Electricity Heat Research Articles

Waste-to-Energy Processes as a Municipality-Level Waste Management Strategy: A Case Study of Kočevje, Slovenia

The escalating challenge of waste management demands innovative strategies to mitigate environmental impacts and harness valuable resources. This study investigates waste-to-energy (WtE) technologies for municipal waste management in Kočevje, Slovenia. An analysis of available waste streams reveals substantial energy potential from mixed municipal waste, biodegradable waste, and livestock manure. Various WtE technologies, including incineration, pyrolysis, gasification, and anaerobic digestion, are compared. The results show that processing mixed municipal waste using thermochemical processes could annually yield up to 0.98 GWh of electricity, and, separately, 3.22 GWh of useable waste heat for district heating or industrial applications. Furthermore, by treating 90% of the biodegradable waste, up to 1.31 GWh of electricity and 1.76 GWh of usable waste heat could be generated annually from biodegradable municipal waste and livestock manure using anaerobic digestion and biogas combustion in a combined heat and power facility. Gasification coupled with a gas-turbine-based combined heat and power cycle is suggested as optimal. Integration of WtE technologies could yield 2.29 GWh of electricity and 3.55 GWh of useable waste heat annually, representing an annual exergy yield of 2.98 GWh. Within the Kočevje municipality, this amount of energy could cover 23.6% of the annual household electricity needs and cover the annual space and water heating requirements of 10.0% of households with district heating. Additionally, CO2-eq. emissions could be reduced by up to 20%, while further offsetting emissions associated with electricity and district heat generation by 1907 tons annually. These findings highlight the potential of WtE technologies to enhance municipal self-sustainability and reduce landfill waste.

Optimal scheduling of a cogeneration system via Q-learning-based memetic algorithm considering demand-side response

An optimization scheduling method for cogeneration systems based on the Q-learning-based memetic algorithm (QMA) is developed to enhance the system's wind power absorption capacity and economical operation. First, an optimal scheduling model for cogeneration systems is constructed. The model integrates time-of-use electricity pricing and heating comfort into the demand side, fully exploiting the potential of demand-side response (DR) in power generation and heating. An additional heat source (AHS), which consists of an electric boiler and heat storage tank, is used to uncouple heat and power. In addition, a QMA algorithm is designed to find the optimal operating scheme for the cogeneration system. The Q-learning algorithm is introduced to dynamically adjust crossover and mutation parameters during the global evolution stage, improving the algorithm's search capability. The Taguchi method is utilized for algorithm parameter calibration. Finally, the simulation results under various operating scenarios are compared and analyzed, verifying the feasibility and effectiveness of the proposed method. The simulation results show that DR and AHS can improve the system's economic performance and wind power utilization rate. Compared with the IMA, IPSO, MA, and IABC algorithms, the QMA algorithm reduces the average economic cost by approximately 1.18 %, 2.23 %, 5.69 %, and 14.69 %, respectively.

Multi-distributed resource coordination based on GAMS (general algebraic modeling system)

To achieve the economic operation of distributed energy resources in the grid, a GAMS-based multi-distributed resource optimization and control method is proposed. Firstly, considering the coexistence of electricity load and heat load in the grid system, a virtual power plant structure involving heat generation from distributed energy is established. Secondly, the General Algebraic Modeling System (GAMS) is utilized to create a detailed mathematical model for the distributed resources within the virtual grid. Subsequently, considering the influence of various uncertain factors, the CLPEX solver is employed for optimization and solution. Research results indicate that during the operation of the virtual power plant, the introduction of system heat load significantly enhances the expected profit and improves the economic efficiency of the operation.

