International Journal of Global Energy Issues (26 papers in press)

Regular Issues

• Evaluating the dynamic effect of oil and exchange rate on food prices: a fresh insight from OECD countries using panel ARDL estimation  
  by Maryum Sajid Raja, Orhan Şanli, Aslı Yenipazarli, Laeeq Janjua, Atteeq Razzak 
  Abstract: The purpose of this study is to reveal the effect of oil prices and exchange rates on food prices in OECD countries. Food prices are usually determined by the exchange rate of the currency or either oil prices. Therefore, this paper questions the food price-exchange rate-oil prices trilemma by presenting empirical evidence from a panel of 38 OECD countries. ARDL bounds test and Granger causality methods were used for empirical analysis. Results suggest the increase in food prices in sample countries is associated with the exchange rate and energy prices. The exchange rate effect should be considered an important parameter in terms of energy costs and global food inflation. According to Dumitrescu-Hurlin panel causality tests results there is a strong bidirectional causality relationship between food prices and crude oil prices and exchange rates. These results indicate that exchange rates and crude oil prices are important variables that determine food prices.
  Keywords: energy; oil prices; food prices; exchange rate; OECD countries.
  DOI: 10.1504/IJGEI.2024.10064061
   
  
• Prioritisation for electric utility expansion scenarios in Maharashtra, India, using analytical hierarchical approach  
  by S.D. Pohekar, Rajesh Kale 
  Abstract: Maharashtra is the second-largest and prominent state in India with an industrial and service sector economy consuming 12% of India's electricity. This paper forecasts electricity demand for 2030 using Long Range Energy Alternatives Planning (LEAP) and generates seven electricity scenarios. The study utilises the Analytical Hierarchy Process (AHP) algorithm for priority setting, employing a three-level hierarchical structure. Scenarios are ranked based on four main criteria and 25 sub-criteria, incorporating inputs from three stakeholder groups: electricity planners, utility officers and end users. The preferred scenario is Business as Usual (BAU), followed by the Energy Conservation (EC) scenario. Sensitivity analysis studies explore future implications for the identified scenarios. While the Least Cost Scenario (LCS) and Zero Emission Scenario (ZES) are highly desirable, the addition of significant infrastructure remains a concern for these scenarios.
  Keywords: analytical hierarchy process; electricity scenarios; prioritisation; electric utility expansion.
  DOI: 10.1504/IJGEI.2025.10067981
   
  
• Implementation plan and impact of natural gas pipeline network transformation from volume metering to energy metering in China  
  by Jun Zhou, Pan Zhou, Cui Liu, Yixiong Qin, Guangchuan Liang 
  Abstract: The volume-based natural gas measurement system not only fails to accurately reflect the value of natural gas but also hinders fair trading and the long-term development of the market. This paper proposes specific implementation schemes for energy measurement systems from three aspects. It presents two methods for converting natural gas prices from volume measurement to energy measurement and three selection methods for reference heating values, resulting in a total of six combined implementation schemes. Taking a certain operational long-distance pipeline as an example, a simulation model is established using SPS to investigate the impact of the transition from a volume-based metering system to an energy-based metering system on the economic benefits of pipeline operator.
  Keywords: natural gas; energy measurement; pipe network simulation; caloric value.
  DOI: 10.1504/IJGEI.2025.10067979
   
  

Special Issue on: Energy Saving Technology in Building

• Optimisation method of residential building energy conservation in hot summer and cold winter areas: particle swarm optimisation  
  by Wen Cao 
  Abstract: In this paper, an optimisation method of residential building energy conservation in hot summer and cold winter areas based on particle swarm optimisation algorithm is studied. First, considering the influence of external and internal factors of the residential environment and the change of energy consumption, select the energy-conservation parameters of residential buildings; Finally, the particle swarm optimisation algorithm is introduced to build the optimisation model of building energy conservation, and the optimisation results are corrected by inertia weight to complete the design. The test results show that the energy consumption of this method is 2796 KWh, the correlation coefficient is higher than 0.95, and the optimisation time is 1.27 s. This method can effectively reduce the energy consumption of residential buildings, and the optimisation speed is faster.
  Keywords: particle swarm optimisation algorithm; hot summer and cold winter areas; residential building; energy saving optimisation; particle fitness.
  DOI: 10.1504/IJGEI.2024.10062749
   
