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The P&P (pulp and paper) industry in Taiwan is highly energy intensive and there is much product diversification. Taiwan has extremely limited coal and petroleum resources and imports 98% of its energy supply. Increased energy utilization efficiency to reduce energy consumption is necessary for industry in order to implement energy audit recommendations. This work summarizes the energy-saving potential of 118 firms from 2009 to 2013 as determined by on-site energy audits, as well as the energy savings implemented in 2011 by 72 firms in Taiwan's P&P industry, according to data from the on-line Energy Declaration System. It is found that the total of the energy-saving potential and the implemented energy savings are 168.3 and 762.1 TJ, respectively. The results of this study can serve as a reference for current P&P operations and as a base case for stimulating changes in energy utilization. [ABSTRACT FROM AUTHOR]

Accurate understanding of the marginal energy-saving costs of energy-using entities is critical for regulatory authorities to formulate and implement energy-saving policies. This article brings out an easy-to-operate analytical framework to measure the marginal energy-saving cost and construct energy conservation supply curve with the help of data envelopment analysis and quantitative model. Furthermore, taking China's pulp and paper industry as an example, the authors discuss the difference of economic costs between industry energy-saving task assignment with and without considering the difference of marginal energy-saving costs of different energy using entities with the help of linear programming model. The main empirical results are as follow. First, there is a big difference in the industrial marginal energy-saving costs in different provinces. The difference between the highest and lowest energy-saving costs is twice as large. Second, the optimal energy-saving task assignment based on an accurate energy conservation supply curve can help to save nearly 35% of total economic cost. • An alternative method of measuring energy conservation cost is provided. • An optimal energy saving task assignment model is constructed. • The problem of trade-off between efficiency and equity in policy making is discussed. [ABSTRACT FROM AUTHOR]

Abstract: Hydrogen produced from renewable biofuel is both clean and CO2 neutral. This paper evaluates energy and net CO2 emissions consequences of integration of hydrogen production from gasified black liquor in a chemical pulp mill. A model of hydrogen production from gasified black liquor was developed and integration possibilities with the pulp mill''s energy system were evaluated in order to maximize energy recovery. The potential hydrogen production is 59000 tonnes per year if integrated with the KAM reference market pulp mill producing 630000 Air dried tonnes (ADt) pulp/year. Changes of net CO2 emissions associated with modified mill electric power balance, biofuel import and end usage of the produced hydrogen are presented and compared with other uses of gasified black liquor such as electricity production and methanol production. Hydrogen production will result in the greatest reduction of net CO2 emissions and could reduce the Swedish CO2 emissions by 8% if implemented in all chemical market pulp mills. The associated increases of biofuel and electric power consumption are 5% and 1.7%, respectively. [Copyright &y& Elsevier]

Currently, lignite-fired boilers often feature low thermal efficiency, difficult coal pulverizing and poor combustion stability owing to lignite having high water content. A novel lignite-fired power generation process is proposed in this paper with using a superheated-steam-drying open-pulverizing-system boiler (SSD-OPSB) and a deep utilization of waste heat from the steam for coal drying. Through using an open pulverizing system, the problems of low furnace temperature and low boiler efficiency are resolved. Meanwhile, the operation safety of the coal pulverizing system is ensured by using superheated steam as the drying agent. This paper described the working principle and engineering feasibility of the SSD-OPSB process, and established analysis model for its thermo-economic performance. Energy savings and environmental benefits of applying the process were calculated and discussed based on an in-service 600 MW supercritical power unit firing lignite with water content of 39.5% at its turbine heat acceptance condition. The result shows that for the power unit, applying the SSD-OPSB process can decrease coal consumption by 6.86% under the same power supply, meanwhile recovering water by 132.2 t/h and reducing CO 2 emission by 27.78 t/h. It indicates that the SSD-OPSB process would significantly benefit lignite-fired power plants regarding energy-saving and environmental protection. • Lignite-fired boilers can benefit greatly from applying open coal pulverizing systems. • The benefits include marked coal-savings, enhanced coal combustion and water recovery. • A novel superheated-steam-drying open-pulverizing-system was proposed for applications. • Waste heat and water recovery system was designed to the new power generation process. • The model of analyzing thermo-economic performance of this process has been developed. [ABSTRACT FROM AUTHOR]

Nowadays, climate change is a major global societal challenge that significantly increases environmental stress. Most international organizations and policies have promoted initiatives to minimize emissions, reduce fossil fuel dependence and increase renewable energy resource integration into different sectors. An energy transformation towards more renewable systems is thus a priority. Under this scenario, the present paper describes and evaluates an alternative energy conversion matrix-based model to combine sector electrification, power generation units from renewables, and new clean technologies. The proposed green matrix-based model allows analyzing future scenarios, including electricity participation in end-use consumption and electric power generated by renewables – potentially integrated into different sectors –. The proposed model is evaluated in the state of Maine (United States). This case study is focused on decarbonizing both residential heating and transport sector through the integration of large offshore wind power plant. Results and discussion is also included in the paper, providing expected energy demand reductions and decreasing emissions through the integration of renewables. This energy transition integration case study is proposed in three road-maps with different penetration rates and time scales. The proposed green matrix-based model can be also applied to other areas and energy resources, as an alternative way to analyze and estimate renewable integration into different sectors. • Green Electrical Matrix to link electricity supply and end-use for energy transition. • Assesses renewable potential and electrification tech for end uses, e.g., transport. • Applies model to Maine, USA to show reductions in fossil fuels and emissions. • GIS and MCDM for optimal offshore wind location, maximizing electricity generation. • Short, medium, and long-term projections of renewable integration into energy system. [ABSTRACT FROM AUTHOR]

Under the guidance of the "Dual Carbon" goal, integrated energy supply stations have gradually become an essential facility for the energy transition. Promoting user repurchase has become a vital marketing strategy for integrated energy supply station enterprises. This paper proposes a prediction method based on the user profiling method to predict user repurchase behavior accurately. First, using an improved RFM model and the K-means algorithm, this paper constructs user profiles by dividing 10,000 users into three clusters: general-value developmental users, high-value new users, and low-value loyal users. Next, this paper uses the random forest, light gradient boosting machine, and extreme gradient boosting to predict the repurchase behavior of non-clustered users and the three clusters and compares their prediction performance. In addition, this paper adopts the stacking method for model fusion to improve the prediction performance further. The results show that the accuracies of the best prediction models for the three clusters are 93.28 %, 93.68 %, and 92.84 %, respectively. Finally, this paper provides each cluster with the corresponding prediction model of user repurchase behavior and marketing strategy. For the application scenario of integrated energy supply stations, this study accurately predicts the repurchase behavior of each cluster with unique consumption characteristics. It helps to provide personalized services for new energy vehicle consumers, optimize their consumption experience, and facilitate sustainable consumption. • A method for predicting user repurchase behavior for integrated energy supply stations based on the user profiling method. • This paper clusters users based on the unique consumption characteristics and constructs user profiles for each cluster and individual. • Three mainstream ensemble learning algorithms to predict the repurchase behavior of each cluster. • Stacking algorithm for model fusion to improve the prediction performance further. [ABSTRACT FROM AUTHOR]

This paper presents a new framework for optimal planning of electrical, heating, and cooling distributed energy resources and networks considering smart buildings' contribution scenarios in normal and external shock conditions. The main contribution of this paper is that the impacts of smart buildings' commitment scenarios on the planning of electrical, heating, and cooling systems are explored. The proposed iterative four-stage optimization framework is another contribution of this paper, which utilizes a self-healing performance index to assess the level of resiliency of the multi-carrier energy system. In the first stage, the optimal decision variables of planning are determined. Then, in the second stage, the smart buildings and parking lots contribution scenarios are explored. In the third stage, the optimal hourly scheduling of the energy system for the normal condition is performed considering the self-healing performance index. Finally, in the fourth stage, the optimization process determines the optimal scheduling of system resources and the switching status of electrical switches, heating, and cooling pipelines' control valves. The proposed method was successfully assessed for the 123-bus IEEE test system. The proposed framework reduced the expected values of aggregated system costs and energy not supplied costs by about 49.92% and 93.64%, respectively, concerning the custom planning exercise. • This paper presents a new framework for optimal planning of distributed energy resources. • The impacts of smart buildings' commitment scenarios on the optimal planning are explored. • The proposed iterative four-stage optimization framework is another contribution of this paper. • The proposed framework reduced the expected values of aggregated system and ENS costs. [ABSTRACT FROM AUTHOR]