Techno-Economic Analysis of Heat-Assisted Hydrogen Production from Nuclear Power

To play a full role in decarbonisation, hydrogen must be produced economically at scale; the role of nuclear power is interesting to national governments as it is capable of supplying both low-carbon electricity and high-quality heat. Depending on the hydrogen production technology choice, a plant may require electricity and/or heat input. This techno-economic evaluation considers not only the costs of the hydrogen plant itself but also the costs of the power supply it requires. This paper calculates cost estimates for HTSE (High Temperature Steam Electrolysis) coupled with nuclear heat and electricity, and a thermochemical SI (Sulphur Iodine) cycle coupled with nuclear heat, based on the predictions of technical process models. These estimates are then compared to estimates made elsewhere for the costs of using wind with low temperature liquid water electrolysis, and steam methane reformation with carbon capture. This analysis led to the identification of the conditions under which nuclear-heat-coupled hydrogen production would be competitively priced. Estimates for nuclear-coupled LCOH2 (levelised cost of hydrogen) in 2050 range from 2.14 to 1.24 £/kg for HTSE, and from 2.88 to 0.89 £/kg for the SI cycle. There is still a great deal of uncertainty around the efficiency of SI and how it may improve over time, and this limits the accuracy to which the LCOH2 can be predicted.

Assessment of CO2 abatement potential of heat pumps using pinch analysis for the Swiss chocolate industry

Decarbonizing industrial processes is crucial for achieving net-zero targets, with process heat electrification emerging as a key pathway. Heat pumps (HPs) are pivotal for this transition. This study introduces a novel methodology to construct exemplar profiles for specific energy demands, representative profiles for various production capacities, and energy demand profiles at product, subsector, or sector levels, using Swiss chocolate production as a case study. Exemplar profiles offer flexibility in generating representative profiles based on production capacities, aiding in identifying integration opportunities and sizes for HPs. Sector-wide profiles provide a broader perspective, aiding in visualizing bottom-up sector-wide potential for HPs. Based on the analysis of four representative profiles for Swiss chocolate production, two potential standard heat pump (SHP) and three high-temperature heat pump (HTHP) integration opportunities were identified. Techno-economic data from 30 commercially available HPs were collected, assessing their cost-effectiveness for Swiss chocolate manufacturing using the levelized cost of saved energy and CO2 abatement. Factors such as company size and electricity and natural gas prices impact the cost-effectiveness of HP integration. Despite variations, HPs with real coefficients of performance above 2.6 generally prove cost-effective for average energy prices and current CO2 levies in Swiss chocolate production. Bottom-up estimations of HP integration potentials using product-specific energy demand profiles suggest a potential reduction of CO2 emissions by up to 56% and an improvement in energy efficiency by up to 28% in Swiss chocolate production.

Energy big data abnormal cluster detection method based on redundant convolution codec

Due to the scattered distribution and poor clustering of abnormal clusters in energy big data, the ability to detect anomalies is poor. Therefore, a high-energy data anomaly clustering detection method based on redundant convolutional encoding is proposed. Quantitative analysis of the coupling characteristics of electrical thermal gas optical time series for multi energy users based on Copula function, and incorporating quantitative values into multi energy feature indicators to extract the energy consumption behavior characteristics of multi energy users. Utilize redundant convolutional codecs to recombine and structurally encode abnormal features of energy big data, and capture multi energy coupling time features using coupling time capsule layers. Then, coupling time features are synthesized through fully connected linear regression layers to generate anomalous clustering feature components, and the energy time series data is then transformed into feature values of the time series in three-dimensional space. Based on this, a comprehensive energy system and massive multi energy user energy big data anomaly clustering analysis are carried out to determine the optimal number of multi energy users. Then, based on linear layers, the electricity heat gas light load characteristic map of multi energy users is transformed into one-dimensional form, and an energy big data anomaly clustering detection model is constructed to complete anomaly detection. The simulation results show that the proposed method has excellent feature clustering performance, detection accuracy above 98.7%, fast convergence speed, and an error rate below 0.1, which has reliable application value.

Dynamic Management of Flexibility in Distribution Networks through Sensitivity Coefficients

Due to a rising share of renewable energy sources on the production side and electrification of transport and heating on the consumption side, the efficient management of flexibility in distribution networks is crucial for ensuring optimal operation and utilization of resources. Nowadays, the sensitivity-based approach is mainly used in medium-voltage (MV) networks for regulating voltage profiles with reactive power of distributed energy resources (DER). The main disadvantage of the simplified sensitivity-based method is its inaccuracy in case of a high deviation of the network voltage from the nominal values. Furthermore, it was also noted that despite the fact that the method is well described in the literature, there is a lack of systematic approach to its implementation in real-life applications. Thus, the main objective of this paper is to address this disadvantage and to propose an algorithm designed to calculate required consumer flexibility in near real-time to ensure distribution grid operation within operational criteria. In the first part of the paper, network state, including line loading and node voltages, is assessed to determine distribution network node capacity. By analyzing the sensitivity of network busbars to changes in consumption and production, our algorithm effectively identifies the most efficient nodes and facilitates strategic decision-making for resource allocation. We demonstrate the effectiveness of our approach through simulations of real-world distribution network data, highlighting its ability to enhance network flexibility and improve resource utilization. Leveraging sensitivity coefficients, the algorithm enables flexible consumption and production management across various scenarios, supporting the transition to a more dynamic and efficient power system.