  
• An optimisation method for energy efficiency of residential buildings in cold regions based on genetic algorithm  
  by Dongmei Zhao, Gaoxian LI, Yifan Wu 
  Abstract: Owing to the high-energy consumption of residential buildings in cold regions, a genetic algorithm-based optimisation method for energy efficiency of residential buildings in cold regions is proposed. Firstly, identify the factors that affect the energy efficiency of residential buildings in cold regions and clarify the energy consumption of buildings; Then, select energysaving parameters for residential building orientation, exterior wall thickness and window to wall ratio, and use these parameters as optimisation indicators; Finally, the energy-saving parameters are encoded to generate an initial population, and the optimised energy-saving parameter operators are selected, crossed and mutated. A building energy-saving optimisation algorithm based on genetic algorithm is designed to achieve optimisation research. The test results show that the proposed method can effectively reduce building energy consumption in cold regions, and the wall to window ratio has a better shading coefficient.
  Keywords: genetic algorithm; cold regions; optimisation of building energy efficiency; building orientation; outer wall thickness; window to wall ratio; sunshade coefficient.
  DOI: 10.1504/IJGEI.2024.10062750
   
  
• A method for monitoring energy consumption data of near zero energy buildings based on BIM technology  
  by Ye Liao 
  Abstract: In order to improve the accuracy of monitoring energy consumption data of near zero energy buildings, this paper proposes a monitoring method for energy consumption data of near zero energy buildings based on BIM technology. Firstly, a near zero energy consumption building BIM model database including family file library and database is established. Secondly, the three-dimensional BIM model is constructed using Ecotect Analysis software. Then, the building energy consumption data output from the BIM model is analysed with the decision tree Analysis of algorithms; Finally, the momentum factor is used to optimise the BP neural network model, and the processed energy consumption data is used as the input of the BP neural network to output the monitoring results of near zero energy consumption building energy consumption data. The experimental results show that the application of this method can accurately monitor short-term and short-term energy consumption data for buildings with near zero energy consumption, and its monitoring error is less than 15 kW h, which has great application value.
  Keywords: BIM technology; near zero energy consumption buildings; energy consumption data; monitoring methods; family file library; momentum factor.
  DOI: 10.1504/IJGEI.2024.10062751
   
  
• Energy saving control method for central air conditioning systems in public buildings based on improved particle swarm optimisation  
  by YanHua Lou 
  Abstract: In order to reduce the energy consumption of central air conditioning system in public buildings, an energy-saving control method based on improved particle swarm optimisation was proposed. This method first analyses the structure and control principle of the central air conditioning system of public buildings, and obtains the result that the air conditioning system flow can be controlled by frequency conversion and speed regulation to reduce energy consumption. Then, on this basis, the energy-saving control problem is transformed into an optimisation problem, and the objective function is designed to complete the establishment of the energy-saving control model of the central air conditioning system. Finally, the solution is completed based on the improved particle swarm optimisation algorithm. The optimal scheme of multi-device variable frequency speed regulation that can minimise energy consumption is obtained. By controlling the water flow rate and fan speed of the central air conditioning system, the energy saving control of the central air conditioning system is completed. The test shows that the energy consumption of each equipment in the air conditioning system is reduced by 20.3 to 1.2% after using this method, which is superior to the comparison method and has great application value.
  Keywords: improving particle swarm optimisation; public buildings; central air conditioning system; energy saving control; variable frequency speed regulation; counter.
  DOI: 10.1504/IJGEI.2024.10062752
   
  
• Maximum power tracking method for roof solar cells in intelligent buildings based on particle swarm optimisation  
  by Yingjie Wang, Caihong Chu 
  Abstract: The maximum power tracking of the rooftop solar cells of intelligent buildings cannot be tracked quickly when the effective photovoltaic array is under uniform illumination because of the slow convergence speed. Therefore, a new method of maximum power tracking of the rooftop solar cells of intelligent buildings based on particle swarm optimisation algorithm is proposed. Firstly, the solar cell model is established, and the influence factors of temperature and light intensity are identified as the factors affecting the tracking effect. Then, the particle swarm optimisation algorithm is introduced to determine the initial position of the battery power parameters. Finally, based on the particle swarm optimisation algorithm, the maximum power tracking of solar cells on the roof of intelligent buildings is realised by solving the function repeatedly. The results show that the proposed algorithm has higher tracking accuracy and better dynamic response ability, and the tracking accuracy is improved by 3.7% and the maximum power point can be tracked again in a short time.
  Keywords: mathematical model of photovoltaic cells; I-U characteristic equation; guided wave function; particle swarm optimisation; maximum power point tracking.
  DOI: 10.1504/IJGEI.2024.10062753
   
  

