Combined Heat And Power Plant Research Articles

Nearly-zero carbon optimal operation model of hybrid renewable power stations comprising multiple energy storage systems using the improved CSO algorithm

In light of the abundant renewable energy resources in Northwestern China, this study introduces a novel hybrid power plant structure known as the (Renewable energy-concentrating solar power-combined heat and power) RCC system. The RCC system integrates various energy sources, including the photovoltaic, the wind power plant, the concentrating solar power (CSP) plant, and the combined heat and power (CHP) plant. It also incorporates power-to-gas (P2G) technology to convert wind and solar power surpluses into methane. Moreover, carbon capture and storage (CCS) technology is applied to capture carbon dioxide emissions from the CHP plants, which serves as a raw material for the P2G process. To address the energy trilemma, we develop a nearly-zero carbon emission optimization model for the RCC system, considering different renewable energy source (RES) endowments. The fuzzy membership function method is employed to identify the optimum satisfaction target across multiple attributes. An enhanced CSO algorithm is introduced and validated using a simulation study on a CSP plant in Dunhuang. The results show that compared with traditional power stations, the proposed RCC system can reduce the investment cost by 34.45 %, increase the operating income by 17.7 %, and reduce carbon emission by 3.2 %. At the same time, the methane stock in the system increased by 53.7 % compared with the traditional power station containing P2G equipment, which helps the hybrid power station to participate in the methane market and obtain more profits. In addition, the direct energy supply ratio of RES decreased by 83.16 %, reducing the risk of the system caused by the uncertainty of RES. To sum up, the proposed RCC system has a good development prospect.

Формування навичок емоційної стійкості учасників освітнього процесу в умовах надзвичайних ситуацій

The article emphasizes that organizing the educational process during a state of war fosters collective hope for social change and improvements in life. It also alleviates people's fears of the future and the unknown, aiding educators and students in utilizing education as a tool for building a peaceful and just world in the future. The authors analyzed available informational resources in Ukraine and abroad concerning the development of emotional resilience skills among participants in the educational process amid emergencies. It's highlighted that despite a significant increase in natural disasters, technological catastrophes, social and military conflicts worldwide, issues related to organizing education in emergencies haven't become a priority in scientific research. In the context of ongoing and integrated manifestations of extraordinary situations—be it natural (COVID-19 pandemic), technological (power outages, lack of communication, accidents in heating stations, fires), social (cyberattacks, population evacuations, false alerts in institutions), or military (rocket attacks, drone strikes, territorial threats, etc.)—the Ukrainian education system strives to continue functioning. This demands considerable physical and, more importantly, psychological efforts from educational participants, given that they all work under constant stress. However, the problems related to organizing education in emergencies of a military nature have yet to find proper reflection in Ukrainian pedagogical science. One of the significant psychological factors for effective performance in emergency situations is emotional resilience, which reduces the negative impact of strong emotions, maintains readiness for action, and prevents severe stress. Therefore, the authors conclude that further scientific research on the emotional resilience of educational participants in situations of war, characterized by frequent occurrences of various emergencies, is crucial for Ukraine. Developing methodologies for fostering and enhancing emotional resilience skills is essential.

Techno-Economic Analysis of a Highly Renewable and Electrified District Heating Network Operating in the Balancing Markets

In pursuit of Finland’s carbon neutrality objective by 2035, integrating renewable energy sources into the power grid is essential. To address the stochastic nature of these resources, additional sources of flexibility are required to maintain grid stability. Meanwhile, district heating network (DHN) operators in Finland are decommissioning fossil fuel-based combined heat and power plants (CHPs) and electrifying heating systems with heat pumps (HPs) and electric boilers. A techno-economic assessment and the optimized operation of DHN-connected HPs and electric boilers in providing ancillary balancing services were explored in this study. The primary goal was to maximize the potential revenue for DHN operators through participation in the day-ahead electricity market and frequency containment reserve (FCR) balancing markets. Three interconnected DHNs in the Helsinki metropolitan area were optimized based on 2019 data and each operator’s decarbonization strategies for 2025. HPs are expected to achieve the highest profit margins in the FCR-D up-regulation market, while electric boilers could generate substantial profits from the FCR-D down-regulation market. In contrast to other balancing markets studied, the FCR-N market exhibited limited profit potential. Sensitivity analysis indicated that spot electricity prices and CO2 emission allowance prices significantly influence the profitability derived from balancing markets.