Thermodynamic investigation of a Carnot battery based multi-energy system with cascaded latent thermal (heat and cold) energy stores

Carnot batteries store electricity in thermal form, allowing for power balancing and also multi-vector energy management as a unique asset. Cascaded thermal energy storage therefore has a vital role in Carnot battery, particularly multi-energy systems delivering electricity and thermal energy at various temperatures. Here, we propose a Carnot battery multi-energy system with cascaded latent thermal energy stores. The effects of compressor pressure ratio, total stage number, stage area and fluid velocity in tubes, on system-level coefficient of performance and total exergy efficiency are investigated. The results show that both the coefficient of performance and exergy efficiency increase significantly and then level off with the total stage number and stage area increasing, while they only increase slightly before a significant decrease with the increase of fluid velocity in tubes. The selection of compressor pressure ratios relates to the demands of cold, heat and electricity. The multi-energy system achieves a maximum coefficient of performance of 95.0% in combined cooling, heating and power mode. Although the thermodynamic performance yileds comparable with Carnot battery systems integrated with packed-bed or liquid-based sensible heat stores, the Carnot battery multi-energy system can deliver electricity and multi-grade heat and cold simultaneously, thus increasing flexibility in future energy systems.

Life cycle assessment and life cycle costing approach for building decarbonization by design choices: A case study

AbstractDecarbonizing the urban environment has two significant challenges: Increasing electricity demand due to the electrification of space heating and increased renewables share in the electricity supply. The European Commission defines a new grid support mechanism for peak‐shaving products in renewed Electricity Market Design. This aims to enable a new market tool to stabilize electric supply and demand. This study examines a grid‐integrated thermal storage device's technical feasibility and economic performance to meet net zero building (nZEB) definitions. Alternative scenarios considering current national nZEB targets, present energy market options, and regulations are compared using the life cycle cost and the global warming potentials over the building lifetime. The results show that better building performance is possible even with a low investment increase of 6.7% compared to minimum building standards based on regulations. This enables older building cases to perform similarly with new building targets for Turkish National nZEB. Building electrification using heat pumps and thermal storage systems gives similar economic performances in the long term when a dynamic electricity tariff is available. Adapting the life cycle approach to decision‐making in construction contracts can lead to a 50% decrease in building emissions while staying within the same construction budget.

Optimal operation of multiple energy system considering load management approach and uncertainty

In recent years, the advancement of technology has led to the development of energy networks' infrastructure, resulting in the transformation of conventional networks into smart networks. By incorporating communication equipment, each component of the network can now exchange information with other components, creating an environment where innovative ideas can be implemented. One such idea is the utilization of multi-carrier energy systems, also known as Energy Hubs. Integrating energy hubs into traditional networks used to be a challenging task. However, with the expansion and enhancement of smart networks, the potential for incorporating and locating energy hubs within the power grid has significantly increased. In these systems, the focus shifts from optimizing a single energy carrier to ensuring the optimal operation of a system that encompasses multiple energy carriers, such as natural gas, electric grid, and thermal energy. Energy hubs act as intermediaries between energy supply companies and various consumers, including residential, commercial, and industrial sectors. These energy suppliers can encompass different energy networks, such as electricity, gas, and local heating. The integration of residential and commercial energy hubs has become a crucial aspect of modern energy systems, particularly in the context of load response applications. This paper proposes a novel approach for effectively utilizing residential and commercial energy hubs, taking into account the time of use (ToU) load response program. In the proposed system, the inherent uncertainties of the system are addressed using the two-point estimation method of the model. To achieve the desired objective, the Cuckoo optimization algorithm, a well-established meta-heuristic algorithm for solving optimization problems, is employed. This algorithm aids in determining the optimal scheduling of energy resources while considering ToU tariffs and load management plan signals. The results demonstrate that the proposed approach can significantly reduce energy costs for the energy system.

