Electricity Heat Research Articles

The race between hydrogen and heat pumps for space and water heating: A model-based scenario analysis

This paper analyses different levels and means of the electrification of space and hot water heating using an explorative modelling approach. The analysis provides guidance to the ongoing discussion on favourable pathways for heating buildings and the role of secondary energy carriers such as hydrogen or synthetic fuels. In total, 12 different scenarios were modelled with decarbonisation pathways until 2050, which cover all 27 member states of the European Union. Two highly detailed optimisation models were combined to cover the building stock and the upstream energy supply sector. The analysis shows that decarbonisation pathways for space and water heating based on large shares of heat pumps have at least 11% lower system costs in 2050 than pathways with large shares of hydrogen or synthetic fuels. This translates into system cost savings of around €70 bn. Heat pumps are cost-efficient in decentralised systems and in centralised district heating systems. Hence, heat pumps should be the favoured option to achieve a cost-optimal solution for heating buildings. Accordingly, the paper makes a novel and significant contribution to understanding suitable and cost-efficient decarbonisation pathways for space and hot water heating via electrification. The results of the paper can provide robust guidance for policymakers.

Comparative analysis of a multi-generation system using different conventional & nano based working fuels

The present study focuses on the energy and exergy analyses of a multi-generation system that uses both non-renewable and renewable energy sources, fulfilling the energy requirements of a community in a sustainable manner. The operational comparison of the proposed system with both conventional and non-conventional nano-based working fuels is also studied. The proposed system provides a total of six outputs which include electricity, desalinated water, space heating, space cooling, hot water, and waste heat for industrial purposes. The effects of variation in geothermal fluid’s mass flow rate, pressure, and quality on system outputs are evaluated. System performance with different fuels having varied calorific values is evaluated and it is found that the fuels with the highest calorific values provide the best possible system outputs. The outputs of the system at a specific working condition are 6.7 MW of electricity, 650 kW of waste heat, 10.54 kg/s of desalinated water, 41 kg/s of hot water, 331.7 kW of heating and 314.1 kW of cooling.

Технології електрогенерації та теплопостачання для підвищення енергетичної незалежності окремих територіальних громад

Russian attacks on Ukraine's energy system, which led to the blackout of entire cities and the termination of district heating, highlighted the risks and disadvantages of relying on large-scale district energy supply for communities. In this context, it is important to consider the development of the energy supply of communities in the direction of their energy independence. The purpose of the article is to form a list of electricity generation and heat supply technologies for increasing the energy independence of individual territorial communities, which are appropriate for implementation in Ukraine. The article considers the criteria for the analysis and selection of technologies for distributed power generation and heat supply. An analytical overview of the following power generation and heat supply technologies is presented: solar and wind power plants, gas piston and gas turbine plants, generators, batteries, co- and trigeneration plants, biofuel power plants and heat-generating boilers, heat pumps and electric boilers, and their grouping is performed according to the established criteria. All the considered technologies contribute to reducing the external supply of communities with energy resources and reducing losses during the transmission and distribution of electricity. Technologies that use renewable energy sources and local fuels are appropriate for implementation in communities in accordance with the availability of sufficient amounts of resources. Still, in most cases, they are not able to fully provide communities with electrical and thermal energy due to their insufficient quantity and high cost of equipment, such as batteries and heat pumps. Decisions regarding the implementation of a specific technology of distributed generation should be made after a thorough analysis of the conditions and possibilities of the energy supply of each individual community. This article is aimed at discussing the options of increasing energy independence and ensuring the reliability of the energy supply of territorial communities in Ukraine. Keywords: distributed generation, power generation, heat supply, renewable energy sources, cogeneration, biofuels, heat pumps.