Battery–integrated combined cooling, heating and power plant (CCHP) through NH3 – H2O absorption system in a hospital facility

Combined heat and power (CHP) systems have been employed in various applications for years. They are gaining increasing attention in the residential and small industrial sectors for their primary energy saving potential and CO 2 emissions reduction. Additionally, in specific applications such as the hospital sector, CHP plants can play a critical role in replacing fossil-fueled electric generators to supply electricity during local grid outages, thus enhancing hospital facilities’ energy efficiency, while also securing reliability and efficiency of operation. Hospitals have unique energy demand profiles, with high and constant demand (particularly heating and cooling demands), making them an ideal use-case for trigeneration systems. Combined, cooling, heating and power plants (CCHP) are capable to provide not only heating and electricity, but also cooling through the efficient exploitation of a single energy source, reducing Hospitals’ reliance on the local grid. In this context, this work aims at evaluating the potential of a battery-integrated CCHP plant through an innovative ammonia-water absorption system, whose energy analysis is based on data acquired from an Italian Hospital facility. The potential of integrating an experimental combined cooling and power production ammonia-water absorption system has been investigated starting from an optimized battery energy storage system (BESS) CHP plant configuration, studied for the same facility. A proper control strategy has been developed to maximize the cooling production when required from the end-user through CHP plant’s exhaust gases waste heat recovery. The energy analysis demonstrated the advantages of the CCHP-BESS plant over the optimal CHP-BESS configuration, with an 11.22% increase in primary energy saving, a 9.85% reduction in CO 2 emissions, and a 5.03% decrease in electric peak power demand.

Quantification of cogeneration vulnerability towards the climate change: framework development

Cogeneration is a vigorous measure to both decrease greenhouse gases emissions and improve an overall efficiency of the primary energy use. The climate change poses serious risks on operation of combined heat and power (CHP) plants due to the shifts in heating load patterns. This work investigates linking of the heating demand to the climate conditions and introduces a framework which can be used to develop an adaptation strategy for district heating systems. We demonstrate viability of the proposed approach by a case study assessing sensitivity of the CHP efficiency to the climate warming across China considering a modern combined-cycle gas-fired power plant with steam extraction. Outputs of the case study have demonstrated that CHP plants are generally more vulnerable towards the climate change in world regions with harsher climate conditions. An effective measure to increase resilience of the cogeneration sector is to account for anticipated climate change effects by applying adjustments to the reference climate inputs used when designing CHP plants.

Characterization and modification of biochar from a combined heat and power (CHP) plant for amending sandy soils collected from wild blueberry fields

Wild (or lowbush) blueberries (Vaccinium angustifolium Ait.) undergo severe drought impacts due to climate warming because they grow in sandy soils with poor water retention. The feasibility was studied for using biochar in a forest biomass-fueled combined heat and power (CHP) plant to amend the sandy soils. The chemico-physical properties (e.g., bulk density, moisture content, porosity, pH) of the biochar were measured. An acid treatment method (1% to 3% acidic or citric acid solution) was developed to decrease the biochar pH from 11.4 to neutral or lower, aiming to aid in weed control in wild blueberry fields. The water holding capacity (WHC) of sandy soils (S) mixed with biochar (B) (Type I) and sandy soils mixed with both biochar and fertilizer (Type II) at four ratios of 100S:0B (control), 50S:50B, 30S:70B, and 10S:90B were measured. The biochar generated from the CHP plant had comparable physical properties (such as bulk density, porosity, pH, and surface area) with woody biochar made from pyrolysis. The acid treatment method significantly lowered the pH to a range of 5.0 to 6.5. The 50:50 mixing ratio for both Type I and Type II increased the water holding capacity by about 20% compared with control groups.

Selecting the approach for dynamic modelling of CO2 capture in biomass/waste fired CHP plants