Symbolic Aggregate Approximation-Based Clustering of Monthly Natural Gas Consumption

Natural gas is an indispensable non-renewable energy source for many countries. It is used in many different areas such as heating and kitchen appliances in homes, and heat treatment and electricity generation in industry. Natural gas is an essential component of the transportation sector, providing a cleaner alternative to traditional fuels in vehicles and fleets. Moreover, natural gas plays a vital role in boosting energy efficiency through the development of combined heat and power systems. These systems produce electricity and useful heat concurrently. As nations move towards more sustainable energy solutions, natural gas has gained prominence as a transitional fuel. This is due to its lower carbon emissions when compared to coal and oil, thus making it an essential component of the global energy framework. In this study, monthly natural gas consumption data of 28 different European countries between 2014 and 2022 are used. Symbolic Aggregate Approximation method is used to analyse the data. Analyses are made with different numbers of segments and numbers of alphabet sizes, and alphabet vectors of each country are created. These letter vectors are used in hierarchical clustering and dendrogram graphs are created. Furthermore, the elbow method is used to determine the appropriate number of clusters. Clusters of countries are created according to the determined number of clusters. In addition, it is interpreted according to the consumption trends of the countries in the determined clusters.

Sodium acetate-based thermochemical energy storage with low charging temperature and enhanced power density

The electrification of heat necessitates the development of innovative domestic heat batteries to effectively balance energy demand with renewable power supply. Thermochemical heat storage systems show great promise in supporting the electrification of heating, thanks to their high thermal energy storage density and minimal thermal losses. Among these systems, salt hydrate-based thermochemical systems are particularly appealing. However, they do suffer from slow hydration kinetics in the presence of steam, which limits the achievable power density. Additionally, their relatively high dehydration temperature hinders their application in supporting heating systems. Furthermore, there are still challenges regarding the appropriate thermodynamic, physical, kinetic, chemical, and economic requirements for implementing these systems in heating applications. This study analyzes a proposal for thermochemical energy storage based on the direct hydration of sodium acetate with liquid water. The proposed scheme satisfies numerous requirements for heating applications. By directly adding liquid water to the salt, an unprecedented power density of 5.96 W/g is achieved, nearly two orders of magnitude higher than previously reported for other salt-based systems that utilize steam. Albeit the reactivity drops as a consequence of deliquescence and particle aggregation, it has been shown that this deactivation can be effectively mitigated by incorporating 10 % silica, achieving lower but stable energy and power density values. Furthermore, unlike other salts studied previously, sodium acetate can be fully dehydrated at temperatures within the ideal range for electrified heating systems such as heat pumps (40 °C – 60 °C). The performance of the proposed scheme in terms of dehydration, hydration, and multicyclic behavior is determined through experimental analysis.

Year-round experimental analysis of a water-based PVT-PCM hybrid system: Comprehensive 4E assessments

In this year-long study conducted in Cairo, Egypt, an innovative water-based photovoltaic-thermal (PVT) system coupled with phase change material (PCM) was evaluated for its ability to enhance building energy efficiency. The system utilizes 22 copper capsules filled with RT35 paraffin wax and a water-cooling duct to ensure optimal electricity generation and heat storage. The proposed system underwent detailed 4E (energy, exergy, economic, and environmental) assessments to compare its performance against traditional uncooled PV panels. The results indicated significant improvements: a reduction in cell temperature by up to 8.3 °C, an increase in electrical efficiency by 4.0–13.3%, and a boost in power output by 4.1–15.9%. Overall, the system demonstrated efficiencies between 27.23 and 67.33%, along with an exergy efficiency peak at 74.64% in July, substantially outperforming the uncooled panel. Economically, the PVT-PCM system achieved a 1.58-year payback period, and carbon emissions were reduced by 32%, highlighting its viability and environmental benefits. The potential of the PVT-PCM system to advance sustainable building energy management was strengthened by this study, providing a significant step forward in integrating renewable energy within architectural designs.

