optimization of multiple heat sources under the specific heating network. A multi-objective optimization approach is discussed in this paper with a goal of achieving complementary advantages among heat sources, and improving the performance of the system in terms of economic cost, energy structure, and environmental benefits. This paper firstly establishes the mechanism model for multi-source district heating systems (MSDHS). Secondly, it proposes a multi-objective optimization system to account for the operation economy, energy structure, and environmental impact for MSDHS. The selected objectives are such selected that they could be justified and used in real sites. The weights of the objective functions are obtained via the fuzzy analytic hierarchy process (FAHP). Finally, this paper solves the optimization problem via particle swarm optimization (PSO) to obtain the optimal load distribution and tests its validity in a real heating system covering an area of 15 million m2. The optimized load distribution scheme achieves a coal saving of 1.14%, a natural gas saving of 0.53%, and a cost-saving of $3,270 during a 24-hour pilot operation. This study provides the basis for future optimization enhancement and algorithm development.

Solar district heating systems have shown significant promise to facilitate the large scale adoption of solar energy technologies and thus substantially reduce greenhouse gas emissions. Given the mismatch between solar energy and district heating demand, energy storage devices play a critical role given their capacity to stockpile solar energy in both the short-term (hours to days) and long-term (months). However, the integration, sizing and control of energy storage technologies is far from simple. This paper investigates sizing and controlling thermal energy storage from the perspective of its performance within a district heating system, highlighting the close link between design and control. A 52-house Canadian solar district heating system, the Drake Landing Solar Community (DLSC), was used as a case study. This system uses solar collectors as main energy supply, borehole thermal energy storage (BTES) for seasonal storage and two 120-m3 water tanks for short-term thermal storage (STTS). The effect of (a) storage sizing (STTS volume) and (b) storage control (rate at which energy is either injected or extracted from the BTES) was evaluated. A control-oriented model, calibrated and validated with operational data at 10-min intervals, was used along with an optimal rule-based control to gauge system primary energy use. Different scenarios were tested, with STTS volumes ranging from 120 m3 to 480 m3, and BTES loop nominal flow rates between 2.5 and 4.5 L/s. An optimization routine was developed to calculate the optimum parameters of the rule-based control strategy. Results show that, in comparison with the design and control in place, primary energy savings of 13%–30% (with BTES flow rates of 2.5–4.5 L/s) could have been obtained with the proposed rule-based control strategy. By decreasing the STTS volume to 120-m3, energy savings up to 6% could still be achieved; savings could reach 27%–36% by increasing the STTS size to 360-m3.

When South Korea develops a new city, the government has made a preliminary decision on one of two heating systems, an individual heating system (IHS) or a district heating system (DHS). However, it is still unclear which system is desirable in terms of maximizing the national economic effect. Thus, this article aims to derive quantitative information about the economic effects of the same amount of production or investment in the two systems through an input-output (IO) analysis using the recently published 2017 IO table. More specifically, the production-inducing effects, value-added creation effects, and wage-inducing effects are systematically analyzed focusing on the IHS and DHS sectors. The results show that one dollar of production or investment in IHS or DHS causes about 1.073 and 1.388 dollars of production, about 0.228 and 0.658 dollars of value-added, and about 0.051 and 0.108 dollars in wages, respectively, throughout the national economy. Overall, the economic effects of the DHS sector are greater than those of the IHS sector. That is, when the same amount of investment or production is made in the two sectors, DHS produces more economic effects than IHS.

In the article author tries to scrutinize the problem regarding demand side management in district heating system. The aim of the article is to depict the ICT and IoT tools supporting demand side management in district heating. In the first part of the article the essence of demand side management was presented in particular in energy industry. After that the functionality and architecture of IT system supporting demand side management in district heating system were shown. In the last part of the article there were presented the benefits coming from implementation of such IT system in practice

We study the role of solar heat in decarbonization of a Nordic district heating (DH) network, where most of the annual heat demand is satisfied with bioenergy. We use actual data from a Finnish municipality to create a dynamic model of the heating system with Apros® simulation software. With the help of modelling, we examine various decarbonization scenarios for the existing heating system, using different combinations solar thermal collectors, thermal energy storage (TES) and limitations on how and when solar heat can access the system. According to results, zero emissions during the summer can be achieved with annual solar share of 13.2% and at 44 €/MWh levelized cost of heat (LCoH), if the integration is supported by TES and a careful planning of solar heat integration. Our results show that a simple approach of pursuing for a maximal solar share does not necessarily lead to a reduction in carbon emission or in LCoH. In fact, aiming at higher solar shares of 15–25% in our case system, actually increase greenhouse gas emissions compared to the base case. This highlights the importance of focusing on emissions reductions instead of simple addition of renewable energy when DH utilities plan for solar heat investments.

Modelling of a complex district heating system by increasing the energy system efficiency and by reducing emissions through the implementation of new and low carbon technologies is presented. One of these technologies is cogeneration which is used to increase energy efficiency and to reduce CO2 emissions. Presented model uses linear programming as a basis for mathematical modelling of the energy system. The mathematical calculation is set pragmatically, so it can be efficiently and reliably used to assess the impact of most important parameters on the efficiency of the regional energy system. The model analyzes the effects of integration of cogeneration into the existing energy system using a given goal function. The basic criterion is set to be the reduction of environmental impact. The model is successfully tested on the complex district heating system with the power of about 600 MW.