The current single energy storage approach and market incentives do not fully exploit the potential of diverse energy storage methods and market incentives. Additionally, the traditional operation method often results in a poor alignment between energy supply and demand. Moreover, the conventional solution algorithm struggles to address complex problem-solving involving multiple variables. To address these issues, this paper proposes an improved carbon-neutral energy system (ICNES). Firstly, ICNES enhances residual energy utilization by implementing dual-layer residual power and heat treatment. Secondly, to enhance the effectiveness of market incentives, ICNES incorporates an improved approach that combines a dual-layer carbon capture drive, step carbon penalty, carbon reward, and green certificate trading. Thirdly, to improve the supply–demand matching, ICNES introduces a dynamic hybrid operation approach (DFHL). Finally, the paper proposes a honey badger-pattern search algorithm (HB-PSA) to optimize the configuration of ICNES for the DFHL multivariate scenario. Results indicate that compared to conventional carbon-neutral energy systems, ICNES reduces annual operating costs by 6.686%, CO 2 emissions by 9.538%, primary energy consumption by 12.826%, and energy waste rate by 17.465%. Furthermore, HB-PSA increases the optimization rate from 48.693% to 53.88% of the local optimum. • Dual-layer residual electric and residual heat treatment system is proposed. • Dual-layer carbon treatment for carbon neutrality and carbon profitability. • Carbon markets and green certificate are used in carbon-neutral energy system. • Dynamic hybrid operation to improve the matching of supply and demand. • A honey badger-pattern search algorithm is proposed for solving. [ABSTRACT FROM AUTHOR]

Zero-energy buildings usually achieve annual net-zero energy balance by generating electricity using on-site renewable energies and interconnecting with the power grid. However, the impact of energy mismatch problem in zero-energy buildings design on the grid is often overlooked, which potentially compromises grid's stability. To address this issue, this paper presents an optimization design method based on "grid-friendly interaction" which optimizes the energy system of zero-energy buildings to ensure better alignment between the building's electricity purchase/sale and grid demand. In this study, an indicator of "grid-friendly interaction", which represents the ratio of the net building friendly interaction power to the total annual interaction power, is firstly established to guide buildings in improving their interaction with the grid. Next, the energy supply, demand, and storage schemes of renewable energy systems in the zero-energy building are iteratively adjusted to achieve the best match with grid's expectations. This optimization design method was applied to a practical case in Hong Kong. Results show that, compared to the benchmark building, the optimal system design scheme increases grid friendliness by 83 %, reduces carbon dioxide emissions by 77 %, but also incurs a total cost increase of 180 %. The optimization design method proposed in this paper can effectively mitigate the impact of zero-energy buildings on the power grid, fostering enhanced interplay between the building structures and the grid. The study significantly contributes to the advancement of exploring the potential for energy flexibility in zero-energy buildings, which is of great significance for the safe and stable operation of future grids. The purpose of this study is to explore the energy flexibility potential of zero-energy buildings, which is of great significance for the safe and stable operation of future grids. • A novel indicator that reflects the degree of friendly interaction is proposed. • An optimization design method based on "grid-friendly interaction" is presented. • Single-objective and multi-objective optimization are applied respectively to ZCB. • It is of great significance for the safe and stable operation of future grids. [ABSTRACT FROM AUTHOR]

In the context of the increasing popularity of distributed energy, this paper proposes a home energy management system method considering the working state of flexible load to deal with the problem of mismatch between home energy supply and demand. Specifically, in this paper, the flexible load in the system is studied, and the model of flexible load and its working state are established. On this basis, combined with the real-time electricity price of the grid, the model of home energy management system is constructed to minimize the electricity purchase cost and improve the utilization rate of renewable energy, the genetic algorithm is used to solve it, and the influence of time step, flexible load ratio and whether to use energy storage equipment on the optimization degree of the model are analyzed. The research results show that, while meeting the requirements of human comfort and electricity demand, the daily electricity purchase cost of the system with flexible load scheduling is 22.5% lower than that of the system without flexible load scheduling, and the utilization rate of renewable energy is increased by 16.5%. In terms of model optimization, shortening the prediction time step, increasing the proportion of flexible load and using energy storage equipment can further reduce the electricity purchase cost. The case study confirms the effectiveness of the proposed home energy management system model, which can provide an efficient optimal scheduling scheme for household energy saving. • The optimal scheduling model for home energy management system of rural dwellings with flexible loads is proposed. • Influence of the proportion of flexible load and different time step sizes on the scheduling model are studied. • The operation cost by 26.62% of battery integration strategy based on load scheduling is further reduced. [ABSTRACT FROM AUTHOR]

Distributed integrated energy system (DIES) will become the main energy supply method for end-users, however, the volatility of renewable energy makes energy consumption more difficult. To address the problem, this paper proposed an optimization method of DIES energy transaction based on Stackelberg game. Firstly, the typical structure of DIES is studied and a energy transaction framework of electric-heat energy is proposed by introducing integrated energy operator(IEO); secondly, with IEO as the leader and DIES as the follower, considering the highest profit of IEO and the lowest cost and carbon emission of DIES as the objectives, and combining the operational constraints of different subjects, a one-master-multiple-slave Stackelberg game model is established; thirdly, the existence of Nash equilibrium of this game model is demonstrated, and a solution algorithm based on Particle swarm optimization nested Non-dominated Sorting Genetic Algorithm-II is proposed; Finally, to verify the validity of this model, two modes are designed and simulated, and the results show that the proposed method can improve the renewable energy consumption by 2.92%, reduce the DIES energy cost by 3.94%, and reduce the interactive power with the grid by 30.91%, while the sensitivity analysis shows that the method can better cope with energy price changes. • The main contributions of this paper can be summarized as follows: • Analyzed the typical architecture of DIES and proposed a new energy trading framework. • A Stackelberg game model with IEO as the leader and DIES as the follower is developed. • The solution algorithm of PSO nested NSGA-II is proposed. • This method can reduce the cost of energy use and increase the consumption of renewable energy. [ABSTRACT FROM AUTHOR]

This paper aims to analyze the effect of integration of combined heat and power (CHP) units, renewables, shunt capacitors, and a heat boiler in a grid connected microgrid (GMG) system. In addition to that, a comparative study is conducted between the GMG and zero bus concept based microgrid (ZBMG) systems. In ZBMG, a predefined amount of power is injected from the grid. Therefore, one of the dispatchable distributed energy resources (DERs) in the ZBMG maintains the power balance and the corresponding DER unit is entitled as zero bus DER. In this paper, eight different microgrid configurations are formed by several combinations of renewable and non renewable sources, which are categorized under GMG and ZBMG systems. The multiple objectives such as total cost, emission, and energy loss are combined and solved using fuzzy technique and particle swarm optimization (PSO) algorithm. Also, point estimate method (PEM) is implemented to handle the uncertainty in renewables. The effect of grid, dispatchable units, renewables, and heat boiler on the objectives in each microgrid configuration is inspected. The results show that the microgrid configuration with non renewables is attained minimum cost and has a minimum emission with renewables. The integration of all types of sources in a microgrid configuration leads to a decrement in all the objectives. The proposed method is tested on a 33-bus grid connected microgrid system considering electrical and heat loads. • Analysis of microgrid system with different combinations of CHP units and renewables. • Study the impact of optimal allocation of sources in each combination on objectives. • Microgrid system with predefined power from the grid shows satisfactory results. [ABSTRACT FROM AUTHOR]

Energy storage system (ESS) has been considered as a pivotal technology enjoying a wide range of applications in different levels of power systems. However, the investment of ESS is still relatively high. Thus, shared energy storage (SES) is consequently recognized as a promising business model. Considering the dynamic virtual energy storage characteristics of heat network, this paper proposes a power-thermal heterogeneous SES model to meet the practical need of participants. Firstly, a quasi-dynamic model of heat energy transport is conducted to analyze the virtual energy storage potential of heat network. Then, the power-thermal heterogeneous SES model is developed to describe the formation mechanism of ESS supply and demand with heat network as the schedulable energy storage resource. Furthermore, a pricing method of electric-thermal heterogeneous SES is proposed. The upper-level problem of it targets at maximizing the benefits of the SES operator, while the lower-level problem aims to minimize the costs of users. Simultaneously, the service price and user purchase capacity can be obtained as optimization variables. Finally, case studies are adapted to verify the rationality and validity of the proposed model. • This paper develops a novel electric-thermal heterogeneous shared energy storage framework. • This paper presents a business model of shared energy storage. • This paper proposes a bilevel Stackelberg game optimization pricing method for the SES the SES service. • A 33-bus electricity network coupled with a 44-bus heat network has been employed to test the effectiveness of this method. [ABSTRACT FROM AUTHOR]