Economic, Technical, and Environmental Benefits of Occupants’ Thermal Comfort-Based Heat Loads Participation in Demand Response Program

The electrification of heating and transportation systems is one of the objectives of developed countries to minimize CO2 emissions. This objective pushes distribution systems’ (DBs) operators to incorporate numerous high-power loads into low-voltage networks that were not designed for such loads. DBs’ reconfiguration and the loads’ flexible characteristics are two remedies exploited to overcome this issue. Heat pumps (HPs), as the most prevalent loads, can be managed by demand response programs (DRPs) to postpone the costly reconfiguration of distribution systems. HPs’ DRP participation affects indoor air temperature. If this is not accomplished reasonably, the occupants’ thermal comfort (OTC) will be compromised, and it will be impossible to convince them to continue contributing to DRPs. Based on the ASHRAE55 standard and an experimental building electrothermal model, this article presents a novel framework for determining the HPs’ DRPs participation. This framework ensures the OTC and optimizes the HPs’ DRP participation. The modified IEEE 33-bus network is employed as the test system to evaluate the proposed method. The simulation results confirm the usefulness of the proposed strategy to improve the technical and economic aspects of the network.

Electric-gas infrastructure planning for deep decarbonization of energy systems

The transition to a deeply decarbonized energy system requires coordinated planning of infrastructure investments and operations serving multiple end-uses while considering technology and policy-enabled interactions across sectors. Electricity and natural gas (NG), which are vital vectors of today’s energy system, are likely to be coupled in different ways in the future, resulting from increasing electrification, adoption of variable renewable energy (VRE) generation in the power sector and policy factors such as cross-sectoral emissions trading. This paper develops a least-cost investment and operations model for joint planning of electricity and NG infrastructures that considers a wide range of available and emerging technology options across the two vectors, including carbon capture and storage (CCS) equipped power generation, low-carbon drop-in fuels (LCDF) as well as long-duration energy storage (LDES). The model incorporates the main operational constraints of both systems and allows each system to operate under different temporal resolutions consistent with their typical scheduling timescales. We apply our modeling framework to evaluate power-NG system outcomes for the U.S. New England region under different technology, decarbonization goals, and demand scenarios. Under a global emissions constraint, ranging between 80%–95% emissions reduction compared to 1990 levels, the least-cost solution relies significantly on using the available emissions budget to serve non-power NG demand, with power sector using only 14%–23% of the emissions budget. Increasing electrification of heating in the buildings sector results in greater reliance on wind and NG-fired plants with CCS and results in similar or slightly lower total system costs as compared to the business-as-usual demand scenario with lower electrification of end-uses. Interestingly, although electrification reduces non-power NG demand, it leads to up to 24% increase in overall NG consumption (both power and non-power) compared to the business-as-usual scenarios, resulting from the increased role for CCS in the power sector. The availability of low-cost LDES systems reduces the extent of coupling of electricity and NG systems by significantly reducing fuel (both NG and LCDF) consumption in the power system compared to scenarios without LDES, while also reducing total systems costs by up to 4.6% for the evaluated set of scenarios.

Peer-to-peer energy trading for demand response of residential smart electric storage water heaters

Environmental concerns and emission reduction targets are driving a transition from fossil fuel to renewable-based electricity generation. However, intermittent and distributed renewable generation brings challenges for the grid operation, as the low voltage distribution grid increasingly becomes constrained during high residential solar PV generation. The electrification of water heating presents a large opportunity to address this challenge by intelligently responding to electrical network conditions. Smart water heaters with thermal storage can soak up excess PV as a thermal battery, which facilitates maximum renewable generation and solves local grid problems. However, the centralized operation of electricity markets tends to impede the benefits of the localized distributed energy resources (DER). In such a scenario, peer-to-peer (P2P) energy trading allows neighbouring prosumers to trade energy between themselves with minimum interference from electricity grid operators. This research develops a P2P energy trading framework, using advanced, multi-zone electric storage water heaters with autonomous and aggregated control. The financial benefits identified in this research are forthcoming due to new participation in the electricity market ancillary services, demand management and P2P energy trading. Simulated results have identified that up to 92% of household water heating energy can originate from their own rooftop PV. At the electricity grid level, P2P energy trading demonstrates an increase in the aggregated PV self-consumption from 39% to 83%, importantly allowing the remaining 17% to target grid support in periods of supply shortfall. Average retail consumer energy savings of AUD$369/annum are identified, which include 17% of savings that are attributed to P2P energy transactions, delivering a capital payback of <3 years.