Integrating CO2 capture with biomass/waste fired combined heat and power (CHP) plants is a promising method to achieve negative emissions. However, the use of versatile biomass/waste and the dynamic operation of CHP plants result in bigger fluctuations in the properties of flue gas (FG), e.g. CO2 concentration (CO2vol%) and flowrates, and the heat that can be used for CO2 capture, when comparing with coal fired power plants. To address such a challenge, dynamic modelling is essential to accurately estimate the amount of captured CO2 and optimize the operation of CO2 capture. This paper compares three dynamic approaches commonly used in literature, namely using the ideal static model (IST) and using dynamic models without control (Dw/oC) and with control (DwC), for MEA based chemical absorption CO2 capture. The performance of approaches is assessed under the variations of key factors, including the flowrate and CO2vol% of FG, and the available heat for CO2 capture. Simulation results show clear differences. For example, when the CO2vol% drops from 15.7 % to 9.7 % (about 38 %) within 4 hours, DwC gives the highest amount of captured CO2, which is 7.3 % and 22.3 % higher than IST and Dw/oC, respectively. It is also found that the time step size has a clear impact on the CO2 capture amount, especially for DwC. Based on the results, suggestions are also provided regarding the selection of dynamic modelling approaches for different purposes of simulations.

Assessing the CO2 capture potential for waste-fired CHP plants

The integration of CO2 capture with biomass-fired power plants has attracted much attention due to its ability to achieve negative emissions. Waste-fired combined heat and power (CHP) plants with CO2 capture, on the other hand, has received little attention, and their potential remains unclear. This study aims to identify the possible range of the amount of captured CO2 and investigate the impact of CO2 capture on the performance of waste-fired CHP plants. Since heat is the primary product of CHP plants, it is important to maintain heat production unchanged when CO2 capture is integrated. Based on this prerequisite, two operating strategies (OS) were investigated, which correspond to the upper and lower boundaries of CO2 capture: OS1 was to maximize the amount of captured CO2 while keeping the heat supplied to the district heating (DH) network unchanged; and OS2 was to maximize CO2 capture while keeping both supplied heat and generated electricity unchanged. To obtain more accurate results regarding the CO2 capture, a dynamic model developed in Aspen Hysys™ was utilized to simulate monoethanolamine (MEA) based chemical absorption for CO2 capture. By using real dynamic data from a waste-fired CHP plant, dynamic simulation results showed that the highest amount of captured CO2, which was achieved in OS1, was 401 kton/year, corresponding to a CO2 capture ratio of 82%; while the lowest amount of captured CO2, which was achieved in OS2, was 99 kton/year, corresponding to a CO2 capture ratio of 20%. For OS1, the electricity generation was substantially decreased by 61%. When determining the negative emission, the emission resulted from the share of fossil fuel in the waste needs to be excluded. For the studied CHP plant, the fossil share was around 45%. As a result, only OS1 can achieve the negative emission, which was 181 kton/year; while OS2 still led to positive emissions. Compared to the plant without CO2 capture, the carbon intensity of heat was reduced from 0.405 ton/MWh to 0.091 ton/MWh in OS1 and 0.351 ton/MWh in OS2, while the carbon intensity of electricity was reduced from 0.409 ton/MWh to 0.072 ton/MWh in OS1 and 0.343 ton/MWh in OS2.

Assessing the Impact of Combined Heat and Power Plants (CHPPs) in Central Asia: A Case Study in Almaty for PM2.5 Simulations Using WRF-AERMOD and Ground Level Verification

According to the World Health Organization, Kazakhstan is one of the most polluted countries in the world. PM2.5, a major air pollutant, is six times higher than the recommended value of 5 mg/m3. The government has implemented measures to reduce air pollution, such as introducing green energy-powered buses for public transportation, but the results have not been sufficient. Therefore, it is necessary to investigate the sources of PM2.5. This study involved simulating the Combined Heat and Power Plants (CHPPs) emissions in Almaty using AERMOD and WRF for two weeks in January 2021. Two scenarios were performed: controlled and uncontrolled. The results showed that if the control mechanism of the CHPP functions at maximum efficiency, the impact of the CHPP emissions on the total emission concentration will be negligible, which is about 6% on average. However, for uncontrolled CHPPs, the emissions will contribute from 30% to 39% on average to the total PM2.5 concentration when compared with data from US Embassy monitoring stations and public air quality monitoring network, which use Pms5003 PM2.5 sensors.

Optimal Scheduling Framework of Integrated Energy System Based on Carbon Emission in Electricity Spot Market

Micro coal-fired units (MCFU) and combined heat and power plants (CHP) in integrated energy system (IES) will emit a large amount of carbon dioxide when providing loads to customers, which will lead to higher operating costs of IES. To solve this challenge, an optimal dispatch model of power-to-gas (P2G) and methane reactor (MR) considering the reward and punishment costs based on carbon emission trading mechanism is proposed, to reduce carbon emissions of IES and enhance the accommodation of renewable energy (RE). Subsequently, considering the uncertainty of RE, a combination optimization method for MCFU and CHP units is developed based on the Lagrange multiplier method. Finally, considering the mechanism of electricity spot market (ESM), a transaction strategy for IES participating in ESM is proposed to further enhance the accommodation of RE. The effectiveness of the proposed framework is demonstrated through simulations.