Domestic hot water and space heating demand in buildings contribute a high share of final energy demand. This demand is often met by fossil fuels, leading to large greenhouse gas emissions. Although renewable energy can be used for heating, there is time discordance between heat supply and heat demand. Seasonal thermal energy storage is a viable solution to overcome this mismatch. This paper presents a simulation method and a simple tool to assess the feasibility of integrating a seasonal thermal energy storage equipped with heat exchangers and/or heat pumps in a district heating system. The developed method and tool are generic and allow the simulation of hourly energy flows using energy balances and predefined conditions. In order to validate the proposed method, the result of the simulated energy flows from two selected systems, Friedrichshafen and Marstal, are compared with monitored values reported in literature. The comparison shows that while simulation of monthly energy flows depends on the accuracy of inputs to the tool, annual energy flows can be closely replicated. Hence, the method can be considered as validated. This simulation tool and method can be used to assess energy flows in a district heating system in future.

The increase of insulation thickness (IT) results in the decrease of the heat demand and heat medium temperature. A mathematical model on the optimum environmental insulation thickness (OEIT) for minimizing the annual total environmental impact was established based on the amount of energy and energy grade reduction. Besides, a case study was conducted based on a residential community with a combined heat and power (CHP)-based district heating system (DHS) in Tianjin, China. Moreover, the effect of IT on heat demand, heat medium temperature, exhaust heat, extracted heat, coal consumption, carbon dioxide (CO2) emissions and sulfur dioxide (SO2) emissions as well as the effect of three types of insulation materials (i.e., expanded polystyrene, rock wool and glass wool) on the OEIT and minimum annual total environmental impact were studied. The results reveal that the optimization model can be used to determine the OEIT. When the OEIT of expanded polystyrene, rock wool and glass wool is used, the annual total environmental impact can be reduced by 84.563%, 83.211%, and 86.104%, respectively. It can be found that glass wool is more beneficial to the environment compared with expanded polystyrene and rock wool.

Solar district heating systems are a promising solution to facilitate the adoption of large-scale, solar energy-based technologies. Thermal energy storage devices could also play an instrumental role to manage the mismatch between solar energy resources and community heating loads; however, controlling such systems is no easy task. In this paper, a novel heuristic reactive control strategy is developed to properly manage the thermal energy storage capacity, at both the short-term and the long-term, in a Canadian solar district heating system (the Drake Landing Solar Community). This strategy targets the optimization of: (a) the temperature difference across solar collectors and (b) the flow rate modulation of the variable speed pump linking the short-term and the seasonal thermal energy storage devices. A simulation is used to compare this new control approach with the conventional control strategy currently in place. Results are assessed for the year 2017–18 in terms of energy, cost and greenhouse gas emissions. Despite a 10% increase in natural gas consumption, electricity use was decreased by 43%; reductions of 34% and 29% were respectively achieved in terms of energy cost and GHG emissions.

The energy, economic and environmental analysis of a solar heating system with seasonal heat storage integrated into a district heating system based on natural gas boiler was performed. The solar collector field has a surface area of 8720 m2 and the pit seasonal heat storage has a volume of 10000 m3. This system covers 79% of the total yearly heat demand of the 15 multifamily buildings with 1500 inhabitants. The total system investment cost (2974100 €) may be recovered in about 17 years. The environmental impact of solar heating system integration is the decrease of CO2 emission by 79%.

Integration of shallow geothermal energy could effectively contribute to long-term improvement in the energy supply systems by slowing down the growth of energy consumption, changing the structure of used energy sources, and by modernizing communal energy infrastructure. Such integration is one way of addressing sustainability goals, ensuring better energy security and economic competitiveness, and making a contribution to environmental protection efforts. This paper examines the integration of local geothermal potential in the northern part of the Republic of Serbia and assesses the implications of using geothermal heat pump technology in a district heating system. This analysis considers different aspects of the proposed application and evaluates the environmental sustainability and viability of utilization of geothermal heat pumps for district heating. Energy, economic and environmental performance was assessed for infrastructure that supplies 1274 properties in collective residential building segment located in a densely populated city area. The assessment quantified performance in key energy, economic and environmental categories, focusing on the use stage of the system's life cycle. The main benefit of the geothermal heat pump system is the reduction of the inlet primary energy by at least 30% by avoiding the use of almost a million cubic meters of natural gas per year. This also results in a competitive energy cost of 17 EUR/MWh, an investment with internal rate of return of up to 38%, and a discounted payback period of 4.9 years. The geothermal heat pump system can bring energy and economic benefits but unfavorable environmental impacts, mainly due to the unfavorable electricity generation mix in the Republic of Serbia. The existing natural gas driven system was found to have lower impacts across all indicators but terrestrial eco-toxicity, natural land transformation and fossil depletion. In the climate change impact category, the existing system's impacts are 82% lower than those of the geothermal system.

openaire: EC/H2020/856602/EU//FINEST TWINS Espoo has set a goal to abandon the use of coal in its district heating system by the year 2025. The local district heating operator is producing a major share of Espoo's heat demand with combined heat and power units, but a large share of that thermal capacity will be closed by 2025. The plan is to replace the closed down capacity with renewable fuels, heat pumps and waste heat utilisation. The goal of this paper is to simulate the impacts of these emission reductive acts on the production costs and CO2 emissions of the system. The possibility of utilising waste heat from data centres in the district heating system is evaluated. The results show that abandoning coal in the city's heating system leads to a significant reduction of CO2 emissions with a small increase of annual production costs. Waste heat enables emission reductions even further, and the increase of production costs can be prevented.