RETRACTED:Optimum planning of energy hub with participation in electricity market and heat markets and application of integrated load response program with improved particle swarm algorithm

The drive for improved energy efficiency and flexibility has birthed an innovative solution: an energy hub. This hub operates in sync with natural gas and electricity grids, integrating batteries and thermal storage to optimize renewable energy use, reduce costs, and bolster network stability. In addressing these objectives, a mathematical optimization model for energy hub operation is developed in this paper. This model captures the intricate interplays between electricity and natural gas networks, accounting for the intricacies posed by uncertainties and variations in renewable energy sources and demand profiles. Also, this paper uniquely delves into the integration of load response programs, an approach geared towards amplifying the energy hub system's flexibility and reliability. Through these programs, subscribers gain the agency to calibrate their energy consumption based on real-time pricing signals and incentives dispensed by the energy hub. The simulation findings serve as a compelling testament to the efficacy of the proposed system. Operating costs witness a substantial reduction, the adoption of renewable energy sources is markedly heightened, and the stability and reliability of the upstream energy networks are tangibly ameliorated. The integration of load response programs emerges as a particularly effective strategy in mitigating peak demand and augmenting the system's overall energy efficiency. Underpinning the entirety of this innovative solution is the transformation of the challenges into an optimization problem. This catalyzes the employment of a newly developed particle community algorithm, custom-tailored to surmount the challenges of local optima. This algorithm inherently bolsters the system's search capabilities, minimizing the risk of entrapment within localized solutions. Ultimately, the proposed energy hub system encapsulates a promising trajectory toward the realization of a sustainable and adaptable energy landscape. By seamlessly integrating diverse energy sources and storage systems, augmenting energy flexibility and efficiency, and aligning with broader energy transition and decarbonization goals, this solution presents a formidable contender. The simulation outcomes underscore its potential by showcasing a substantial 4.57 % reduction in the cost of procuring energy from the upstream electrical network.

Projecting Future Energy Production from Operating Wind Farms in North America. Part III: Variability

Abstract Daily expected wind power production from operating wind farms across North America are used to evaluate capacity factors (CF) computed using simulation output from the Weather Research and Forecasting (WRF) Model and to condition statistical models linking atmospheric conditions to electricity production. In Parts I and II of this work, we focus on making projections of annual energy production and the occurrence of electrical production drought. Here, we extend evaluation of the CF projections for sites in the Northeast, Midwest, southern Great Plains (SGP), and southwest U.S. coast (SWC) using statewide wind-generated electricity supply to the grid. We then quantify changes in the time scales of CF variability and the seasonality. Currently, wind-generated electricity is lowest in summer in each region except SWC, which causes a substantial mismatch with electricity demand. While electricity of residential heating may shift demand, research presented here suggests that summertime CF are likely to decline, potentially exacerbating the offset between seasonal peak power production and current load. The reduction in summertime CF is manifest for all regions except the SGP and appears to be linked to a reduction in synoptic-scale variability. Using fulfillment of 50% and 90% of annual energy production to quantify interannual variability, it is shown that wind power production exhibits higher (earlier fulfillment) or lower (later fulfillment) production for periods of over 10–30 years as a result of the action of internal climate modes. Significance Statement Electrical power system reassessment and redesign may be needed to aid efficient increased use of variable renewables in the generation of electricity. Currently wind-generated electricity in many regions of North America exhibits a minimum in summertime and hence is not well synchronized with electricity demand, which tends to be maximized in summer. Future projections indicate evidence of reductions in wind power during summer that would amplify this offset. However, electrification of heating may lead to increased wintertime demand, which would lead to greater synchronization.

