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This article provides the state-of-the-art on the optimal planning and design of future district heating (DH) systems. The purpose is to provide practical information of first-step actions for countries with a low DH market share for heating and cooling supply. Previous research showed that for those countries, establishing a heat atlas with accurate geographical data is an essential prerequisite to promote the development of DH systems. In this review, essential techniques for building a high-quality heat atlas are elaborated. This includes a review of methodologies for district thermal energy demand prediction and the status of the integration of sustainable resources in DH systems. In the meanwhile, technical barriers for the implementation of various sustainable heat sources are identified. Furthermore, technologies for the optimal planning of DH systems are discussed. This includes the review of current approaches for the optimal planning of DH systems, discussions on various novel configurations which have been actively investigated recently, and common upgrading measures for existing DH systems.

Rationalising the production and use of thermal energy would be the key to energy transition. However, in most rural areas heat planning and just transition is challenging. Energy geography solutions such as innovative online heat atlases, like Hotmaps are valuable tools for estimating household heat demand at municipality level. The aim of this study was twofold, firstly to validate the Hotmaps database with the help of field-obtained actual consumption data and to determine its usability for local thermal energy planning. Secondly to develop and test a complex methodology supporting the definition of a heating energy mix in a highly diverse landscape and energy mix in a Hungarian rural study area facing coal phase-out. The results confirmed that settlements with residential heat demand above 5,000 MWh/a could rely on the Hotmaps, however, mapping the local heating energy mix can only be done by field data collection, especially where the ratio of the solid fuels is over 50%. The heating energy mix can vastly vary even within a small geographical area which underlines the importance of in-situ rural energy mapping and makes clear the need to develop such complex but replicable methodologies as this paper has.

There is a strongly growing interest for wastewater heat recovery (WWHR) in Sweden and elsewhere, but a lack of adequate tools to determine downstream impacts due to the associated temperature drop. The heat recovery potential and associated temperature drop after heat recovery on a building level is modelled for a case study in Linköping, Sweden. The maximum temperature drop reaches 4.2 °C, with an annual recovered heat of 0.65 kWh · person−1 · day−1. Wastewater temperature out from the heat exchanger was 18.0 °C in winter at the lowest. The drinking water source type can be an important factor when considering wastewater heat recovery.

This paper aims to present an approach for the planning of carbon low heat supply in a future district heating system based on open data for German cities with existing district heating networks. One focus is on the integration of industrial waste heat and the uncertainty of future waste heat sources as well as restrictions on the use of biomass. For that purpose, knowledge about the energy demand is necessary. In a first step it is shown how the demand around a heating network is estimated with spatial data and a load profile is generated. Local available heat sources are examined according to their suitability and their kind of integration in the heating network. As heat production from different units are optimised, the development of a simulation model will be presented. The simulation is based on the optimisation of the operational costs of the used technologies for heating supply. Different scenarios covering various technologies and economic assumptions are applied. The results show the levelized costs of heating as well as the ecological performance. A sensitivity analysis shows the importance of uncertainties for the economic assumptions. The results showing levelized costs of heating as well as the ecological performance underlining the advantage of excess heat integration.

In this work, a model of an energy system based on photovoltaics as the main energy source and a hybrid energy storage consisting of a short-term lithium-ion battery and hydrogen as the long-term storage facility is presented. The electrical and the heat energy circuits and resulting flows have been modelled. Therefore, the waste heat produced by the electrolyser and the fuel cell have been considered and a heat pump was considered to cover the residual heat demand. The model is designed for the analysis of a whole year energy flow by using a time series of loads, weather and heat profile as input. This paper provides the main set of equations to derive the component properties and describes the implementation into MATLAB/Simulink. The novel model was created for an energy flow simulation over one year. The results of the simulation have been verified by comparing them with well-established simulation results from HOMER Energy. It turns out that the novel model is well suited for the analysis of the dynamic system behaviour. Moreover, different characteristics to achieve an energy balance, an ideal dimensioning for the particular use case and further research possibilities of hydrogen use in the residential sector are covered by the novel model.