Special Issue on: Renewable Energy, Innovations, Energy and Economic Security

• Energy consumption and climate change in Sub-Saharan Africa (SSA)  
  by A. Akinyemi Ajibola, Wisdom Okere, Oreoluwa Adedeji, Obiajulu Chibuzo Okeke, Cynthia Okere 
  Abstract: This study analysed energy consumption and climate change in SSA to validate the Environmental Kuznet Curve (EKC) theory. This study included multiple econometric tests, Autoregressive Distributed Lagged model (ARDL), Fully Modified Ordinary Least Squares (FMOLS) regression analysis and Granger Causality Test. In the long run, Gross Domestic Product (GDP) and Electricity consumption (ELE) have a positive and significant relationship with climate change, measured by carbon dioxide emissions, while Fossil energy consumption (FOS) and Renewable Energy Consumption (REN) do not. ELE has a positive relationship with climate change as assessed by carbon dioxide emissions, while FOS and REN have a negative association. Only the ELE and FOS coefficients are significant at 5%. Since fossil fuels and renewable energy do not contribute to long-term climate change, energy consumption patterns have started to reflect their environmental policies. More eco-friendly techniques are needed to reduce electricity's environmental impact. The EKC theory found that SSA countries are evolving so that economic growth's negative effects on climate change will be reversed. The study advises policymakers to adopt renewable energy to cut carbon dioxide emissions.
  Keywords: climate change; carbon dioxide emission; energy consumption; Sub-Saharan Africa; sustainability.
  DOI: 10.1504/IJGEI.2024.10061362
   
  
• Economic and environmental drivers of physical safety in Central Europe  
  by Oleksandra Karintseva, Oleksandra Kubatko, Oleksandr Derykolenko, Vitaliy Omelyanenko, Victoria Sulym, Anastasiia Yaremenko 
  Abstract: Physical safety is not only about the actual safety of humans but also their mental health and calmness. The article examines the key drivers of people's physical safety, well-being and satisfaction with life. The study covers seven Central European countries during 2011-2018. The random effects estimations for the panel data are used for empirical estimations. The study found that crime/violence, unemployment and noise from neighbours negatively impact individuals' physical safety. The empirical results proved that an increase in median income by 1000 euros in Central European states promotes an increase in life expectancy by 0.7 years. However, if unemployment rises by 10%, the decline in life expectancy would range from 0.7 to 1.19 years. The paper proves that the marriage factors like indicators of moral factors are an inevitable part of a healthy society. Noise from the neighbours is considered to be an object of irritation and reduces the level of physical safety of EU citizens. Thus, governments need to stay on top of the problems mentioned above to cope with them.
  Keywords: physical safety; economic development; well-being; life satisfaction.
  DOI: 10.1504/IJGEI.2025.10067975
   
  
• The impact of innovations and intellectualisation on sustainable national development  
  by Oleksandr Kubatko, Rytis Krušinskas, Leonid Melnyk, Bohdan Kovalov, Pavlo Denysenko 
  Abstract: Innovations are an integral part of the modern global economy. The purpose of this research is to investigate impact of innovations and intellectualisation on sustainable national development. Based on the World Bank sets, two models with panel data from selected economies (Bulgaria, the Czech Republic, Hungary, Kazakhstan, Poland, Romania, Moldova, the Slovak Republic, Ukraine and Uzbekistan) in 2006-2018 were built. Using random-effects GLS regression it was proved that factors of intellectualisation and innovations (both exogenous and endogenous) increase the level of economic growth. Empirical results proved that intellectualisation of the economy of endogenous origin is one of the stimulators of improving the environmental situation (when there is an increase in the number of researchers in the country by 100 people, the amount of carbon dioxide per capita decreases by 84-131 kg), while exogenous intellectualisation turned out to be a statistically insignificant factor. The paper proved several decarbonisation drivers, which include energy efficiency and life expectancy. Following the results, policy recommendations were provided and indicated the importance of national education development and innovation fostering. This can be achieved by revising learning standards according to market requirements, retraining educators and using a competence-based approach.
  Keywords: innovations; intellectualisation; sustainable development; sustainability; economic growth; carbon dioxide emissions.
  DOI: 10.1504/IJGEI.2025.10067976
   
  
• Military and economic prerequisites for transforming the energy supply of the housing sector of Ukraine based on Industry 3.0  
  by Oleksandr Matsenko, Leonid Melnyk, Yevhen Skrypka, Iryna Dehtyarova, Serhiy Kozmenko, Liudmyla Kalinichenko 
  Abstract: The paper investigates the direction of the transformation of the energy supply of the residential sector of Ukraine as a result of the aggression of the Russian Federation and the significant destruction of the energy infrastructure. The paper aims to investigate the sustainability of the energy supply of the residential sector in Ukraine and propose directions for its transformation. The research method is based on analysing the state of Ukraine's residential sector's energy supply system and identifying the possibilities of its change into martial law conditions. The research examines the Ukrainian economy and infrastructure losses. Two alternative options for ensuring the energy dependence of the residential industry are suggested. The main measures to save energy and electricity for the population of Ukraine are presented step by step.
  Keywords: energy independence; energy efficiency; economy; residential sector; house; construction; modernisation; war; martial law.
  DOI: 10.1504/IJGEI.2024.10061968
   