To decrease irreversible loss and reduce natural gas consumption of conventional district heating systems based on natural gas fired boilers, new configurations of the district heating system based on natural gas and deep geothermal energy are proposed and analyzed from the perspective of thermodynamics and financial benefit. The results show that the proposed district heating system based on natural gas and deep geothermal energy with absorption heat exchangers and a gas-fired absorption heat pump (DH-AHE-DAHP) not only has higher thermodynamic performance, but also enables us to gain better financial benefit, and its configuration is optimal. Compared with conventional district heating systems based on natural gas, the DH-AHE-DAHP could increase product exergy efficiency by about 12%, reduce natural gas consumption by about 54% and heating cost by about 25%, and its cost-effective heat transmission distance of the primary heating network could approach about 28 km, which contributes to efficient exploiting deep geothermal fields far away from urban districts for space heating.

A set of dynamic models was developed for an indirect district heating system (IDHS), including pumps and adjusting valves. Firstly, dynamic simulations were conducted to find out how the supply water temperature of the boiler, indoor air temperature and fuel consumption vary with outdoor temperature. The influence of outdoor temperature could be compensated by modulating fuel consumptions, but the influences of solar radiation and indoor heat gains could not be ignored. Then, one-week operational states were simulated with actual meteorological data exerted and validated. And then, different control strategies were implemented and the one-week operational situations were simulated, respectively. The smallest indoor temperature variations could be achieved if the fuel, the primary piping network and radiator water flow rates were jointly controlled. However, the least amount of energy was consumed if the fuel consumption was controlled in terms of boiler supply temperature jointly with primary piping network flow rate controlled in terms of indoor temperature.

Waste heat recycled from supermarket refrigeration systems (SRS) exhibits a potential heat source that can supply the required heat to the supermarket or sell to the district heating system (DHS), thereby reducing the gross heat costs. This paper presents a cost-effective heat recovery control (HRC) for the heat recovery unit (HRU) integrated into SRS. The basic idea is to manipulate dynamically the amount of heat recovery by minimizing the real-time heat recovery cost based on quantifying heat production of SRS and dynamic energy prices. Moreover, a field test is conducted based on data communication between a master control computer executing the proposed control strategy and remote monitoring SRS. Experimental testing results and comparisons with other simulation cases demonstrate that the proposed method could promote a cost-effective heat recovery for SRS.

The research paper is focused on how to choose the most suitable renewable energy solution using multi-criteria analysis for a district heating system. Making choices is based on indicators – economic, environmental and social. In this case, the study used five indicators: resources costs, totals investments, reduction of greenhouse gas emissions, specific weight of renewable energy resources and impact on utilized land. Three situations have been compared – current situation: gas boiler, planned: solar collectors 21 595 m2 + accumulation tank 8000 m3 and alternatives: solar PV panels 5504 m2 – heat pump COP 3 are used in the estimation. The multi-criteria decision-making analysis shows that solar collectors 21 595 m2 + accumulation tank 8000 m3 are considered as the best alternative. The methodology is based on choosing a solution for a district heating company in Latvia.

The design and operational optimisation of fourth generation district heating networks is a crucial step towards highly renewable energy systems of the future. In order to optimise such complex systems, a toolbox modesto (multi-objective district energy systems toolbox for optimisation) is being developed. Seasonal thermal energy storage is an essential technology to allow larger shares of renewable energy sources, yet large computational power is required for its representation in full-year operational optimisations, as a step towards district energy system optimal design. To decrease computational complexity, a technique with representative days able to include seasonal thermal energy storage systems is developed and validated. This methodology combines different part-solutions from literature, but also adds a novel aspect to safeguard the chronology of the optimisation problem. To validate the approach, the design optimisation of a fictitious solar district heating system with seasonal thermal energy storage is compared to different representative day optimisations in two steps. The operational optimisation is a linear optimisation problem, implemented using modesto ; the design optimisation is built as a genetic algorithm, optimising the size of the storage and solar systems in the network. The validation exercise is done for the operational and for the design optimisation separately. This comparative study shows that modelling with representative days adequately mimics the behaviour for the presented case. Furthermore, a solution speed-up in the order of 10–30 times is shown for the representative optimisations with respect to the full year optimisation, in line with the reduction of the number of variables.

Evidence from a various research suggests that buildings hold a vital role in climate change by significantly contributing to the global energy consumption and the emission of greenhouse gases. Considering the trend of higher energy consumption in the building sector, it is important to influence this sector by decreasing its energy demand. District generation and cogeneration systems integrated with the energy storage system have been suggested as a potential solution to achieve such planned goals. Unlike the older generation of the DHS, where the focus of the design was on minimizing the system heat loss, in 4th generation DHS, achieving higher system efficiency is made possible by picking the optimal equipment size as well as adopting the appropriate control strategy. Designers have adopted different design methods for selecting the equipment size, however, finding the optimal size is a challenging task. This paper reports the development of a simplified methodology (dynamic optimization) for a hybrid community-district heating system (H-CDHS) integrated with a thermal energy storage system by coupling the simulation and optimization tools together. Two, existing and newly built communities, have been considered and the results of the optimization on the equipment size of both communities have been studied. The results for the newly built community is later compared with the one obtained from the conventional equipment size methods whereas static optimization methods and potential size reduction with the conventional method has been obtained.

The identification of heating load patterns, also known as load profiles, is of vital importance to effective management and operation of district heating system (DHS). Clustering algorithms have been successfully applied in identifying heating load patterns. In this paper, we propose that the heating load patterns should be analyzed more specifically, and Gaussian Mixture Model (GMM) clustering is selected to extract sub-patterns. The novelty of this paper is that a new GMM clustering is applied to identify temperature related sub-pattern and people behavior related sub-pattern, and the clustering result is further utilized to improve the accuracy of prediction models. An energy station in Tianjin is used as case studies and four typical operation patterns are found with their characteristic of occur time and energy signature, which are defined as working pattern, on-duty pattern, daytime–nighttime pattern and nighttime–daytime pattern. The results reveal that this proposed method can make an in-depth identification of heating load patterns and also proves that the prediction accuracies of regression and artificial intelligence model are significantly improved by utilizing the GMM clustering results.