The impact of electrification of heating on the power grid for a selected area microgrids

The impact of electrification of heating on the power grid for a selected area microgrids

Sensitivity analysis and thermodynamic evaluation of a combined cooling, heating and power system utilizing exhaust gases of smelting furnace

Exhaust gases from the smelting furnace have high temperature and mass flow rate, and there is huge potential to use them for energy-related purposes such as electricity generation, cooling and heating. Utilization of the gases for energy-related purposes would lead to fuel savings and emissions reduction. To use this potential, it is necessary to design proper systems and cycles and apply a heat recovery unit. Several technologies are useable for heat recovery depending on the characteristics of exhaust gases, such as their mass flow rate, temperature and compositions. Due to the higher potential of combined heating, cooling and power (CCHP) generation systems compared with the systems with a single output, a CCHP is designed and investigated in the present study by consideration of the specifications of the exhaust gases. The applied system in this study comprises a Supercritical CO2 (SCO2) cycle, heat exchanger and single-stage absorption chiller for simultaneous heating, cooling and power production. Engineering Equation Solver (EES) is employed to model the proposed system by considering the properties of the flows and characteristics of the components. To get deep insight into the effective parameters on the outputs of the designed system, the impact of three factors, namely the mass flow rate of the gases, the effectiveness of heat exchanger and temperature of exhaust gases, are analyzed and investigated by the implementation of sensitivity analysis. As one of the main conclusions, it is found that an increment in the mass flow rate of exhaust gases from 30 kg/s to 70 kg/s causes augmentation in the power generation from 2037 kW to 4754 kW. Furthermore, exergy analysis is carried out, and it is found that an increase in the temperature or mass flow rate of exhaust gases or a decrease in the effectiveness of heat exchangers would lead to decrement in the exergy efficiency of the system. According to the performed sensitivity analysis, the mass flow rate of exhaust gases has the most remarkable influence on the heating and cycle-generated power among the considered factors.

A small ammonia heat pump using linear compressor

The electrification of space heating and hot water via heat pumps is a widely pursued policy aim but field trials demonstrate poorer seasonal performance than anticipated. Linear compressors without crank mechanism can be oil-free. The potential for capacity modulation by adjusting the compressor stroke offers significant advantages over traditional methods including on-off control and variable frequency given that heat pumps operate at part load most of time. R717 (ammonia) has superior latent heat which offers a higher heating capacity compared to R134a, making it a very promising refrigerant for small heat pumps but there is no compatible compressor due to corrosivity. This paper introduces a novel small ammonia heat pump using an oil-free linear compressor technology that is compatible with R717. A numerical model was established to predict the heat pump baseline performance. The outcomes show a linear relation for specific power input, heating capacity, and Coefficient of Performance (COP) against ambient temperature. The system can achieve COP of 2 when ambient temperature is 0 °C. With linear compressor, there will be no on-off cycling for heat pumps so that the seasonal COP will be significantly higher than on-off control and variable frequency drive systems.

A pH-Sensitive Stretchable Zwitterionic Hydrogel with Bipolar Thermoelectricity.

Amid growing interest in using body heat for electricity in wearables, creating stretchable devices poses a major challenge. Herein, a hydrogel composed of two core constituents, namely the negatively-charged 2-acrylamido-2-methylpropanesulfonic acid and the zwitterionic (ZI) sulfobetaine acrylamide, is engineered into a double-network hydrogel. This results in a significant enhancement in mechanical properties, with tensile stress and strain of up to 470.3kPa and 106.6%, respectively. Moreover, the ZI nature of the polymer enables the fabrication of a device with polar thermoelectric properties by modulating the pH. Thus, the ionic Seebeck coefficient (Si) of the ZI hydrogel ranges from -32.6 to 31.7mV K-1 as the pH is varied from 1 to 14, giving substantial figure of merit (ZTi) values of 3.8 and 3.6, respectively. Moreover, a prototype stretchable ionic thermoelectric supercapacitor incorporating the ZI hydrogel exhibits notable power densities of 1.8 and 0.9mW m-2 at pH 1 and 14, respectively. Thus, the present work paves the way for the utilization of pH-sensitive, stretchable ZI hydrogels for thermoelectric applications, with a specific focus on harvesting low-grade waste heat within the temperature range of 25-40 °C.