Increasing energy consumption rates and concerns over environmental problems like global warming have led researchers to provide new energy supply solutions, one of which is the use of combined energy systems. Combining conventional fossil energy cycles with renewable cycles is one of the most effective ways to improve their performance and also help harvest green energy. To address this solution, in this paper, a hybrid novel energy system including a gas cycle, a steam cycle, two organic Rankine cycles (ORC), and a renewable cycle based on geothermal and solar energy sources using concentrating photovoltaic thermal panels (CPVT) is proposed. A comprehensive study has been conducted on this system from the perspective of energy, efficiency, economy, and the environment. Different fluids have been investigated for use in ORC subsystems in this study. Additionally, a parametric study has been conducted to determine how the cycle's overall performance is affected. Multi-objective optimization using the Non-dominated Sorting Genetic Algorithm second version (NSGA-II) has been performed based on the objective variables of exergy efficiency and capital costs. In this paper, Engineering Equation Solver (EES) and MATLAB are used for modeling and optimization. The results show that the best fluids to use in ORC are R123 in the first cycle and Ammonia in the second cycle, which energy efficiency, exergy efficiency, exergy destruction rate, and generated power in the base state for the whole cycle are 50.59%, 25.44%, 1537.35 kW and 524.66 kW, respectively. Also, the amount of annual capital cost and the amount of carbon dioxide emission from energy and exergy are 107,034 dollars, 11,672, and 35,401 kg per month, respectively. The optimization results indicate a 0.25% improvement in exergy efficiency and a 500$ annual capital cost reduction at the optimal point. • Providing a new combined cycle with a combination of fossil and renewable energies. • Conducting energy, exergy, economic and environmental analyzes (4E). • Performance analysis and selection of the best operating fluids for ORC cycles. • A parametric study of factors affecting cycle efficiency and total cost. • Multi-objective optimization of the cycle using DoE, ANN, and NSGA-II methods. [ABSTRACT FROM AUTHOR]

The imbalance between power supply and demand is increasing around the world. As an important basis for the coordination between supply side and demand side to solve the problem of supply and demand balance, the rational formulation of demand response strategy is very important. Aiming at the shortcomings of current demand response strategies in optimizing power flexible allocation, this paper establishes a flexible allocation strategy model under three different objectives of flexible optimization, economic benefit, and energy conservation to realize energy scheduling and flexible optimization under different objectives. The accuracy and rationality of the flexible allocation strategy are verified through experimental comparison. The maximum fluctuation value of the electricity load is 115 W in all electricity parity periods of the experimental days, accounting for 4.9% of the building electricity load, avoiding the occurrence of secondary peak electricity consumption. The power flexibility value provided by the strategy can reach 143% of the building electricity load before the demand response, making the building can be more flexible to face the power supply and demand balance problem of the grid. • A flexible allocation strategy model under three different objectives is established in this paper. • The impact of the energy scheduling at peak power consumption period on other times is considered. • The coupling of various forms of flexible sources makes the strategy have good performance. • Different objectives have significant benefits in flexibility, economy and energy conservation. [ABSTRACT FROM AUTHOR]

Adding propane to CO 2 can improve the thermal efficiency of the supercritical Brayton cycle under high condensation temperatures. Integrating the thermal energy system in a direct-heated solar power tower plant can maximize the thermal utilization of solar energy. In this paper, the thermodynamic model of the plant is constructed, and an operation strategy is proposed to realize round-the-clock operation by flexible scheduling of solar, molten salt, and fossil fuel energy supply. Notably, the potential of adding propane to CO 2 in the plant was analyzed by comparing the off-design performance and the operation behavior under typical days. The results show that the thermal efficiency of the plant using CO 2 -propane is not only 1.63% higher than the original, but also the adequate utilization time of solar energy will be prolonged by 0.3 h. In addition, the hot molten salt filling rate of the CO 2 -propane system is more sensitive to changes with direct normal irradiance. However, the performance of the system will deviate from the optimal design value when the heating mode is switched. The achievements from this paper have testified the CO 2 -propane cycle is better than the initial cycle in the direct-heated solar power tower plant under off-design conditions. The system scheme and operation strategy can be regarded as valuable references for CO 2 -based mixtures application. • The CO 2 -propane is used as working fluid in a direct-heated solar power tower plant. • An operation strategy is proposed to realize all-weather stable operation. • The performance of the plant will deviate from the optimal design value at sunset. • The solar energy adequate utilization time will be prolonged after adding propane. [ABSTRACT FROM AUTHOR]

Serving as the information backbone of an increasingly digitalized world and energy-intensive, the data center industry has to seek low-carbon developing way to properly meet the rapidly rising service demand. This paper designs 45 kinds of configuration choices for each decision units by integrating three data centers, three cooling technologies, as well as five energy supply mixes. The model is formulated as a bi objective optimization problem for the decision maker to decide newly established data location and configuration with objective of reducing data center expansion costs and well as minimizing power utilization associated with carbon emissions from a country level. The pilot study in China under the scenarios of different carbon emissions limitation and propagation delay that China can reduce at least 25% of newly established data center related emissions from 2020 to 2023. It further shows that future expansion can be focus on Inner Mongolia and Ningxia for the north, Hubei for the middle, and Yunnan and Guangxi for the south. This paper provides a fresh perspective and makes a valuable attempt at the low-carbon development of data centers. • Carbon awareness based integrated optimization model for data center in China is proposed. • Layout, scale, cooling technology and power supply mix are simultaneously considered. • 25% of newly established data center electricity related emissions in China can be avoided. [ABSTRACT FROM AUTHOR]

A large amount of low grade heat is wasted at temperatures below 100 °C but its quantity remains mostly unknown. Therefore, the identification and quantitation of low grade heat availability enables further assessments on whether or not the recovery of this fraction of heat is convenient. By considering the countries composing the European Union (EU), this work quantifies the low grade heat from power generation and industrial sectors (mining, minerals, metals, chemicals, pulp and paper, food) with a particular focus on the faction of heat below 100 °C. The analysis shows that, in the year 2018, 8774.4∙106 GJ (2437.3 TWh) of heat was available in the EU below 100 °C, with the power generation sector accounting for 95% of the total low grade heat emitted. In addition, around 96% of the waste heat was in the temperature range from 25 °C to 80 °C, being of ultralow grade. Similar conclusions were obtained in terms of exergy loss, which was essentially from the power generation sector, especially in the range of temperatures between 40 °C and 60 °C. These results suggest that ultralow waste heat is an untapped source of energy which can be conveniently exploited by the same point-source emitters, primarily in the power generation sector or in wider industrial areas where infrastructure is present. • 8774.4∙106 GJ of heat below 100 °C in EU are from power generation and industrial sectors. • Largest fraction (7847.2⋅106 GJ) of ultralow heat in EU is between 40 °C and 60 °C. • The greatest contributor to ultralow grade waste heat is the power generation sector. • An exergy amount of 733.5∙106 GJ is available from ultralow grade waste heat. [ABSTRACT FROM AUTHOR]

Integrated energy systems (IES) have become a popular direction in the field of energy research due to their economic, efficient and environmental friendly advantages. Among them, multi-region integrated energy systems (M-RIES) are more valuable than single-region integrated energy systems (S-RIES) due to their low energy loss, high economy and reliability. At present, there is a lack of an optimisation method that integrates station-network synergy, inter-station interaction, shared energy storage configuration, overall planning of equipment configuration and multi-timescale rolling for the multi-faceted performance enhancement of M-RIES. Therefore, this paper proposes an M-RIES with station-storage interaction and inter-station interaction under the consideration of station-network synergy, and conducts a study on the optimal configuration of M-RIES from the viewpoint of economy and environmental protection. The final analysis is based on a northern region. The results show that the system achieves an energy efficiency of 1.07, a 16.9% reduction in total station equipment configuration, a 3.87% reduction in cost and a 0.76% increase in new energy consumption rate compared to a stand-alone operating system. Taking one of the energy stations as an example, under the operating conditions of 10% intra-day and 5% real-time error, the multi-timescale rolling optimisation method significantly improves the energy supply rate compared to the day-ahead dispatching method, where the error rates for the three typical days of transition, winter and summer are only 0.43%, 2.56% and 0.06%, corresponding to a reduction of 5.02%, 2.49% and 5.06%, and a smaller cost error than the ideal solution The cost error rates for the three typical days are only 1.99%, 3.60% and 3.46%. In summary, the collaborative autonomous planning and operation method proposed in this paper has great advantages in terms of economy, reliability, energy efficiency and environmental protection. • A multi-area collaborative integrated energy system with shared energy storage is proposed. • Day-ahead collaborative, intra-day autonomous multi-timescale rolling optimisation method. • The system has advantages in terms of economy, energy efficiency and the rate of new energy consumption. • The multi-time-optimised rolling method has advantages in terms of both meeting demand and economy. [ABSTRACT FROM AUTHOR]