Publisher Copyright: CCBY Lately, the European Union has reinforced the targets set to cut back carbon emissions. The energy generation sector and particularly, the district heating (DH) system, is still prevailed by combustion of fossil fuels that heavily contributes to such emissions. This paper presents a system-based approach to study the coupling between electricity and DH sector for effective mitigation of emissions. A mixed integer linear programming framework is proposed that aims to exploit the flexibility of electricity cogeneration together with partial electrification of the DH system by investing in renewable technologies. The objective is to simultaneously minimize the investment cost and emissions. Both the electricity and DH load profiles are segregated into critical and flexible types. Comprehensive demand response (DR) framework of thermostatically controlled loads and electric vehicles is considered while preserving the chronology. The framework is applied to the Finnish energy system considering the generation mix. Results prove that coordinating the electricity cogeneration with renewable generation combined with partly shifting from DH to electrified heating has a great potential in reducing the emissions. For an average weather scenario under DR, the least-cost solution guarantees an annual emission reduction of 12.04% relative to the total emissions of Finland against the total investment of €13.24Bn in wind and solar power generation.

The Republic of Moldova have presented, in March 2020, to the Secretariat of the UNFCCC the second Nationally Determined Contribution (NDC2). The country’s new economy-wide unconditional target is to reduce its greenhouse gas emissions by 70% below its 1990 level in 2030. The economy-wide conditional target, in NDC2 is up to 88% below 1990 level, if a global agreement addressing important topics including low-cost financial resources, technology transfer, and technical cooperation, accessible to all, is secured. The implementation of the NDC2 targets will require major change in current model of energy use in the country, in particular the advanced heat pumps are one option for district heating systems to secure clean and affordable heating for the people. The paper presents results of TIMES modeling of district heating system scenarios to year 2050, with consideration of climate change targets of NDC2. The results show that with CO2 emissions limits, the gas fired CHPs are replaced by distributed heat pumps at the consumers side. The results were obtained in the framework of the of the State Program 20.80009.7007.18: “Eco-innovative technical solutions for improving energy consumption in buildings and the smart grids development options with advanced integration of renewable energy in Moldova (SYNERGY)”.

This paper presents a modeling and simulation method that supports energy performance assessment and operation strategy investigation of borehole thermal energy storage in the Chifeng district heating (DH) system. A living laboratory in Chifeng, China that integrates a 0.5 million m3 borehole thermal energy storage system, an on-site solar thermal plant and excess heat from a copper plant is presented. The research adopts Modelica models from open source libraries to evaluate the system. The validity of the borehole thermal energy storage model is evaluated through an inter-model comparison study and an empirical validation test. We used the validated model to investigate three operation strategies. We conclude that the time-scheduled combined operation strategy is more beneficial for the studied system regarding CO2 emission reduction.

District heating (DH) has been highlighted as an important part in future carbon neutral energy supply. However, the performance of different DH systems varies a lot and the existing regulations do not always motivate DH companies to move toward more sustainable heat production. Therefore, this article presents novel methodology for Climate index determination which can be further used for the comparison of DH systems. The Climate index includes seven different indicators which show DH system performance according to energy efficiency, sustainability and environmental impact dimensions. The methodology is applied for 20 different DH systems operating in Latvia. The results show that the performance of 5 natural gas-based DH systems is below the determined climate benchmark.

Koreans usually prefer the district heating system (DHS) to the individual heating system (IHS) because DHS can give them convenience and safety within their living environment. The Korean government thus plans to expand the DHS and requires information about the value that consumers place on the DHS over the IHS, which has not been dealt with in academic literature. This paper attempts to investigate Korean households’ willingness to pay (WTP) for DHS over IHS, for residential heat (RH). To this end, the authors apply the dichotomous choice contingent valuation to assessing additional WTP for DHS using a survey of 1000 randomly selected households living in buildings with IHS. A mixture model is applied to deal with the zero WTP responses. The WTP distribution is specified as a mixture of two distributions, one with a point mass at zero and the other with full support on the positive half of the real line. The results show that the mean additional WTP for DHS-based RH over IHS-based RH is estimated to be KRW 5775 (USD 5.4) per Gcal. This value can be interpreted as the consumer’s convenience benefits of DHS over IHS, and amounts to approximately 6.0% of the average price: KRW 96,510 (USD 90.4) per Gcal in 2013, for IHS-based RH. This information is useful for evaluating changes to the method used for supplying RH from IHS to DHS.

District heating is thought as an important part of future energy system because of the easier accessibility to renewables and waste heat sources. Despite facing the problems such as rapid efficiency improvement in individual heating and energy-saving activities, the overall energy efficiency of district heating is higher than individual heating. With a comprehensive review on the recent development of district heating systems, this chapter introduces the key technologies, system design and integrated urban planning toward a future district heating system, particularly emphasizes the measures for multiscale demand-side management to enhance the performance of district heating system. In addition, the authors’ practice of district-heating-oriented integrated urban planning in Japan are also introduced as the reference for transiting towards renewable-energy-driven district heating.