The impact of 100% electrification of domestic heat in Great Britain

The impact of 100% electrification of domestic heat in Great Britain

Towards BitCO2, an individual consumption-based carbon emission reduction mechanism

Human activities, such as burning fossil fuels for electricity generation, heating, and transport, are the primary drivers of a large amount of greenhouse gases emission. The individual consumers, able to influence the supply-chains behind the commodities their chose to fulfil their needs is the driver behind production and, consequently, its impacts. Thus, the active and willing participation of citizens in combatting climate change may be pivotal to address this issue. The present work is aimed at presenting and modelling a novel market-based carbon emission reduction mechanism, called BitCO2, designed to incentivize individual consumption choices toward lower carbon footprints. This mechanism is tested for the Italian private transportation sector thanks to an ad hoc developed System Dynamics model. The Battery Electric Vehicle (BEV) adoption, if compared with the Internal Combustion Engine Vehicle (ICEV) one, cause less CO2 emissions per km travelled. After a certain number of travelled km, a BitCO2 token is assigned to BEV owners for each ton of avoided CO2. This token can be exchanged in a dedicated market and used to get a discount on insurance services. Assuming a Social Cost of Carbon of 9.22 [2.13–22.3] €/tonCO2eq, model results show that the BitCO2 mechanism would allow for a cumulated CO2 emission reduction of 973 [68.9–5’230] ktonCO2eq over 20 years of operation with a peak of 39.3 [5.34–189] thousand additional BEV registration per year.

Performance investigation on a concentrating photovoltaic thermal system integrated with spectral splitter and absorption heat pump

To alleviate the energy consumption crisis and environmental pollutant problems, a concentrating photovoltaic thermal system integrated with spectral splitter and absorption heat pump is proposed. Through solar spectral splitting, the photo-electric and photo-thermal processes are decoupled, which facilitates the cogeneration of electricity and high-temperature heat. Through absorption heat pump, the temperature of geothermal energy is improved by high-temperature solar heat for subsequent utilization. Thus, the efficient utilization of full spectrum solar energy is achieved. To further evaluate the performances, an electric-thermal coupled model is developed and the comprehensive analysis is carried out from energy, exergy and exergoeconomic viewpoints. Results indicate that for an optical window of 400–1300 nm, strong LiBr/H2O solution concentration of 64 %, concentration difference of 5 % and thermal receiver temperature of 438.15 K, the overall energy and exergy efficiency is obtained about 102.14 % and 37.49 %, respectively. Among all components, parabolic trough concentrator is the most inefficient component with energy losses of 123.86 MWh. Highest exergy destruction is observed in the solar cell, accounting for 67.51 % of the total destruction. Moreover, a total exergoeconomic factor of 79.94 % is obtained for the entire system indicating that 20.06 % of the total costs are related to exergy destruction.

Economic Dispatch of Integrated Electricity–Heat–Hydrogen System Considering Hydrogen Production by Water Electrolysis

Water electrolysis is a clean, non-polluting way of producing hydrogen that has seen rapid development in recent years. It offers the possibility of resolving the issue of excessive carbon emissions in conventional hydrogen production methods. In addition, waste heat recovery in hydrogen fuel cells can significantly increase the efficiency of energy use. Thus, to combine the electric power system, the hydrogen energy system, and the district heating system, this research suggests a novel optimal multi-energy complementary electricity–hydrogen–heat model. Rooftop photovoltaics, energy storage batteries, electric boilers, and hydrogen energy systems made up of hydrogen generation, hydrogen storage, and hydrogen fuel cells are all included in the suggested model. Furthermore, the electricity–hydrogen–heat system can be connected successfully using waste heat recovery in hydrogen fuel cells to create a coordinated supply of heat and power. In this work, the waste heat of hydrogen fuel cells is taken into account to increase the efficiency of energy use. To show the effectiveness of the suggested optimal multi-energy complementary model, many case studies have been conducted.