Recently, the policymakers, economy, and societies' primary and ambitious objective has been to make the world cleaner and carbon neutral. One critical problem in reaching these goals is building energy management, including using local energy sources. This paper provides a methodology based on a total sustainable performance index estimated as the "total life cycle costs," including externalities, that apply to a possible energy source, energy generation, energy storage, energy use, and management. The methodology is applicable to comparative analysis of the locally available energy sources, optimization of the energy generation mix, and real-time energy management of the building, especially for individuals and groups of small and private houses. The significant results of this research conducted in this paper show that (i) the effective, optimized energy mix includes 2 or 3 types of locally available energy sources, (ii) the real-time energy support of the building is effective in case of dealing with all the energy sources, energy generation, and energy use methods, (iii) the energy management system should be centralized and supported by a large number of sensors, (iv) developing local micro grid including 20–100 houses increasing the energy supply efficiency for 20–45%. • Residential buildings use 26% of total energy in the European Union. • All the applicable technologies and locally available energy sources must be optimized/managed. • New objective function: overall life cycle cost/unit of energy used (single parameter index). • Concept/methodology created for optimization/management of building energy support. • Developed system improves building energy support for efficiency by 12–26%. [ABSTRACT FROM AUTHOR]

The coalbed methane energy resources waste, environmental pollution and miner's health remain challenging problems in worldwide mining operations accompanied by coal-gas outbursts; thus, the safe and efficient yield of these resources plays a vital role in the world's energy market. The tectonic coal development is a significant geological feature of coal and gas outburst sites, and the study of coal and gas outburst mechanism should be based on more precise geological occurrence characteristics. In this paper, the geological characteristics of coal and gas outburst sites were analyzed. The failure law of coal body under the stratified occurrence of tectonic coal and raw coal seam with different thickness was studied. The mechanical equilibrium equation of non-synchronous deformation of tectonic coal and raw coal was constructed, the initiation criterion of coal and gas outburst was established based on the support body model, and a case study was carried out. The results show that with the thickness increase of the tectonic coal seam, the peak displacement of the driving face increases. The outburst start-up and development of coal and gas outburst, coal and gas extrusion outburst and coal and gas collapse outburst were deeply analyzed, as well as the internal reasons of the occurrence of coal-gas outburst portent are explained, based on the support body model. The development process from the start to the end of coal and gas outburst is revealed, and a new perspective is proposed for the prevention and control of coal and gas outburst: improving the strength of support body is also of great significance for the prevention and control of coal and gas outburst. • Asynchronous deformation induced coal-gas outburst mechanism. • The initiation criterion of coal and gas outburst was established. • The start and development process of the three types outburst were revealed. • New theoretical method and direction into dynamic disaster monitoring. [ABSTRACT FROM AUTHOR]

The 2023 revision of the Energy Performance of Building Directive underlines the need to consider the whole life cycle emissions for buildings. The decarbonization targets could not be achieved if reduction of energy demand in the operational phase is accompanied by a high energy resource use in the whole life. This paper proposes a novel investigation of an energy renovation project, involving both building envelope components and space heating system. The adopted method is based on the life cycle assessment, in the variant cradle-to-gate with options, to analyze and compare the design data achieved through an analysis of product (embodied) and use (operational) stages. Different solutions for energy improvement of the building performance are identified, and the scenario with the lowest embodied energy was found to be more energy efficient globally. The most effective scenario, with energy and CO 2 savings of 39% and 40% is characterized by a weight of embodied energy and emissions of 6.5% and 6.9%, respectively. Given the rise of the weight of the embodied energy in the whole life cycle of future buildings, the life cycle assessment will become crucial for sustainable design and in the transition to an energy-efficiency built environment. [Display omitted] • The impact of life cycle analysis in the process of energy efficiency is investigated. • The "cradle-to-gate" with options approach is implemented. • The efficiency of walls and windows involves the greater use of energy resources. • The most energy-efficient scenarios from an operational and non-operational point of view are different. • The scenario identified in the analysis of A1-A4 phases allows a higher total energy saving. [ABSTRACT FROM AUTHOR]

Cogeneration nuclear power plants (NPP) can reduce carbon emissions and improve the economy to deal with climate problems. However, after adding the thermal energy supply system (TESS), the nuclear reactor power control system (NRPCS) is affected by the change in the relationship between energy supply and load. Therefore, the NRPCS of VVER-1000 with TESS (Ts-VVER) is studied. In this paper, first, the simulation model of Ts-VVER is established, with the extraction of steam from the main steam header. Second, dynamic characteristic analysis, coupling characteristic analysis, and energy balance relationship analysis are studied to evaluate the influence of Ts-VVER. Then, the NRPCS modified scheme is designed, and the new nonlinear feedforward gain curve is gotten from the original curve by translation. Finally, the designed NRPCS modified scheme is verified by typical conditions simulation. The modified scheme can offer a reference for the design of the NRPCS of other cogeneration NPPs. • The simulation model of VVER-1000 with the extraction steam from the main steam header is established. • The dynamic characteristic, coupling characteristic, and energy balance relationship are studied. • A modified scheme of nuclear reactor power control system is proposed and verified. [ABSTRACT FROM AUTHOR]

Wind power and pumped storage combined system (WPCS), as an entity integrates multiple energy sources, can provide a reliable overall power supply by optimizing the management of available resources, helping to combat the serious climate change challenges. In order to address the participation of combination system in multiple market operations and multiple uncertainties, this paper proposes a joint declaration strategy for WPCS to participate in the electricity market (EM) and frequency regulation market (FRM). Firstly, the trading mechanism is developed for WPCS to collaborate in power markets. Secondly, a joint declaration and dispatching strategy decision-making model of WPCS is constructed, and the uncertainty of market prices and wind power output in the model is processed by using the information gap decision theory-distribution robust optimization (IGDT-DRO) technique. Finally, simulations implemented on an actual WPCS are delivered to show that: 1) WPCS achieved an expected profit by 8.79% and decrease deviation penalty costs by 58.81% through multi energy complementary operation. 2) Compared with the single market, WPCS can increase the expected profit by 77.5% in the joint declaration of multi-markets.3) IGDT-DRO technology can simultaneously manage the uncertainty of both price and electricity. When the sample size increases tenfold, the runtime increases by less than 40%, which has advantages in data-driven and stable runtime. [Display omitted] • A synergistic trading mode of electric energy and frequency regulation markets is designed. • A declaration-dispatching strategy for wind power and pumped storage participating in EM andFRM is constructed. • The IGDT-DRO technique is used to deal with the uncertainty of market price and wind power generation. • The characteristics of IGDT-DRO model in data-driven feature, non-conservative result and stable run time have been proved. [ABSTRACT FROM AUTHOR]