A novel temporal mixed-integer market penetration model for cost-effective uptake of electric boilers in the UK chemical industry

The UK chemical industry is the largest consumer of natural gas for process heating and power generation, with an annual consumption of 26.3 TWh. Reduction in natural gas consumption and associated carbon emissions can be achieved through electrification of heat. However, the adoption of electric boilers is lethargic due to economic barriers. Hence, market-based policy interventions are required. This study aims to accelerate the adoption of electric boilers in the UK's chemical industry, aligning with the UK's ambitious 2035 industrial decarbonisation goals while considering economic impacts, by designing market-based policy interventions and comparing two adoption patterns. A novel multi-period Mixed-Integer Market Penetration Optimisation Model is developed and applied to inform decisions about transitioning from natural gas to electric boilers. The model is applied to a case study of all the heating systems (490 boilers) in the UK chemical industry from 1 MW to 60 MW boilers. Results show that effectively implementing a gas tax, electricity subsidy, annual grant and carbon tax can generate sufficient demand-pull to reduce the cost of electric boilers from 30 to 85 % depending on the boiler size. A carbon tax starting at £280 per tCO2e and reducing to £170 per tCO2e coupled with electricity subsidies is essential for this transition. The policies are designed such that a win-win is achieved between government and industry; specifically, revenue from the carbon tax and gas tax is used to support the grant and electricity subsidy thereby achieving cost neutrality for government. At 100 % uptake of electric boilers in 2033, the total carbon emissions reduce by 89 %, which is above the 2035 UK industry goal of 60 % reduction. The research establishes a robust policy timeline that can drive industrial electrification in the UK's chemical sector. It highlights the need for a multi-faceted approach, incorporating various policy instruments to overcome the barriers of high initial capital costs.

Integrated Gasification of Biomass Residues (IBGCC)

A comprehensive outline of a new approach in integrated gasification of biomass residues including the material flow management in urban areas being targeted on the generation of electricity and district heating is presented. The feedstock is derived from civilian material by fully automated collection, sorting and separation. Thereby an outward transfer of inerts is executed, such as minerals, metals, glass and electronic scrap as well as sorted plastics being object to recycling. Finally a ligno cellulosic and a non-lignocellulosic fraction are gained. The for mer one is suitable for thermochemical conversion, the latter one for biological conversion into fuel gases which subsequently are oxidised completely at low air excess in a horizontally arranged cyclone combustion chamber. The heat recovered from the flue gases in the utility boiler is used to generate steam scooping in the supply of electricity and district heating. The basic design is scaled to an overall thermal capacity of 2-5 MW. This type is most capable of utilising renewable energy by converting the organic fractions of civilian material flows. The power plant is based on a reliable technology representing an on-site integrated biomass gasification combined cycle system including peripheral units specified for the treatment of complementary materials.

Assessing the Flexibility Potential of Industrial Heat–Electricity Sector Coupling through High-Temperature Heat Pumps: The Case Study of Belgium

Thermal processes represent a significant fraction of industrial energy consumptions, and they rely mainly on fossil fuels. Thanks to technological innovation, highly efficient devices such as high-temperature heat pumps are becoming a promising solution for the electrification of industrial heat. These technologies allow for recovering waste heat sources and upgrading them at temperatures up to 200 °C. Moreover, the coupling of these devices with thermal storage units can unlock the flexibility potential deriving from the industrial sector electrification by means of Demand-Side Management strategies. The aim of this paper is to quantify the impact on the energy system due to the integration of industrial high-temperature heat pumps and thermal storage units by means of a detailed demand–supply model. To do that, the industrial heat demand is investigated through a set of thermal process archetypes. High-temperature heat pumps and thermal storage units for industrial use are included in the open-source unit commitment and optimal dispatch model Dispa-SET used for the representation of the energy system. The case study analyzed is Belgium, and the analysis is performed for different renewable penetration scenarios in 2040 and 2050. The results demonstrate the importance of a proper sizing of the heat pump and thermal storage capacity. Furthermore, it is obtained that the electrification of the thermal demand of industrial processes improves the environmental impact (84% reduction in CO2 emissions), but the positive effect of the energy flexibility provided by the heat pumps is appreciated only in the presence of a very high penetration of renewable energy sources.