Optimal Configuration of Power-to-Heat Equipment Considering Peak-Shaving Ancillary Service Market

The serious problem of wind power curtailment in northern China has created a pressing need to enhance the peak-shaving ability of the power system. As the main source of power supply in northern China, combined heat and power (CHP) units have significant potential for peak-shaving. Currently, the Chinese government encourages CHP plants to increase their peak-shaving capacity by installing power-to-heat (P2H) equipment. In addition, the government has implemented auxiliary service market policies to encourage CHP plants to provide peak-shaving services. In order to maximize economic benefits for CHP plants, this paper proposes an optimal configuration method of P2H equipment with the static payback time (SPT) as the objective function. Cost and income models of installing the P2H equipment are constructed by taking into account the auxiliary service market policies. The peak-shaving income model of the CHP plant is derived emphatically as a key part of the proposed method. Finally, the district heating region in Jilin province is used as a case study example. The results show that adding the P2H equipment is significantly effective in improving the peak-shaving ability of CHP units, and investing in heat pumps is more cost-effective than electric boilers. The proposed method can be applied to other northern regions relying on CHP units for central heating, providing a valuable solution to the problem of wind power curtailment in these regions.

Optimal control of combined heat and power station operation

Combined heat and power stations have become one of the most utilized units of district heating systems. These stations usually contain several boilers for burning fossil fuels and renewable resources used for heating up steam, which can be used either for residential and commercial heating or electricity generation. To ensure efficiency, a boiler should either run continuously (for at least a given period) on a power output higher than a given threshold or switch off. The optimal control of the plant operations should combine an efficient setup for the turbine and boilers in operation, reflecting the demand for steam and the price of electricity, and a schedule that describes which boilers should be in operation at a given time. This paper proposes a method for optimal control of combined heat and power station operation for a given time horizon. The method is based on a two-level approach. The lower-level models correspond to finding the optimal setup of the combined heat and power station parameters for an hourly demand for different kinds of steam. The upper-level model corresponds to the optimal schedule of the operations of the individual boilers, which is planned for the entire time horizon. The lower-level model is modeled as a mixed-integer linear programming problem and is solved using parametric programming. A dynamic programming algorithm solves the upper-level model with a rolling horizon. The validity of the proposed method and its computational complexity for different granularity of the time horizon, different ranges of the parameters, varying demand for various kinds of steam, and varying electricity prices are investigated in a case study. The presented approach can be readily applied to other control problems with a similar structure.

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.

Design and Operation Optimization of a Nuclear Heat-Driven District Cooling System

Carbon-free thermally driven district cooling systems (DCS) can effectively mitigate the excessive electricity consumption and carbon emissions associated with the cooling sector. This study proposes a DCS that employs nuclear heat as the primary energy source. The system comprises three main subsystems: heat station, heat transmission, and cooling station. A heat-only small modular reactor called Teplator, gas boilers, and heat storage are considered to supply the heat required to drive absorption chillers; cold storage and compression chillers are the supplementary units. The technoeconomic aspects of the system are formulated, and an algorithm is developed to determine the optimal design and operation. The method is examined for supplying a typical cooling demand profile with a peak of 2050 MWc. The resulting optimized design includes 11 nuclear plants (150 MWt each), 20 000 MWth heat storage, and 1.9 m diameter heat supply/return pipes. Absorption chillers with a total capacity of 1424 MWc are determined, covering 92% of the total cooling demand, and 244 MWc of compression chillers and 20 000 MWch of cold storage are found to cover the peak and enhance the load following. This system saved 69% of the electricity consumption and carbon emissions and 34% of the costs compared with an electric-based scenario.