Autonomous underwater vehicles (AUVs) are one of the most important means of ocean exploration. However, the restricted energy supply poses a significant challenge to the advancement and practical application of AUVs. Based on the structural characteristics, this paper proposes a novel AUV, which integrates a deformable double-float wave energy converter (WEC), called DFWEC-AUV. The DFWEC empowers the AUV to capture wave energy to supply itself by oscillating double-float form in power generation mode. The structural design, focusing on the deformable float (DeF) and the onboard damping plate (DP), and the working principle, including mode switching and energy capture, are firstly introduced. Then, a double-float dynamic model of DFWEC-AUV oscillating in regular waves is established to reveal the energy capture mechanism in both frequency-domain and time-domain. Finally, the influence of the presence of DP, structural parameters (diameter of DP and deployment angle of DeF) and power take-off (PTO) system damping coefficient on the dynamic response characteristics and energy capture performance is analyzed. In addition, to verify the effectiveness of the performance analysis, a comparative simulation of parameter optimization is carried out under actual wave excitation. The results show that the addition of onboard DP is able to effectively enhance the energy capture performance of DFWEC-AUV, as well as increase the energy capture bandwidth. Moreover, the larger the diameter of the DP is, the greater the performance improvement of DFWEC-AUV is. Conversely, increasing the deployment angle of the DeF does not necessarily lead to better power capture performance. Additionally, it is observed that waves of a particular period are consistently associated with an optimal PTO damping coefficient, which leads to superior power capture performance. In comparative simulation, the energy capture performance of DFWEC-AUV after parameter optimization is increased by 4.7 times. • A deformable double-float WEC for AUV is designed and the working principle is analyzed. • The hydrodynamic model of DFWEC-AUV is established, simulated and verified. • The influence of several key factors on the energy capture performance of DFWEC-AUV is analyzed. [ABSTRACT FROM AUTHOR]

Natural gas, as a clean and low-carbon energy resource, assumes a vital role in facilitating the transformation of the Chinese energy structure. Effectively forecasting its consumption holds great practical implications for the high-quality social development of China. Therefore, a hybrid model for forecasting natural gas consumption (NGC) in China is developed in this paper. Firstly, the Logarithmic Mean Divisia Index (LMDI) method is adopted to decompose the influencing factors of the NGC in China from 1994 to 2020, which revealed that the energy structure effect and the economic development effect have a positive promotion on NGC, while the energy intensity effect manifests a significant inhibition. Subsequently, based on the contribution rate of each factor, the particle swarm optimization (PSO) algorithm to optimize the long and short-term memory neural network (LSTM) model is constructed for NGC forecasting. Compared to other benchmark models, the PSO-LSTM model demonstrated a significant improvement in predictive accuracy, showcasing its valuable application in NGC prediction. Finally, the PSO-LSTM model is employed to analyze the scenario prediction of NGC development from 2021 to 2035. The forecast result indicated that the future NGC in China will show a yearly growing trend, which may lead to a serious imbalance between the supply and demand of natural gas, so the Chinese government should fully consider the energy security issue when formulating relevant policies. • The LMDI method is applied to decompose the factors of natural gas consumption. • The energy consumption structure and economic development positively promote NGC. • The energy intensity effect negatively inhibits the development of NGC. • Scenario analysis of NGC is performed by constructing a PSO-LSTM model. [ABSTRACT FROM AUTHOR]

Hybrid energy storage offers a new way to increase the renewable energy proportion (REP) of near-zero energy community energy system (NZECES). However, the optimization operation method of NZECES combining hybrid energy storage is not yet mature. Therefore, this paper proposes integrating electricity storage, heat storage and hydrogen storage into the NZECES, and conducting multi-time scale (MTS) operation optimization research. Firstly, a NZECES with electricity-heat-hydrogen storage is constructed. Secondly, a MTS optimization operation model of day-ahead scheduling, intra-day rolling, and real-time adjustment is established. Among them, the hourly scheduling scheme targeting the lowest daily operating cost is obtained through the optimization of the day-ahead stage. In the intra-day stage, the scheduling scheme with a time interval of 15 min is obtained by the rolling optimization. The operation scheme of electrical-related equipment with the minimum adjustment cost is obtained in the real-time stage. Finally, a NZEC with different building types is used as the energy supply object. The results show that compared to the traditional day-ahead scheduling scheme, the REP is increased by 3.6 % and the operation cost of the energy system is reduced by 5.3 % by using the MTS operation optimization method. • A near-zero energy community energy system with hybrid energy storage is constructed. • A multi-time scale operation scheme of day-ahead, intra-day, real-time is proposed. • The scheme can improve the renewable energy proportion and operation economy. [ABSTRACT FROM AUTHOR]

The integration of source-grid-load-storage greatly improves the energy managing flexibility of regional integrated energy systems (RIES). Considering the conflicting interests of multi-operator, this paper divides RIES into 1) energy supply center (ESC); 2) load aggregator (LA); 3) energy storage aggregator (ESA), and establishes a multi-operator two-layer optimal scheduling model by combining 1) the Stackelbelberg-Nash asymmetric bargaining game based on the genetic algorithm; and 2) the alternating direction method of multipliers algorithm (GA-ADMM). Firstly, considering the absence of historical data, trapezoidal fuzzy parameters are introduced to construct fuzzy chance constraints based on credibility theory to simulate the source-load uncertainties. Secondly, the uncertainty of demand response behavior, real-time carbon credits trading within RIES, and cooperation-competition behavior of followers (LA and ESA) are considered to simulate the asymmetric relationship between followers and leaders (ESC) based on GA. Then, based on the ADMM algorithm, a Nash asymmetric bargaining game considering energy dependency and energy supply-reception status is proposed to realize the revenue allocation between followers. Finally, simulations are implemented to verify the validity and reliability of the proposed model. Results show that: 1) Cooperation improves the energy-managing flexibility of followers, reduces their dependence on ESC, and thus enhances their game ability. 2) The real-time carbon credits trading enables zero-carbon energy interactions and natural gas replenishment within RIES. 3) Increases in the price of various energy and carbon credits can enhance cooperation between followers. • Source-load uncertainties are considered by FCCP. • Regional carbon credits trading based on sharing CCS is established. • The asymmetric game relationship of multi-operator is simulated. • A revenue allocation considering consumption features and efficiency is proposed. • The stability of followers' competition-cooperation relationship is explored. [ABSTRACT FROM AUTHOR]

Digitization has dramatically facilitated the development of internet data centers (IDCs), which have become necessary demand response resources for distribution networks. To improve equipment utilization, integrated coordination of IDCs, photovoltaics, energy storage systems, and flexible substations is essential. This also ensures power supply reliability and the operational economy of IDC park. This paper proposes a distributionally robust planning method for an IDC park considering operational economy and reliability. First, a coordinated planning model of an IDC park is proposed with multiple resources, in which the workload dispatch of the IDC is incorporated under fault conditions. The reliability index of the IDC park is designed to quantify its reliability cost. Then, considering the fluctuation of distributed generators and workload, a distributionally robust planning model is established. A planning scheme for the IDC park under the worst scenario probability distribution is obtained. Furthermore, the influence of uncertainties on the planning scheme is analyzed. Finally, a practical data center park is used for case studies. The established planning scheme effectively balances the operational economy, reliability, and planning conservatism. • Coordinated planning for data center parks was conducted with multiple resources. • Workload dispatch of data center is considered under fault conditions. • Reliability indices were designed to quantify reliability costs of IDC park. • A robust planning model was established for data center parks with uncertainties. • Planning scheme achieved a balance between economy, reliability, and robustness. [ABSTRACT FROM AUTHOR]

Based on the analysis of energy structure and the development trends of advanced nuclear energy technology, combining the complementary advantages of nuclear energy and other energy sources in China, the Fluoride-Salt-cooled high-Temperature Advanced Reactor (FuSTAR) system has been proposed. FuSTAR system is designed to address production capacity issues in areas with energy shortages or resource concentration and can be combined with high-temperature process heat to achieve high-value-added processes such as hydrogen production. In this paper, the Tri-structural isotropic fuel combined with helical cruciform elements has been studied in detail on the neutron physics and thermal-hydraulic properties, and the flow and heat transfer experiment is carried out for the first time. The multilayer nonlinear programming method has been applied to the design of thermal transport systems. Then the optimal parameters and configuration of the thermoelectric conversion system are obtained by the superstructure optimization method. The inherent safety of FuSTAR is demonstrated through deterministic safety analysis. In addition, the iodine-sulfur cycle technology and the characteristics of tritium production are also analyzed. This study highlights the significant potential of integrating nuclear energy with other energy sources in an optimized energy-production system. • Multi-purpose reactor energy system for power - hydrogen - tritium production. • Over 50 % maximum thermal efficiency. • Simultaneous analysis of design, optimization, and safety. [ABSTRACT FROM AUTHOR]