Multiple energy carriers can be coupled as an Integrated Energy System (IES) through interconnection technologies. Unexpected risks will be transferred with the growing coupling of energy systems, mainly stemming from the uncertainties in different energy sectors. It is imperative to coordinate the operation of different energy systems to improve energy efficiency and ensure energy security. With the close integration of different energy systems, it is necessary to couple these different energy markets to achieve the holistic energy supply economy. On the other hand, uncertainties in the energy systems will bring the financial risk for the operator of IES. A risk-averse stochastic market clearing model for the IES is proposed to study the operating strategy aiming at minimizing the operation cost. While the financial risk imposed by the wind power uncertainties is restricted to a predefined level. Simulations results are provided to verify that the proposed model can improve market efficiency and handle the trade-off between cost and risk.

Evaluating the feedstock requirement of biomass-fed district heating systems is important when planning their installation or expansion. Public acceptance, which favors or deters the utilization of biomass, could be impacted by feedstock supply logistics. Feedstock requirement of district heating plants depends on the heat demand from the consumer and biomass quality characteristics, which vary over time. Previous studies on utilizing biomass for district heating mostly assumed average feedstock quality characteristics and aggregated heat demand values without considering their daily variations. While using average quality characteristics provides the average feedstock requirement of the plant, the actual requirement may vary significantly from the average value when daily variations in quality characteristics are considered. Not including these variations could lead to infeasibilities in meeting the heat demand of the plant. This study assesses the feedstock requirement of expanding a district heating plant considering daily variations in biomass quality characteristics and heat demand. A Microsoft Excel-based simulation model with one-year planning horizon and daily time steps is developed for the assessment. The costs and CO2-eq emissions of using different feedstock types are evaluated with and without trucking limitations. The developed model is applied to a real biomass-fed district heating plant at the University of British Columbia, Canada. The capacity of the heating plant is planned to be expanded from 6 MW to 18 MW. Three feedstock types, namely, wood residues, pellets and briquettes, and a mix of them are assessed. The results suggest that when enough trucking capacity is available, the plant would receive 2–9 truckloads of wood residues or 1–3 truckloads of pellets/briquettes. The expansion could reduce the total CO2 emissions by about 11,000 tonnes compared to those emitted by the 6 MW (current) biomass-fed heating capacity and natural gas (for a total of 18 MW) when sufficient biomass is available to the plant. However, when trucking is limited, using only wood residues could cause biomass shortage for almost half of the year and result in more emissions due to natural gas consumption. Utilizing energy dense feedstock, such as pellets and briquettes, could mitigate the effects of limited trucking, though, the total fuel cost could increase by 76% and 58%, respectively, compared to using only wood residues. Using a mix of wood residues and pellets/briquettes could achieve a reasonable trade-off between emission reduction and unit fuel cost.

In traditional integrated electricity and district heating systems, the inflexible operation of combined heat and power units leads to a large amount of wind power curtailments during winter. The thermal inertia of aggregated buildings can provide additional operational flexibility to promote wind power accommodation. In this study, a day-ahead scheduling model for integrated electricity and district heating system considering the thermal inertia of buildings is proposed. In this work, the operation model of the district heating network under constant mass flow and variable temperature operation strategy is presented, and the aggregated model of buildings based on the detailed thermal model of buildings is established. Then, the scheduling framework is analysed and the day-ahead scheduling model is formulated as quadratic programming problem to minimise the operation cost of integrated electricity and district heating system. The validity of the proposed model is verified by the case studies performed on a 6-bus power system with a 6-node heating system and IEEE 39-bus electricity system with a 16-node heating system. The results demonstrate that the thermal inertia of buildings can provide additional operational flexibility and effectively help reduce wind power curtailment and operation costs.

the scope of the work is solving the multicriteria task - determination of the optimal ratio between the heat rejected from the return water and the external air for designing of heat pump of maximum efficiency. The goal has been achieved by resolving the following tasks: energy efficency calculus of Combined Heat Power Plant (CHPP) with district heating pumps using a part of return water heat and using ambient air as source of low temperature heat for hot water production, elaboration thermodynamical cycles for heat pump.

The aim of this article was to determine the energetic effect of use buildings and a district heating network as thermal energy storages to compensate the reduced heat output of the district heating system. Moreover, another so far underestimated values were analyzed, like the effect of the incidence of external temperature and duration of episodes with the lowest external temperatures on the heat output of the district heating system based on 63 heating seasons. Obtained results were presented for the reference district heating system in Poland. According to the results, an average daily external temperature below −15 °C occurred once per heating season and temperatures below −20 °C occurred only once in four heating seasons. The analysis shows that a temperature of −18 °C can be adopted as the reference to determine the expected heat output in the DHS. On this basis the heat output can be reduced for central heating by 1%. The energetic effect of use buildings and a district heating network as thermal energy storages to compensate the reduced heat output of the district heating system was 16.2 MW. The achieved equivalent heat output was 93.2 MW. Considering all solutions, the heat output can be reduced for central heating by 14.8%.