Thermoeconomic analysis and multiple parameter optimization of a combined heat and power plant based on molten salt heat storage

The global energy supply is transitioning to sustainable, low-carbon energy. Power-to-heat technology with molten salt thermal energy storage (TES) is a potential way to accommodate renewable power, and the stored heat can be converted to heat and electricity for residential heating and power supply with a combined heat and power plant (CHP). In this study, a CHP-TES system with valley electricity as the input energy source is proposed. Thermodynamic models are developed, and an economic evaluation index is established by considering electricity price, heat price, TES scale, and CHP layout. Then, multiparameter optimization of the proposed CHP-TES system is conducted with the genetic algorithm, and the energy-exergy-economic feasibilities of the system are evaluated. The CHP-TES system can operate under CHP and condensing modes in heating and non-heating periods, and its output power can be regulated during peak and valley load time, respectively. The exergy efficiency of the CHP-TES system is 45.07% and 36.67% in condensing modes with the peak and valley output power, respectively. The exergy efficiency of the CHP-TES system is 46.16% and 42.96% in CHP modes with the peak and valley output power, respectively. The exergy is mainly destructed in the electric heater, which accounts for over 65% of the total exergy loss in all operation modes. The equipment investment of the TES, steam generator, and CHP systems account for 87.59%, 3.53%, and 8.88% of the total, respectively. The electric heater takes the largest portion of the total equipment investment, which accounts for 37.99%. When the peak-valley electricity price changes from 0.121 $ kWh−1 to 0.259 $ kWh−1, the net present value increases from $592 million to $5.79 billion.

Design of district heating system with dual-temperature supply based on thermal energy discretisation and matching method

As heating requirements continue to evolve and heating technology advances, radiators and radiant floor heating devices, which require different supply-water temperatures, have gradually become the two main heating terminals in district heating systems. However, the primary return-water temperature of current solutions based on heat exchangers and heat pumps is relatively high and fails to recover waste heat from the combined heat and power plants, owing to improper use of heat sources. To address this issue, a heat exchanger network optimisation method—the thermal energy discretisation and matching method—was used to design a dual-temperature water district heating system consisting of two absorption heat pumps and two heat exchangers. The primary supply water flows through the two generators, two heat exchangers, and two evaporators of the absorption heat pumps. The radiator and floor heating return water was divided into two parts and heated by the heat exchanger and the absorber and condenser of the absorption heat pump, respectively. The performance of the designed heating station was evaluated using the coefficient of performance and the primary return-water temperature and compared with that of other district heating systems. The changes in the district heating system's configuration when the boundary conditions changed were investigated. Results showed that (1) the designed system based on thermal energy discretisation and matching method -had the lowest primary return-water temperature of 18.8 °C and the highest coefficient of performance of 5.62. (2) When the low-temperature load ratio changed from 0% to 100% while maintaining a constant total load, the system's form changed regularly. (3) When the primary supply-water temperature increased, the heating station's form remained unchanged and the capacity of the heat exchange equipment changed regularly. (4) When the secondary supply and return-water temperatures increased, the evaporation temperature of the absorption heat pump increased, resulting in a change in the system's form. This study provides valuable insight into the design of district heating systems that supply dual-temperature water under various design conditions.

A hierarchical classifying and two-step training strategy for detection and diagnosis of anormal temperature in district heating system

Anormal temperature data caused by various reasons such as sensor faults and operation faults, which has a negative influence on heat metering and operation regulation in district heating system (DHS). However, it is difficult to detect and diagnose anormal temperature among massive unlabeled operation data. Therefore, this paper proposes a novel hierarchical classifying and two-step training strategy to facilitate the anormal temperature detection and diagnosis task. Firstly, self-defined feature change rate of operation data like water temperature, flow rate, and valve opening are constructed as additional training features to capture the characteristics of anormal temperature conditions. Then, a hierarchical classifying method is proposed to detect anormal temperature data. Finally, a two-step training strategy which combines expert knowledge with support vector machine (SVM) to fulfill anormal temperature type diagnosis. The proposed strategy is applied to a typical DHS in cold region of China. A total of 10,920 anormal data are detected. Four anormal temperature conditions are diagnosed including offline sensor, inversely connected sensor, anormal operation of heat source, and shutdown of heat station. The diagnosis accuracy for the 4 kinds of anormal temperature conditions all reached over 98%.

Optimal scheduling method of air source heat pump heating station considering optimal power flow of distribution network

Participation of adjustable loads in demand response can alleviate power supply and demand challenges. As a typical adjustable load, this paper gives an optimal scheduling method considering optimal power flow in distribution networks of air source heat pumps, and studies adjustable load power allocation schemes for multiple distribution network nodes. The scheme with the goal of the lowest network loss determines the scheduling amount of the corresponding node heat supply stations to achieve optimal power flow dispatch, and the genetic algorithm is used to solve the model. Specific examples analysis shows that the proposed decision-making method can reasonably allocate power adjustments, prevent node voltage overruns in distribution networks, and reduce active power losses.