Abstract In this article, a novel analytical approach (named as zero bus load flow (ZBLF)) is proposed for DG placement to the distribution network under the scenario of known power injection from the utility/substation. The study is carried out for deferent load levels and for two different distribution networks (viz. 33- and 69-bus distribution networks). In this work, biomass (working at the power factor same as that of the load power factor) is considered as the DG source. From this study, it may be noticed that, by placing the DG at the selected bus, the active power loss of the network may be reduced even when the power supply from the utility grid is zero. In this paper, a combined approach of ZBLF and symbiotic organism search (SOS) has been proposed for the placement of multiple numbers of DGs for the scenario when the power supply from the utility/substation is known. Both the technical as well as the economic aspects of the DG placement for both the distribution networks are studied and presented in this research paper. DG placement using the proposed method also founds to be economical to the utility. Highlights • DG placement under the scenario of known power injection from utility is studied. • Zero bus load flow (ZBLF) is proposed for DG placement. • For multiple DG placements, a combined ZBLF and SOS approach is proposed. • The economical aspect of DG placement is also studied. • Optimum placement of DG reduces active power loss of the distribution network. [ABSTRACT FROM AUTHOR]

In today's China, the reverse distribution of electricity resources and electricity demand makes large-scale and long-distance transmission of electricity inevitable, resulting in the problem of electricity allocation optimization. To address this problem in the region covered by the China Southern Grid (CSG), the paper establishes an optimized model for electricity generation and interprovincial trading strategies in southern China. Based on data from 2015, this paper simultaneously optimizes electricity generation and interprovincial trading strategies in each of the five provinces. The result shows that interprovincial trading in the CSG-served area can yield significant energy, economic, environmental and interconnection benefits. It can reduce the power supply cost and environmental pressure in Guangdong province, help make Yunnan province a hydropower base in China and a thermal power base in southern China, facilitate the completion of the "West-to-East Power Transmission" project, and partly resolve the issues raised in each province's 13th Five-Year Plan as well as the problem of optimizing electricity allocation in the region covered by the CSG. • We propose an annual total optimized model for electricity generation and interprovincial trading in Southern China. • The model optimizes the electricity trading and transmission routes across regions. • The model considers the generation cost and penalty cost of emitting CO 2 , SO 2 and NO x. • Corresponding policies and proposals are put forward for power grid and five regions in South China. [ABSTRACT FROM AUTHOR]

Abstract In this paper, a novel power generation system integrating a natural gas expansion plant with a geothermal organic Rankine cycle (ORC) was proposed. The paper begins with an introduction to the thermodynamic and economic models of the system. Secondly, contrastive analyses of three candidate working fluids were made, leading to the selection of R600 as the best fluid for the system, and the effects of gas pipeline parameters fluctuation on the system performance were originally investigated and analyzed based on the actual operating data of a natural gas PRS, located in Xiqing district, Tianjin, China. Finally, a multi-objective optimization for the system using R600 as working fluid was done to find the optimal evaporation temperature based on the TOPSIS decision-making method, and exergy loss analysis was accomplished at the optimal condition. The results indicated that the proposed system had a net profit of 3.97 M$ in the life time and a small payback period around 2.0 years at the optimal evaporation temperature of 45.5 °C where the system had a high thermal efficiency of 89.8% and exergy efficiency of 84.13%. Additionally, the condenser has the greatest potential to reduce the total exergy loss of the system. Highlights • A power system integrating a natural gas expansion plant with a geothermal ORC. • R600 is the most suitable working fluid for the system. • Effects of gas parameters fluctuation on the system performance. • A multi-objective optimization for the system with R600. [ABSTRACT FROM AUTHOR]

Abstract With the revolution of the traditional economic and social pattern based on centralized fossil energy consumption, the regional integrated energy system (RIES) has gained rapid development in recent years for achieving higher energy efficiency. This paper expands the Demand Response (DR) concept to the RIES and presents an optimal operation model of RIES considering the DR mechanism on the energy price. In this paper, a comprehensive DR strategy combining energy price and different loads is firstly developed to exploit the demand flexibility of RIES in the DR model established. Based on the DR modeling of the RIES, an operation optimization model with environmental, economic benefits and energy supply reliability as objective functions has been firstly established in detail. Secondly, a complete scheduling scheme is built based on the energy consumption characteristics and system operation characteristic of the integrated energy system. The model presented could reduce the cost of system without causing a significant amount of environmental pollution, and improve the energy efficiency of the RIES efficiently. Besides, the scheduling strategy proposed could also provide support for the operation strategy of integrated energy system under the energy development. Hopefully, this paper will provide reference for future research and engineering projects on DR programs in the RIES. Highlights • The typical structure of the RIES is introduced. • A DR model suitable for the RIES considering different loads is established. • An optimal operation model of the RIES based on DR is established. • The load in the RIES is affected not only by energy price but also by other loads. [ABSTRACT FROM AUTHOR]

Abstract This paper shows the common developments performed by the Institute of Thermal Technology and the Research Centre for Energy Resources and Consumption regarding the assessment of natural resource degradation. Particularly, it shows the last model of the Szargut's Reference Environment, which was updated with new geological and geochemical information not available when it was originally developed. This R.E. allows for a more precise assessment of the chemical exergy of natural resources. The paper further shows the concept of the Exergy Replacement Costs (ERC) and the model of Thanatia, a theory that serves to assess the concentration exergy of mineral resources based on their scarcity degree in Nature. The combination of the ERC concept with the Thermo-Ecological Cost method (TEC), originally proposed by Szargut to assess products considering the exergy associated to the consumption of non-renewable resources extracted directly from Nature, gave birth to the TERC methodology, to better assess the degradation of the mineral capital. Highlights • The joint work on exergy between the Zaragoza and the Gliwice schools is shown. • The latest update of Szargut's Reference Environment is presented. • The Exergy Replacement Costs (ERC) and Thermoecological (TEC) costs are explained. • The ERC and the TEC methods are merged to better account for mineral resources. • The functionalities of the new Exergoecological Portal are shown. [ABSTRACT FROM AUTHOR]

Abstract A shortage of gas supply renders gas expensive and may even cause power outages. Estimation of the failure probability of gas supply is an essential component of an integrated energy system. To ensure that failure probability estimation is relevant to an actual project, energy network constraints should be fully considered in calculations. Here, this paper develops a second-order reliability estimation method to cope with the nonlinearity caused by network constraints. Under conditions of integrated energy supply, correlations exist between the extremes of wind power, the heat loads, and failure of the natural gas supply. This paper illustrates the proposed method by comparing the results to those of other methods. The proposed method is efficient in terms of both accuracy and computational time. Compared to a mixed algorithm, which required 1101.1 s to simulate tens of thousands of samples, the proposed method takes 3.5 s to obtain a failure probability. Also, the proposed method improves accuracy by at least 10-fold compared to that of a first-order reliability method. Highlights • This paper presents the gas supply problems for an integrated energy system. • Practical engineering problems are investigated in China and the United States. • The stochastic behaviours of gas supply deliverability are considered. • The dependencies between extreme wind power, heat loads and gas supply deliverability are modelled. • The application of the proposed method is illustrated using an ideal integrated energy system. [ABSTRACT FROM AUTHOR]

In dispersed power generation, low power devices are used for local combined generating of heat end electric power. There are developing concepts of micropower plants with electric generators driven by steam or gas microturbines. The paper presents the results of an experimental investigations of the microturbine set consists of the turbine with partial admission, permanent magnet generator and three phase AC-to-DC rectifier. The microturbine was designed for steam of HFE7100 as a working medium. The dynamic behavior of the microturbine unit was experimentally examined. Microturbine unit was tested during changes of the parameters of the working medium or the electrical load. Experiments were performed with compressed nitrogen as a working medium. The dynamic model of microturbine unit was developed. The examples of the comparison between experiment results and simulations are shown and discussed in the paper. [ABSTRACT FROM AUTHOR]

More accurate and reliable wind speed forecasting results can provide an effective assessment of wind energy resources and improve the efficiency of wind energy utilization. Therefore, this paper is devoted to constructing accurate wind speed forecasting models and quantitatively analyzing the models by using interpretable analysis. Firstly, a multivariate wind speed forecasting model (PMI-CMOGSA-RELM) is proposed based on machine learning methods and a clustering-based multi-objective gravity search algorithm (CMOGSA). Among them, wavelet packet decomposition (WPD) is used for noise reduction, candidate input feature pool and partial mutual information (PMI) are used for feature selection, and CMOGSA is used to optimize the final combined weights. Secondly, a new evaluation metric, Absolute Error Coverage Probability (AECP), is proposed to better evaluate forecasting accuracy. Then, post-hoc attribution analysis methods and visualization tools are used to analyze the forecasting model interpretability to help us better analyze the robustness and reliability of the forecasted results. Finally, this paper validates and evaluates the proposed model with two data sets of different resolutions. The experimental results not only prove the rationality of the AECP evaluation criteria, but also demonstrate that the proposed model has smaller errors, higher estimation accuracy, and is easier to understand. • The proposed model is based on multiple time-lag multivariate data. • In this paper, CMOGSA is proposed based on clustering algorithm. • A new evaluation metric is proposed in this paper. • Interpretability is analyzed from significance and sensitivity of model weight. • PDP and ICE visualization analyses are used for interpretable studies. [ABSTRACT FROM AUTHOR]