Solar thermal energy is widely recognized as one of the most important renewable energy resources. However, in high latitudes, due to various climatic and mismatch challenges, such solar district heating networks are difficult to implement. The objective of the paper is to optimize and compare two different design layouts and control strategies for solar district heating systems in Finnish conditions. The two different designs proposed are a centralized and a semi-decentralized solar district heating system. The centralized system consists of two centralized short-term tanks operating at different temperature levels charged by a solar collector and heat pumps. Borehole thermal energy storage is also charged via these two centralized tanks. In contrast, the semi-decentralized system consists of one centralized low temperature tank charged by a solar collector and a borehole thermal energy storage and decentralized high temperature tank charged by an individual heat pump in each house. In this case, borehole thermal energy storage is charged only by the centralized warm tank. These systems are designed using the dynamic simulation software TRNSYS for Finnish conditions. Later on, multi-objective optimization is carried out with a genetic algorithm using the MOBO (Multi-objective building optimizer) optimization tool, where two objectives, i.e. purchased electricity and life cycle costs, are minimized. Various design variables are considered, which included both component sizes and control parameters as inputs to the optimization. The optimization results show that in terms of life cycle cost and purchased electricity, the decentralized system clearly outperforms the centralized system. With a similar energy performance, the reduction in life cycle cost is up to 35% for the decentralized system. Both systems can achieve close to 90% renewable energy fraction. These systems are also sensitive to the prices. Furthermore, the results show that the solar thermal collector area and seasonal storage volume can be reduced in a decentralized system to reduce the cost compared to a centralized system. The losses in the centralized system are 40–12% higher compared to the decentralized system. The results also show that in both systems, high performance is achieved when the borehole storage is wider with less depth, as it allows better direct utilization of seasonally stored heat. The system layout and controls varied the performance and life cycle cost; therefore it is essential to consider these when implementing such systems.

The rational and effective operation regulation mode of a district heating system plays a significant role in heating feasibility, security, and energy savings of an integrate heat and power dispatch system for integrating fluctuating wind power. In this study, a new integrated heat and power dispatch model considering the thermal inertia of an indirect connection district heating system (including the district heating network and buildings) were proposed, in which complete hydraulic and dynamic thermal model of the indirect connection district heating system was first proposed and the function of the integration method was further improved for simulating the dynamic temperature distribution of a district heating network under variable flow conditions. On this basis, the operation regulation modes of the district heating system were respectively applied into the integrated heat and power dispatch model to analyse and compare their effects on an integrated heat and power dispatch system for wind power integration in terms of heating feasibility, security, and energy saving, in which a real indirect connection district heating system in Jilin Province was used. Results demonstrate that the proposed model can truly utilize the thermal inertia of an indirect connection district heating system to increase the wind power integration by regulating the operation of the heat source based on the optimal temperature and flow rate at the heat source and the predicted indoor temperature. Case studies show that applying the “variable temperature-variable flow control mode” to the integrated heat and power system is more economical, which is 0.9% less than the “variable temperature control mode” by reducing the pump power consumption and 2.9% less than the “centralized control with flow varied by steps mode” by promoting wind power integration. Therefore, the proposed integrated heat and power dispatch model can be applied to truly utilize the thermal inertia of an indirect connection district heating system for wind power integration and select the best operation regulation mode of the district heating system for wind power integration in an integrated heat and power dispatch system.

In nowadays, increased energy efficiency in buildings and reduced thermal energy consumption requires innovative solutions and appropriate district heating system development planning process. 4th generation district heating system is one of the key solutions for improved overall system efficiency by decreased heat losses, improved heat generation efficiency, more efficient use of renewable energy sources and other advantages. The article describes the approach and the methodology for development of strategy to transform the existing DH system to 4GDH system particularly in cases with low DH systems loads. Two factors (low heat load and low temperatures) are becoming more and more actual. The article analyses the transformation process of the particular small-scale DH system in a parish located in the East part of Latvia. As a result, several transformation scenarios are identified. The technical solutions include replacement of a boiler, heating network reconstruction, heat supply temperature lowering and solar panel installation. Further technical analyses is carried out for system development evaluation and strategy implementation. Results shows that it is essential to evaluate the future energy efficiency measures in buildings when such small scale system is evaluated as it results in lower heat density and higher specific heat losses.

The transition towards 4 th generation district heating systems are widely studied in last years. In this research, the economic reasonability of recovered industrial waste heat usage in the district heating system is investigated. Research is based on a case situation with an actual district heating system and nearby located factory with possible waste heat. This article contains a description and characteristics of selected district heating system and potential waste heat source, the overall methodology for the thermal energy potential and recovery calculations of waste heat flow. Taking into account losses in transmission, 67.5 MWh of heat can be transferred to the heat supply network every month, covering 4–12 % of the system load during the heating season. This would reduce the CO 2 emissions from the heating system by 5–10 % monthly.

Peak load has significant impacts on the economic and environmental performance of district heating systems. Future sustainable district heating systems will integrate thermal storages and renewables to shave their peak heat demand from traditional heat sources. This article analysed the techno-economic potential of implementing thermal storage for peak load shaving, especially for the district heating systems with waste heat recovery. A campus district heating system in Norway was chosen as the case study. The system takes advantage of the waste heat from the campus data centre. Currently, about 20% of the heating bill is paid for the peak load, and a mismatch between the available waste heat and heat demand was detected. The results showed that introducing water tank thermal storage brought significant effects on peak load shaving and waste heat recovery. Those effects saved up to 112 000 EUR heating bills annually, and the heating bill paid for the peak load could be reduced by 15%. Meanwhile, with the optimal sizing and operation, the payback period of the water tank could be decreased to 13 years. Findings from this study might help the heat users to evaluate the economic feasibility of introducing thermal storage.

Performance of the new enhanced ejector heat exchanger is the key to improving performance of the district heating system based on industrial waste heat, and it is significantly affected by thermo-physical property of refrigerant. In this paper, characteristics of the new enhanced ejector heat exchanger are considered, and a new principle for screening refrigerant is proposed. Eleven kinds of refrigerants are firstly selected as candidates, and then they are evaluated from the perspective of property and thermodynamic performance of the new enhanced ejector heat exchanger. The results show that refrigerant property has a greater influence on thermodynamic performance of the new enhanced ejector heat exchanger. Under the condition of low temperature space heating, R152a and R1234yf are favorable choices for the new enhanced ejector heat exchanger. While under conditions of other temperature space heating, R245fa and R600 are better choices for the new enhanced ejector heat exchanger.