The aim is to assess the impact of the civil sector’s heat demand electrification on the entire energy system, in the Italian case study. The hourly heat demand profiles are estimated at census cells level using the BIN method or monitoring data. Profiles are used as input in the oemof-based NEMeSI model employed to optimize both the capacity expansion of power generation and the operation of the power system in 2030, with hourly temporal resolution and NUTS2 spatial detail, in three heat demand electrification scenarios. The model considers the availability of sources, the import and export profiles, and the limit on renewable sources. The results show that no additional capacity of renewable energy is driven by the increasing electrification in fact the installed capacity remains the same in the three scenarios (97GW of photovoltaic and 33GW of wind turbines). The increase of power demand results in a reduction of overgeneration (48.6TWh to 38.3TWh), an increase in installed batteries (40.6GWh to 115.3GWh) and in CHP (+10%) and CCPP systems (+16%). The results show a slight increase of natural gas in electricity generation (+5.2TWh) respect to a high reduction in its use in civil sector’s heat demand (-68.5TWh).

The paper presents a developed methodology of short-term forecasting for heat production in combined heat and power (CHP) plants using a big data-driven model. An accurate prediction of an hourly heat load in the day-ahead horizon allows a better planning and optimization of energy and heat production by cogeneration units. The method of training and testing the predictive model with the use of generalized additive model (GAM) was developed and presented. The weather data as an input variables of the model were discussed to show the impact of weather conditions on the quality of predicted heat load. The new approach focuses on an application of the moving window with the learning data set from the last several days in order to adaptively train the model. The influence of the training window size on the accuracy of forecasts was evaluated. Different versions of the model, depending on the set of input variables and GAM parameters were compared. The results presented in the paper were obtained using a data coming from the real district heating system of a European city. The accuracy of the methods during the different periods of heating season was performed by comparing heat demand forecasts with actual values, coming from a measuring system located in the case study CHP plant. As a result, a model with an averaged percentage error for the analyzed period (November–March) of less than 7% was obtained.

District heating plays a key role in achieving high primary energy savings and the reduction of the overall environmental impact of the energy sector. This was recently recognized by the European Commission, which emphasizes the importance of these systems, especially when integrated with renewable energy sources, like solar, biomass, geothermal, etc. On the other hand, high amounts of heat are currently being wasted in the industry sector, which causes low energy efficiency of these processes. This excess heat can be utilized and transported to the final customer by a distribution network. The main goal of this research was to calculate the potential for excess heat utilization in district heating systems by implementing the levelized cost of excess heat method. Additionally, this paper proves the economic and environmental benefits of switching from individual heating solutions to a district heating system. This was done by using the QGIS software. The variation of different relevant parameters was taken into account in the sensitivity analysis. Therefore, the final result was the determination of the maximum potential distance of the excess heat source from the demand, for different available heat supplies, costs of pipes, and excess heat prices.

This paper provides a comprehensive overview of policies and incentives aimed at promoting high-temperature heat pumps (HTHPs) globally. It examines the various strategies employed by different countries to encourage the adoption of HTHPs, highlighting both the opportunities and the barriers encountered in these efforts. The analysis includes a review of financial incentives, regulatory measures, and technological initiatives designed to facilitate the integration of HTHPs into industrial applications. By describing different approaches across regions, this paper identifies best practices and potential pitfalls, offering a nuanced understanding of how different policy frameworks impact the deployment of HTHPs. Additionally, this paper explores the technological challenges that influence the effectiveness of these policies. The findings underscore the critical role of supportive policies in overcoming technical and economic barriers, ultimately fostering the widespread use of HTHPs as a viable solution for reducing industrial emissions and advancing global decarbonization goals. Furthermore, utilizing electricity from renewable energy sources (RESs), HTHPs can also contribute to grid stability by reducing electricity peaks. This aspect enhances the integration of RESs into the energy mix, creating a more resilient grid and optimizing energy consumption patterns in industrial applications.

Excess heat can make an important contribution to reduce greenhouse gas emissions in the heating and cooling sector. Due to the local character of heat, the local excess heat potential is decisive for using excess heat. However, the spatially distributed potential and the subdivision of the potential into different subsectors have not been sufficiently investigated in Germany. Here we analyse the excess heat potential in Germany according to different subsectors and spatially distributed to the municipal level. We use data of more than 115,000 records on exhaust gas and fuel input from over 11,000 industrial sites. We calculate the site-specific excess heat potential and check its plausibility using the fuel input of the respective industrial sites. Finally, we compare the excess heat potential with the residential heat demand at the municipal level. Our results show that the excess heat potential in Germany is about 36.6 TWh/a, and that in 148 municipalities, the annual excess heat potential is greater than 50% of the annual heat demand. In conclusion, there is a large potential for excess heat utilisation in Germany. In some regions, more excess heat is available throughout the year than is needed to provide space heat and hot water.