Industry poses one of the biggest challenges in the renewable energy transition. In this paper, fossil fuels in the European industrial sector are replaced by renewable energy using a novel tool, IndustryPLAN, a planning tool for the assessment of national industrial sectors. In a bottom-up approach, each industry sub-sector is addressed with energy efficiency and fossil fuel replacement measures based on best available and innovative technologies, and in a top-down approach, the fuel and electricity consumption per country is analysed and decarbonised. The results indicate that: 1. Known technologies can decarbonise most of the industrial sector; 2. Costs and efficiencies are improved by energy savings and electrification; 3. Limiting bioenergy consumption is a critical challenge, emphasising the key role of energy savings and electrification, and the alternative of using hydrogen or hydrogen-based electrofuels will make the transition more expensive and induce energy losses. A full transition to renewable energy and a decarbonised industry sector may be possible before 2050, however, this requires that all investments are sustainable from 2030 onwards and that grid electricity is fully decarbonised. This paper presents several pathways toward 100% renewable energy supply in the European industrial sector and discusses the implications of the outlined scenarios. • Four tangible 100% renewable energy scenarios for industry in EU27 + UK are established. • 100% renewable energy in industry is feasible before 2050. • Energy efficiency improvements are essential to limit biomass consumption. • Industry energy transition needs to be prioritised in short- and long-term planning. [ABSTRACT FROM AUTHOR]

Large-scale new energy access to the power grid poses significant challenges to its stable operation. Differentiated user-side power consumption patterns further widen peak-valley differences in power demand. This paper focuses on operation scheduling problems of virtual power plants with coordinated optimization of diverse flexible loads and new energy, through efficient aggregation and optimization control of new energy and demand-side resources, improving power supply and demand mismatch. Firstly, Long Short-Term Memory and Latin Hypercube Sampling were employed for predicting the day-ahead output of wind and photovoltaic power. Secondly, wind and photovoltaic power, batteries and a pumped storage plant were aggregated into a virtual power plant, and the day-ahead optimization scheduling model was constructed considering system operation costs, energy curtailment costs and demand response costs. Finally, a simulation analysis was conducted. The results show that when large-scale new energy accesses to the power grid, traditional "Generation varies with Load" regulation modes will cause massive energy waste, while the "Generation-Load Interaction" regulation mode can achieve the linkage optimization between the generation side and the demand side, enhancing the system acceptance of new energy. Demand response can optimize users' power consumption behaviors, reducing the charging costs by 52.13 % and heating costs by 0.84 %. • "Wind-Photovoltaic-Battery-Pumped Storage" virtual power plant model. • Aggregation and control of new energy and demand-side resources. • Coordinated optimization of "Generation-Load-Storage". • Cost-benefits evaluation of participating entities from a whole-part perspective. [ABSTRACT FROM AUTHOR]

The recent geopolitical conflicts in Europe have underscored the vulnerability of the current energy system to the volatility of energy carrier prices. In the prospect of defining robust energy systems ensuring sustainable energy supply in the future, the imperative of leveraging renewable indigenous energy sources becomes evident. However, as such technologies are integrated into the existing system, it is necessary to shift from the current centralized infrastructure to a decentralized production strategy. This paper presents a method to identify a panel of technological solutions at the district level, intended to reduce complexity for the integration of decentralized models into a national-scale model. The framework's novelty lies in combining a global sensitivity analysis for solution generation with clustering to identify typical configurations. The global sensitivity analysis is performed on a mixed integer linear programming model, which optimally sizes and operates district energy systems. The sensitivity analysis determines the most influential parameters of the model using the Morris method and provides a representative sampling of the solution space by leveraging the Sobol sampling strategy. The latter is then clustered using a density-based algorithm to identify typical solutions. The framework is applied to a suburban and residential Swiss neighborhood. The first outcome of the research is the high sensitivity of the model to energy carrier prices. As a result, Sobol's sampling space separates itself into two system types: those based on a natural gas boiler and those relying on a combination of electrical heaters and heat pumps. For both types, the electricity demand is either fulfilled by PV panels or electricity imports. The identified configurations showcase that the framework successfully generates a panel of solutions composed of various system configurations and operations being representative of the overall solution space. • Energy carriers' retail prices are the most influential parameters of a district energy system. • Energy system configurations differ according to the consumed energy carrier and PV penetration. • PV deployment is affected by electricity tariffs but not by technological implementations. [ABSTRACT FROM AUTHOR]

Solar thermal power system and photovoltaic coupled system can supply electric energy based on renewable solar energy. To explore the optimal configuration of hybrid microgrid driven by solar energy and to achieve a stable and sufficient electric power supply for the distributed energy system, this paper configures a solar thermal-photovoltaic hybrid microgrid and compares the performance of several microgrids based on the power load analysis of the building. The working fluid and the microgrid configuration are determined based on the performance evaluation of single and hybrid microgrids. The effect of solar irradiation on economic and environmental performance is analyzed under the meteorological data of Xi'an and Lhasa in China. Furthermore, the configuration optimizations of a hybrid microgrid based on the actual load and basic load of the building are carried out to examine the performance of the system. Results indicate that economic and environmental performances are sensitive to solar irradiation. More than 50 % of the area of solar thermal collector can be saved for Lhasa compared with Xi'an. Solar thermal-photovoltaic hybrid microgrid with battery can decrease carbon emission and avoid dependence on the external power grid. • Cooling, heating, power load of a six-story building is evaluated and converted. • Multi-objective optimization of solar thermal power system microgrid is performed. • Configuration optimization of solar thermal-PV hybrid microgrid is carried out. • Optimal microgrid configuration under different power load types is compared. [ABSTRACT FROM AUTHOR]

As a result of the development of energy commercialization, integrated energy services can meet multiple forms of energy supply. In this paper, the cooperative game of a multi-park integrated energy system for industrial, commercial, and residential areas with hydrogen energy based on Nash bargaining theory is established towards the joint dispatching of parks with operation differences in energy sharing mode. Firstly, the techno-economic framework considering the difference of park integrated energy systems is built, whilst introducing the hydrogen-doped electric-to-gas process. Second, by taking into consideration the interests demands and individual differences of each park subject through the cooperative game, the operation representing the interests of the multi-park integrated energy system is established. Then, on the basis of ensuring that the proposed cooperative game model can maximize the social benefits, the original problem is transformed into two easier-to-solve sub-problems. The alternating direction method of multipliers is used to successively solve the two sub-problems in a distributed manner. Finally, the simulation results show that the proposed model can reduce the purchased cost by 1298.8199 $, operation cost by 2319.3456 $, and carbon emissions by 62.1281 t, and improve the renewable energy integration by 12.3011 MW compared with the non-cooperative operation. • A cooperative framework for multi-park integrated energy systems is developed. • The hydrogen-doped electric-to-gas process is established for flexibility. • Nash bargaining determines the energy transaction and the pricing strategy. • The individual differences of industrial/commercial/residential areas are studied. [ABSTRACT FROM AUTHOR]