Krakow has an extensive district heating network, which is approximately 900 km long. It is the second largest city in terms of the number of inhabitants in Poland, resulting in a high demand for energy—for both heating and cooling. The district heating of the city is based on coal. The paper presents the conception of using the available renewable sources to integrate them into the city’s heating system, increasing the flexibility of the system and its decentralization. An innovative solution of the use of hybrid, modular heat pumps with power dependent on the needs of customers in a given location and combining them with geothermal waters and photovoltaics is presented. The potential of deep geothermal waters is based on two reservoirs built of carbonate rocks, namely Devonian and Upper Jurassic, which mainly consist of dolomite and limestone. The theoretical potential of water intake equal to the nominal heating capacity of a geothermal installation is estimated at 3.3 and 2.0 MW, respectively. Shallow geothermal energy potential varies within the city, reflecting the complex geological structure of the city. Apart from typical borehole heat exchangers (BHEs), the shallower water levels may represent a significant potential source for both heating and cooling by means of water heat pumps. For the heating network, it has been proposed to use modular heat pumps with hybrid sources, which will allow for the flexible development of the network in places previously unavailable or unprofitable. In the case of balancing production and demand, a photovoltaic installation can be an effective and sufficient source of electricity that will cover the annual electricity demand generated by the heat pump installation, when it is used for both heating and cooling. The alternating demand of facilities for heating and cooling energy, caused by changes in the seasons, suggests potential for using seasonal cold and heat storage.

District heating system is designed to minimize energy consumption and environmental pollution by employing centralized production facilities connected to demand regions. Traditionally, optimization based algorithms were applied to the heat production planning problem in the district heating systems. Optimization-based models provide near optimal solutions, while it takes a while to generate solutions due to the characteristics of the underlying solution mechanism. When prompt re-planning due to any parameter changes is necessary, the traditional approaches might be inefficient to generate modified solutions quickly. In this study, we developed a two-phase solution mechanism, where deep learning algorithm is applied to learn optimal production patterns from optimization module. In the first training phase, the optimization module generates optimal production plans for the input scenarios derived from operations history, which are provided to the deep learning module for training. In the second planning phase, the deep learning module with trained parameters predicts production plan for the test scenarios. The computational experiments show that after the training process is completed, it has the characteristic of quickly deriving results appropriate to the situation. By combining optimization and deep learning modules in a solution framework, it is expected that the proposed algorithm could be applied to online optimization of district heating systems.

Approach to mathematical modeling of temperature regime of district heating systems was analyzed. Using the single-circuit individual heat point, the temperature regime of the district heating system was simulated, taking into account the control of the outside air temperature and the specific thermal characteristics of the buildings. Measures to reduce the level of thermal energy consumption and CO 2 emissions and to provide comfortable indoor conditions have been identified. The results of the study show that this approach can reduce overall heat consumption and CO 2 emissions by 21-23%.

Background Local biomass potential in Southeastern European countries is relatively high. Nevertheless, biomass residues such as wood leftovers, straw and energy crops are often not properly managed or inefficiently utilised for energy purposes in individual house heating or domestic hot water preparation. This is more relevant in rural areas, where the utilisation of biomass resources is mainly based upon traditional technologies, has low efficiency or is carried out by using individual bases without local energy supply management. Usage of biomass residues in combination with other renewable energy sources is in agreement with the targets of the EU’s Energy and Climate Goals and promotes rural development and a circular economy. Methods For this purpose, local heating and domestic hot water preparation demands, as well as the available biomass potentials, were analysed and mapped by using a geographic information system (GIS). A model for analysing the optimal operation of the district heating boiler with a relatively high share of solar energy, which is backed up by either a short- or long-term heat storage, was developed. The model takes the supply and the return temperatures from the DH network into account and decides whether the excess of solar heat produced by the prosumers can be delivered into the network. This reduces heat overproduction and enables a smooth and uninterrupted operation of the system. Such configuration would benefit both the DH Company and the prosumers. The DH Company would have the opportunity to buy cheaper excess heat from the prosumers rather than to start its own and relatively slow biomass boiler. Results In this paper, several scenarios are proposed for the Romanian village Ghelinta. The target village is characterised by a small-scale biomass district heating boiler with thermal storage and prosumers with either solar thermal collectors or locally installed heat pumps. Integration of seasonal thermal storage and local prosumers can smooth out the biomass district heating boiler operation and bring additional socio-economic benefits for the bioenergy village communities. This could be the first step towards the establishment of a micro-scale thermal energy market. Conclusions Analysis has proven that the proposed system configuration is socio-technically feasible, even for micro-scale systems, as apparent in the Romanian target village Ghelinta. The main objective of this research is to analyse the implementation of a small-scale biomass and renewable energy-based district heating system and to prove the concept of bioenergy villages from a technical and economical perspective. Furthermore, the role of residential household prosumers has been analysed. Based on outcomes, the transferability of the results is also discussed, while several suggestions for stakeholders who implement such projects were formulated for future research as well.