Proposal and analysis of a concentrating photovoltaic-driven system for combined production of electricity, hydrogen, and low-temperature refrigeration

A trigeneration system that uses concentrating photovoltaic (CPV) waste heat for low-temperature refrigeration and surplus electricity to power an electrolyzer for hydrogen synthesis is presented in this research to address the energy demands of a multi-unit building. Energy and exergy assessments evaluate system performance under various situations. The ANSYS-FLUENT and Engineering Equation Solver are used. To evaluate its energetic and exergetic performance, the system is studied at different direct normal irradiation (DNI), photovoltaic areas, and absorption chiller driving temperatures. At a constant DNI, increasing the coil diameter from 400 to 600 mm may raise channel water temperature by 3–5%. Ejector-absorption cycle driving temperature enhancement from 65 to 95 °C increased refrigeration capacity from 22 to 34 kW, hydrogen production from 0.76 to 2.8 kg/h, and power generation from 5.9 kW to 4.1 kW. By increasing the photovoltaics area from 78 to 126 m2 and using an absorption chiller and electrolyzer, system energy and exergy efficiencies increase by 23.47% and 8.02%, respectively, while CPV exergy efficiency decreases by 18.06%. The CPV destroys the most exergy in the system, whereas the electrolyzer destroys the least. Combining photovoltaics and the refrigeration machine with an electrolyzer is a novel approach to harnessing sunshine energy.

Heat pump integration in non-continuous industrial processes by Dynamic Pinch Analysis Targeting

A key strategy for the transition towards a low-carbon economy is the electrification of industrial heat. Heat pumps can recover and upgrade excess or waste heat. They present a highly efficient component to decarbonize process heating. In Pinch Analysis, most approaches to design the heat recovery system as well as the utility system are based on a single operating point or a couple of operating point. In the past, this was due to the lack of temporally detailed process data. However, the available process data is expected to increase drastically by the use of transient process simulation models. Thus, a method is needed which interprets the data correctly and assists with design choices.This study proposes a methodology for the design and sizing of a heat pump based on the simulated annual process data of an industrial process. Three approaches are explored: (1) the conventional approach for heat pump integration by application of the Time Average Model (TAM), (2) an approach that investigates the optimal heat pump parameters for each data point by the principles of Pinch Analysis and mathematical optimization and (3) an optimization method, which considers the entire annual process data as well as thermo-economic objectives such as net present value (NPV) and internal rate of return (IRR).The new methodology compared to the conventional TAM approach is able to design a 33 % smaller heat pump, which reduces the annual operating cost by an additional 2.2 %. The NPV and IRR are more than tripled.

Ukraine`s Bioenergy Sector: Trends and Perspectives for the Post-war Green Energy Transition

The paper investigates trends in bioenergy development in Ukraine and its role in accelerating the green energy transition in the post-war period. The focus of the article is on the use of bioenergy resources for electricity generation, heat energy and liquid biofuel production. In this context, the potential of biomass, state support mechanisms, the results of their influence on bioenergy capacities deployment and the barriers restraining this sector development are considered. The study’s results proved that the inconsistency of the state policy and the failure to consider the specifics of energy production based on various bioenergy resources caused a significant lag in its development compared to other renewable energy technologies. With this in mind, the article systematizes strengths and weaknesses, opportunities and threats, and based on them, strategic recommendations for bioenergy development in Ukraine in the post-war period are developed.

Coordinated scheduling of electricity–heat–gas integrated energy system considering emerging energy conversion technologies

Couplings between electricity, heat, and natural gas system are deepening due to the requirement of a new energy paradigm and the development and commercialization of emerging energy conversion technologies such as heat pump (HP) and power-to-gas (P2G). In this context, this paper proposed a coordinated scheduling model for a heat–gas–electricity integrated system with compound emerging energy conversion technologies. First, new emerging/growing energy conversion technologies are reviewed and their models are discussed. Secondly, a coordinated scheduling model of the heat–gas–electricity integrated system is proposed with respect to their characteristics and interactions. Finally, an integrated electricity–gas–heat distributed energy system is employed to validate the proposed model. The utilization efficiency and installation suggestion are discussed as well.