"In the field of energy supply, coordinated multi-carrier systems, which include natural gas and electric energy, offer unique opportunities to enhance energy efficiency and flexibility. Nevertheless, the interdependence between electricity and natural gas networks poses various challenges related to the flow of electricity and gas in feeders, pipes, and connection points. To address these challenges, the concept of an energy hub emerges as an essential component in multi-carrier energy systems, serving as a connection point between the electricity grid and gas grids. This study introduces an optimal operation method for coordinating gas and electricity distribution networks through interconnected energy hubs. The infrastructure of the proposed energy hub comprises a combined heat and power unit, a boiler, an electric energy storage system, a heat pump, and a gas-burning unit, effectively meeting heating and electrical load requirements. The model formulation follows a stochastic approach based on a two-stage scenario. Considering uncertainties related to wind energy, electric load, and real-time energy prices, the primary objective of this study is to minimize the total operating cost of the energy system. The optimization problem is solved using Wall's optimization algorithm. To meet its energy requirements, the integrated energy system presented in this paper actively participates in the real and daily electric energy markets, as well as the natural gas market, providing the necessary energy resources. Additionally, the model incorporates realistic descriptions of electric power and gas flow in feeders and gas pipelines, considering AC load distribution and the Weymouth equation. With consideration of connectivity constraints, the proposed model offers a comprehensive representation of the integrated electricity and gas networks. The simulations conducted on the integrated energy system, comprising a 33-bus electric network and a 6-node gas network with interconnected energy hubs, highlight a remarkable 12 % decrease in electricity purchase costs and a substantial 18 % reduction in natural gas procurement expenses, underscoring the cost-efficiency and effectiveness of the stochastic planning approach. • "Stochastic scheduling for coordinated electricity & natural gas systems with integrated energy hubs.". • "Comprehensive study to optimize performance, minimize costs, & tackle uncertainties in multi-energy systems.". • "Incorporates real characteristics of electricity & gas networks using AC load & Weymouth equations.". • "Integrated energy hubs as connection points for gas & electricity carriers, participating in markets.". [ABSTRACT FROM AUTHOR]

The long-term variability of wave energy resources will affect the practical decadal application of wave energy converters. This paper has evaluated the distributions and long-term trend of wave energy resources in the sea regions along the Chinese coastline for 83 years based on reliable ERA5 wave reanalysis data from 1940 to 2022 after verifying by 39 local buoys, and found that it is of great potential to develop and apply wave energy resources projects. The long-term trend analysis of the wave energy density and its major contributing wave parameters, significant wave height, and wave energy period, is carried out using Theil-Sen estimation showing the general positive tendency. And the impacts of the decadal variation on four wave energy converters are evaluated via computing the decadal mean power production by combining the wave energy density and the wave energy characteristic. It is verified that the long-term wave energy density in this region increases along with the decrease in power production and the capture width. This study shows that long-term variability of wave energy resources and wave energy characteristics should also be considered in the designing of WECs and the identification of energy hotspots. • Long-term variability of wave energy resources along the Chinese coastline are analyzed based on the 83-year ERA5 wave reanalysis data in 1940–2022. • Decadal variations of power production and capture width are figured showing the obvious decrease in the time span. • The impact of long-term wave energy characteristics on wave energy converters is significant. [ABSTRACT FROM AUTHOR]

The scale-up of urban electric vehicle (EV) fleets, driven by environmental benefits, is resulting in surging aggregate energy demands that may reshape a city's power supply. This paper establishes an integrated data-driven assessment model for investigating the energy use (kWh) patterns and charging load (kW) profiles of urban-scale EV fleets. To this end, urban EV operating and operational datasets are linked with climate data and vehicle specifications. Four vehicle fleet types are distinguished: private, taxi, rental, and business fleets. Statistical models regarding distribution analysis, spectrum analysis, and identical distribution tests are employed to analyze the patterns of driving distances, energy consumption, and shares of active charging EVs. The minute-level changes in charging EV numbers and aggregate charging power are examined to reflect the grid load impact. The results show that private light-duty EVs in Beijing consume an average of 9.1 kWh/day, with more charging activities on Fridays. The primary load peaks of light-duty EVs in Beijing usually occur between 11 p.m. and 1 a.m., attributable chiefly to the private fleet's midnight peak load estimated at 28 % of the total daily charging private EV count multiplied by 5.5 kW/EV. Secondary peaks occur between 8 a.m. and 10 a.m. on weekdays for private fleets, and at 4 p.m. for public fleets. Our work can be extensively used for analyses on transport emissions, urban power supply, infrastructure build-ups, and policymaking. • An integrated data-driven model for large-scale EV operation analysis is proposed. • Real-world energy use patterns and load profiles of urban EV fleets are unveiled. • Urban-scale EV big data are utilized for fact-based assessments. • Diverse data sources are linked through spatiotemporal information. [ABSTRACT FROM AUTHOR]

GreenValve (integrating a runner into a ball valve) is a highly promising solution for harvesting excess water energy from the pipe to power the electrical equipment in the pipe network. In order to better match the actual operation of the GreenValve and to realise the simulation of the non-stationary operation process of the GreenValve, a modified passive model is proposed in this paper. The model is based on the idea of incoming flow induced rotor rotation and on a modification of the 6-DOF model that takes into account the added mass of the fluid. Based on the model, the energy harvesting characteristics and fluid regulation characteristics of the GreenValve with a modified Savonius runner with different number of blades and hollow ratios are investigated. Numerical results show that at an inlet flow rate of 15.7 × 103 m3/s, with the increase in the number of blades, the movement of the runner tends to be smooth, and the power and efficiency of the GreenValve gradually increases, up to 245 W of power and 13.6% of efficiency; the increase in the hollow ratio from 0.25 to 0.33 improves the overall performance of the GreenValve. • A control valve with energy harvesting is investigated. • Provide power supply for monitoring equipment in pipe network far from the grid. • A modified passive model is proposed to simulate the non-stationary state of GreenValve. • The performances of different shapes and structures are compared and analyzed. [ABSTRACT FROM AUTHOR]

The Electric Vehicle(EV) charging station frequently participates in the daily regulation and operation of the power distribution system, whether the installation position is reasonable and the configuration capacity is appropriate, it will directly affect the operation strategy and operating conditions of the distribution system, and then affect the economic and environmental benefits of the distributed power supply and EV load connected to the power grid, based on the analysis of fuel vehicles, EV travel characteristics and electrical geography coupled state, by fitting the charging data of EV with travel chain, more accurate EV charging load can be obtained. Secondly, the optimal allocation model of EV charging stations is established to optimize the grid loss, and the nonconvex problem is solved by combining the second-order cone relaxation technique with the distflow power flow model, the configuration scheme of EV charging station is obtained. Finally, taking an EV charging scene in a certain area as an example, the optimal configuration of the charging station is simulated by setting up two types of charging station: conventional charging station and conventional charging station and fast charging station, the effectiveness of the proposed configuration scheme is verified. The optimal configuration scheme of EV charging station described in this paper provides a theoretical basis for charging station planning and capacity expansion. • The EV charging load forecasting based on trip chain is established. • Optimized configuration of EV charging stations. • The second-order cone relaxation method is used to realize the matching between charging resource and charging demand. [ABSTRACT FROM AUTHOR]

The electricity mix in Tunisia mainly relied on conventional energy sources for over 50 years. Recently, due to fossil fuel prices oscillations and national reserves shortage, the need arose for restructuring the energy supply system. Targeting the integration of renewable energies could be a plan for satisfying the increasing demand and the supply independence. However, several macroeconomic conditions and policies present barriers for the integration of Renewable Energy Sources (RES), despite their abundance, availability and environmental benefits. This paper presents a long-term model of Tunisia electricity system, based on OSeMOSYS (Open Source energy MOdelling SYStem), aimed at unveiling potential benefits of increasing RES in electricity production. The paper first investigates peculiarities of Tunisia electricity system, arguing the necessity to include them in the electricity system model. Then, it explains the choice of OSeMOSYS and brought modifications, including peculiar system characteristics. Finally, the model is applied to two scenarios, a Business As Usual case and a 30% RES target in electricity production case, for time horizon 2010–2030. Results demonstrate the importance of system features detailed modelling. Specifically, they show that targeting RES state-invested integration in the electricity mix may allow higher energy independence to be reached, without increasing significantly system costs. [ABSTRACT FROM AUTHOR]

Brazil has an energy system with a hydrothermal characteristic that interconnects consumers and generators covering 98% of the demand for energy supplies. Most of the plants are concentrated in the southeast region, where the largest consumers and the largest population concentration are located. The expansion of this system, considering the hydroelectric contributions, will occur exploring the potentials located in the Amazon region. This analysis paper shows that the variations imposed by climate changes on some climatological variables create significant uncertainties about the power generation forecasts of the hydroelectric power plants to be installed in the Amazon, thus compromising the financial economic feasibility of these enterprises and also possibly compromising the expansion plans of the Brazilian energy system. The methodological approach uses information from various climate change scenarios and compares those with historical hydrological patterns and generation information. By exploring the characteristics of a large-scale hydrothermal system with high dependence on water resources, this paper provides valuable insights on how energy policy would address hydroelectric vulnerabilities and climate change. This analysis is focused on the Brazilian case but reveals important issues related to systems with hydro thermal characteristics. [ABSTRACT FROM AUTHOR]