With the rapid development of the data center industry, a major source of waste energy is created through the increasing demand for cloud-based connectivity and performance. A recent study demonstrated that data centers are responsible for approximately 1.3% of total global electricity usage. In addition, nearly 40% of this power is consumed by computer room air conditioning (CRAC) systems for cooling the servers, which creates a significant stream of waste heat. The waste heat in a data center has a low quality; therefore, recovery and reuse of the waste eat is a challenge. In this study, a district heating system solution using waste heat in a data center was introduced. A distributed cooling solution was discussed to improve the quality of this waste heat. Then, heat pump technology was used to further raise the quality. The energy-saving effect was theoretically compared with coal-fired heating. A new index PUEwh was defined to evaluate the power utilization effectiveness of the data center with the heat recovery system. This waste heat district heating solution was implemented at a data center in Hohhot, China, and measurements demonstrated that the PUEwh of this data center was 0.13.

To better facilitate renewable energy systems, the district heating sector is currently changing towards lower temperatures and increased cross-sectoral integration. Seasonal thermal energy storage systems alongside heat pumps have received an increasing attention. However, the operation of a seasonal thermal energy storage system alongside a heat pump is more complex than a short-term thermal energy storage system, and as such, several complex simulation models have been developed. These models have shown to be usable for simulating the operation, but due to their complexity are difficult to implement in simulation models that focus on overall energy system analyses. Based on the operation of an existing seasonal thermal energy storage system, this paper provides a simulation method for a seasonal thermal energy storage system with a heat pump that can be utilized in overall energy system simulation models. The simulation method is based on the proven different operational situations of the seasonal thermal energy storage system. The method is shown to be able to approximate the actual operation on an hourly basis and the yearly thermal losses.

Seasonal thermal energy storage (STES) technology is a proven solution to resolve the seasonal discrepancy between heating energy generation from renewables and building heating demands. This research focuses on the performance assessment of district heating (DH) systems powered by low-grade energy sources with large-scale, high temperature underground STES technology. A pilot DH system, located in Chifeng, China that integrates a 0.5 million m3 borehole thermal energy storage system, an on-site solar thermal plant and excess heat from a copper plant is presented. The research in this paper adopts a model-based approach using Modelica to analyze the energy performance of the STES for two district heating system configurations. Several performance indicators such as the extraction heat, the injection heat and the storage coefficient are selected to assess the STES system performance. Results show that a lower STES discharge temperature leads to a better energy performance. A sensitivity analysis of the site properties illustrates that the thermal conductivity of soil is the most influential parameter on the STES system performance. The long-term performance of the STES is also discussed and a shorter stabilization time between one and two years could be achieved by discharging the STES at a lower temperature. This research is part of the seasonal storage for solar and industrial waste heat utilization for urban district heating project funded by the Joint Scientific Thematic Research Programme (JSTP)–Smart Energy in Smart Cities. We gratefully acknowledge the financial support from the Netherlands Organisation for Scientific Research (NWO). We would also like to thank our research partners from Tsinghua University working on the project of the International S&T Cooperation Programof China (ISTCP) (project No. 2015DFG62410). Without their efforts, we would not have been able to obtain the technical data to conduct the case study.

This paper deals with an energy and exergy evaluation and modeling of geothermal district heating systems for their system analysis, performance evaluation and optimization. As a comprehensive case study, the Afyon geothermal district heating system (AFJET) in Afyon, Turkey is considered and actual thermal data are collected and employed for analysis. Using actual system data, an evaluation of the district heating system performance, energy and exergy efficiencies, and exergy destructions in the system are conducted in this regard. This study is also conducted to show how energy and exergy efficiencies of the GDHSs will change with the reference temperature and how exergy losses will affect by the temperature difference between the geothermal resource and the supply temperature of the district heating distribution network. In addition, the negative effects of discharge waters of the AFJET are presented. The energy and exergy efficiencies of the entire AFJET are found to be 37.59% and 47.54%, respectively. The results are expected to be helpful to researchers and engineers in the area. © 2010 Published by Elsevier Ltd. All rights reserved., The authors gratefully acknowledge the support provided for the present work by the AFJET Geothermal Inc. and the personal support of the managing director, Mr. Erhan Ozsakaci. They are also very grateful to the reviewers and the editor for their valuable and constructive comments, which have been utilized in improving the quality of the paper. E energy (kJ) Ex exergy (kJ) E ' energy rate (kW) Ex · exergy rate (kW) F ' exergy rate of the fuel (kW) f exergetic factor (%) h specific enthalpy (kJ/kg) I ' irreversibility (exergy destruction) rate (kW) IP improvement potential rate (kW) m ' mass flow rate (kg/s) P ' exergy rate of the product (kW) P pressure (kPa) Q ' rate of heat (kW) s specific entropy (kJ/kg K) S ' entropy rate (kW/K) W ' work rate, power (kW) T temperature (°C or K) SExI specific exergy index (dimensionless)

Short-term heat demand forecasting in district heating (DH) systems is essential for a sufficient heat supply and optimal operation of the DH. In this study, a machine learning based multi-step short-term heat demand forecasting approach using the data of the largest Slovenian DH system is considered. The proposed approach involved feature extraction and comparative analysis of different representative machine learning based forecasting models. Nonlinear models performed better than linear models, and the best forecasting results were obtained by Gaussian process regression (GPR), where the mean absolute normalized error was 2.94% of the maximum heating power of the DH system. The analysis confirmed the importance of accurate temperature forecasts but did not confirm the relevance of using future solar irradiation forecasts. The optimal length of training data is shown to be 3 years, and past data of up to 4 days can be used as input to increase the forecasting accuracy. The forecasting model (GPR) proposed in this study can be fitted to different DH systems. In the presented case study, it was selected to implement the online forecasting solution for the DH of Ljubljana and has been generating forecasts with a mean absolute normalized error of 2.70% since November 2019.