Conventional and advanced exergy and exergoeconomic analysis of a biomass gasification based SOFC/GT cogeneration system

In this paper, a small scale biomass gasification based solid oxide fuel cell/gas turbine (SOFC/GT) combined heat and power (CHP) plant is investigated by means of both conventional and advanced exergy and exergoeconomic analysis. A one-dimensional model of an internal reforming planner SOFC is employed to account for the temperature gradient within the fuel cell solid structure, which is maintained at the maximum allowable temperature gradient (150 K) under different operating conditions. Two main parameters of the gasification process, namely, air-to-steam ratio and modified equivalence ratio, are investigated, and the key parameters of the cycle exergy and exergoeconomic study are analyzed. Moreover, a multi-objective optimization procedure is applied to determine the unavoidable gasifier conditions required for the advanced exergy analysis of the system. The results of the conventional exergy and exergoeconomic analysis reveal that the highest rate of exergy destruction occurs in the gasifier, followed by the afterburner (AB) with 41.87% and 21.98%, respectively. Also, the lowest exergoeconomic factor is related to AB by 5.34%, followed by heat recovery steam generator (HRSG), gasifier, air compressor, and SOFC, which implies that the priority is to improve these components to reduce the exergy destruction cost rate. The results obtained from the advanced exergy and exergoeconomic analysis indicate that the most of the total exergy destruction rate is unavoidably in the CHP plant. The AB shows the least improvement potential in terms of reduction of the exergy destruction by almost 2% avoidable part, followed by Heat Exchanger 3 (H.X.3), gasifier, and SOFC duo to their lowest avoidable exergy destruction parts of almost 5%, 10% and 13%f respectively. Furthermore, the unavoidable part of the investment cost rate for all the components of the cogeneration plant is larger than the avoidable part, which means that it is difficult to reduce the investment cost rate of the system components. Meanwhile, the endogenous/exogenous analysis shows that the exergy destruction is completely endogenous for all components of the integrated plant, except for HRSG, GT, and HX1. Compressors and turbines have the highest potential to reduce endogenous exergy destruction. This is due to their higher avoidable endogenous exergy destruction. Reducing the investment cost rate seems difficult, as the main investment cost rate was found to be an unavoidable endogenous part for all system components. Finally, some results obtained from the advanced analysis approach are the opposite to those of the conventional method. This fact emphasizes that the results of conventional exergy analysis alone are insufficient and unreliable. For example, based on the advanced analysis perspective, the gas turbine and H.X.2 by 8.9% and 8.46% modified exergoeconomic factor, respectively, should be considered for reducing investment cost rate, while the conventional method gives opposite results.

Using flexible energy system interactions amongst industry, district heating, and the power sector to increase renewable energy penetration

Sweden’s goal of 100% renewable electricity generation by 2040 requires investments in intermittent electricity production (e.g. wind power). However, increasing the share of intermittent electricity production presents challenges, including reduced flexibility of electricity production. A strategy for overcoming this issue is developing flexibility in electricity consumption. This study analyses the potential for using flexible industrial processes, heat pumps (HP), and combined heat and power (CHP) plants in Swedish district heating systems to increase the share of wind power capacity without compromising grid stability. The simulation tool EnergyPLAN was used to assess the potential contribution of these strategies. The analysis includes a range of annual wind power production between 45 and 60 TWh. The required electricity imports and critical excess electricity (that can neither be used nor exported due to transmission line limitations) were used to evaluate the system’s stability. Managing the operation of CHP plants, HPs, and industrial processes in a flexible way is challenging, but these strategies may still play a decisive role in increasing the share of renewable electricity production and reducing demand peaks in cities. Whilst HP regulation is better at reducing excess electricity production at lower wind power capacities (from 32 to 15% for the analysed interval of wind power production), CHP regulation becomes more relevant when wind power capacity increases (from 14 to 39%). Like HP regulation, flexibility in electricity demand in industrial processes had a greater percentage contribution at lower wind power capacities. Combining HP, CHP regulation, and flexible electricity demands in industry can reduce excess electricity production by 68–80% and electricity imports by 14–26%. Wind power contributing to grid stabilisation reduces excess electricity production but does not reduce electricity imports.