Characterizing sector-wide thermal energy profiles for industrial sectors

Process heat electrification, energy efficiency improvement, and renewable technology integration are the most effective ways of achieving industrial decarbonization. However, precise knowledge of thermal energy demands and excess heat sources along with the corresponding temperature levels is imperative for the most optimum integration of aforementioned process. The current study presents a novel methodology for constructing sector-wide composite curves to accurately characterize the thermal energy demands and the available excess heat sources for the Swiss industry subsectors. The sector-wide energy demand profiles derived from this methodology offer valuable insights into the quantity of heat demand and the quality of the available excess heat. Thus, enabling the implementation of energy efficiency and decarbonization technologies such as heat pumps, and renewable heating and cooling technologies. The sector-wide energy demand profiles are built using Pinch Analyses and top-down statistical approach, thus ensuring complete sectoral coverage. The application of this novel approach is demonstrated using Swiss meat and chocolate industry subsectors as case studies. Based on the sector-wide energy demand profiles developed for meat and chocolate production, heat pump integration and solar thermal integration can potentially reduce about 80% of process heat demand, for both sectors.

Carbon capture from combined heat and power plants – Impact on the supply and cost of electricity and district heating in cities

The capture and storage of biogenic CO2 emissions from large point sources, such as biomass-combusting combined heat and power (CHP) plants, can contribute to climate change mitigation and provide carbon-negative electricity while supplying district heating in urban areas. This work investigates the impact of retrofitting CO2 capture processes to CHP plants in a city energy system context. An energy system optimization model is applied to a case study of the city Västerås, Sweden, with scenarios involving two existing CHP plants in the city, retrofitted with either a heat-driven (MEA) or an electricity-driven (HPC) carbon capture process. The results show that the CHP plants might be retrofitted with either option without significantly impacting the district heating system operation or the marginal costs of electricity and district heating in the city. The MEA process mainly causes a reduction in district heating output (up to 30% decrease on an annual basis), which can be offset by heat recovery from the capture unit. The electrified HPC process does not impact the CHP plant steam cycle but implies increased import of electricity to the city (up to 44% increase annually) compared to a reference scenario.

The Optimal Energy Flow Strategy of Integrated Energy System Considering Demand Response

Building an integrated energy system with source-load coordination and flexible interaction in the context of dual carbon is an effective path to building a new type of power system. The efficient operation of the integrated energy system can be promoted by establishing incentives such as energy subsidies to reasonably regulate the demand response on the customer side. In this paper, we consider the multi-source demand response on the customer side and study the optimal energy strategy from the perspective of the Integrated Energy Service Company (IESC), specifically involving the construction of the system electricity demand response and heat demand response models. And we propose an IESC optimal energy flow considering the customer’s demand and supply balance game to optimize the IESC. The optimal energy flow strategy of IESC considering the demand response of users is proposed. Finally, the correctness and rationality of the model are verified by simulation analysis.

An Agent-Based Decision Support Framework for a Prospective Analysis of Transport and Heat Electrification in Urban Areas

One of the main pathways that cities are taking to reduce greenhouse gas emissions is the decarbonisation of the electricity supply in conjunction with the electrification of transport and heat services. Estimating these future electricity demands, greatly influenced by end-users’ behaviour, is key for planning energy systems. In this context, support tools can help decision-makers assess different scenarios and interventions during the design of new planning guidelines, policies, and operational procedures. This paper presents a novel bottom-up decision support framework using an agent-based modelling and simulation approach to evaluate, in an integrated way, transport and heat electrification scenarios in urban areas. In this work, an open-source tool named SmartCityModel is introduced, where agents represent energy users with diverse sociodemographic and technical attributes. Based on agents’ behavioural rules and daily activities, vehicle trips and building occupancy patterns are generated together with electric vehicle charging and building heating demands. A representative case study set in London, UK, is shown in detail, and a summary of more than ten other case studies is presented to highlight the flexibility of the framework to generate high-resolution spatiotemporal energy demand profiles in urban areas, supporting decision-makers in planning low-carbon and sustainable cities.