  
• Industry 4.0: the transformation of management systems and influence tools  
  by Larysa Shaulska, Hanna Bei, Galina Zaharieva, Andrey Zahariev 
  Abstract: The article focuses on management system transformation, considering changes caused by the technological renewal of enterprises due to the standards of Industry 4.0. The aim of the article is to explore how enterprise management systems change in response to Industry 4.0 technologies and to identify effective management influence tools within the 'smart' ecosystem. Method of scientific systematisation was applied to categorise key aspects of management tools transformation in Industry 4.0, namely technological, human, organisational and behavioural aspects. Results cover changes across corporate, functional and individual levels. The source of empirical data was semi-structured in-depth expert interviews with managers of selected enterprises in Ukraine and Bulgaria that are in the process of transition to a 'smart' ecosystem. All data was analysed using qualitative content analysis. The main findings reveal targeted aspects of management system transformation in Industry 4.0 to be done in the early stage. Originality of the article is among the first to give specific examples of management system transformation in Industry 4.0 aimed to accelerate overcoming of existing implementation barriers.
  Keywords: Industry 4.0; management; management system; influence tools; digitalisation; transformation; technologies; behaviour.
  DOI: 10.1504/IJGEI.2025.10067977
   
  
• Energy technology efficiency influence on energy poverty and energy justice in West African households  
  by Evrard Karol Ekouédjen, Safiou Bouraima, Gaston Ganhoun, Latif Adéniyi Fagbemi 
  Abstract: This paper presents a new indicator which measure energy poverty (as energy justice component) called Modified Energy Poverty Index (MOEPI). It is a composite index and developed based on United Nations Human Development Index (HDI) methodology. MOEPI defines energy poverty as three dimensions conjunction: excessive energy inconvenience, energy deficit and equipment energy (in)efficiency. It captures energy deficit effect on education and include energy acquisition cost in energy inconvenience assessment. MOEPI is implemented on a sample of 640 households in Benin. Results showed 65.15% energy poor households surveyed. Energy poor are divided into three sub-groups, slightly energy poor (6%), moderate energy poor (53%) and severe energy poor (41%). Energy deficit and equipment energy inefficiency are the main dimensions responsible for household energy poverty. An improvement in equipment energy efficiency resulted in a 32.02% decrease in the number of energy poor households.
  Keywords: energy efficiency; energy poverty; energy justice; index; energy deficit; energy inconvenience.
  DOI: 10.1504/IJGEI.2025.10067978
   
  
• A case for replacing local generators by a service using only renewable energy sources in the city of Sulaymaniyah  
  by Hariam Luqman Azeez, Banw Omer Ahmed, Ali H.A. Al-Waeli 
  Abstract: Despite the abundance of oil and gas reserves in the Kurdistan region, a critical challenge persists in fully meeting the region's electricity demand. Local investors, recognising the daily shortfall of electricity in homes lasting six to eight hours, have introduced diesel generators to bridge the gap. Presently, each neighbourhood relies on multiple diesel generators to address the electricity deficit. However, these local generators pose significant issues, including inadequate power supply, substantial pollution, noise emissions, high-fuel consumption and an unsightly appearance. Given the region's suitability for renewable energy, coupled with the intermittent nature of electricity demand, there arises a logical opportunity to develop a service as an alternative to local generators. This paper aims to explore the viability of such a service, intending to replace local diesel generators with a renewable energy solution. The study undertakes the following tasks: (i) conducting a life cycle assessment of local diesel generators to evaluate their environmental impact, cost-effectiveness and social acceptability, (ii) assessing the potential of Sulaymaniyah for renewable energy applications, particularly solar photovoltaic (PV) panels and wind turbines and (iii) incorporating a neighbourhood survey in Sulaymaniyah to gauge resident opinions and reactions toward the proposed renewable energy service.
  Keywords: local diesel generators; renewable energy service; cost analysis; social considerations; environmental impact analysis.
  DOI: 10.1504/IJGEI.2024.10062449
   
  
• Trade-offs between energy, the economy, amenity, and education: findings from Indonesia  
  by Nugroho Agung Pambudi, Ahmad Fauzi Nasrulloh, Muhammad Kunta Biddinika, Andrew John Chapman, Bernard Saw Lip Huat 
  Abstract: This study examined the trade-offs among energy, the economy, amenity and education concerning the implementation of renewable energy in Indonesia. The objective was to offer a comprehensive understanding of the economic and environmental advantages associated with renewable energy and to investigate the role of education in fostering social acceptance. The data was obtained by conducting a survey among local tourists at Pangandaran Beach in Indonesia, using random sampling techniques. The research assesses the level of acceptance regarding the potential integration of wind turbines, consistent with the national energy system development policy. The results show that there is a well-informed stakeholder group who have positive toward the deployment of wind turbines. Meanwhile, some objections were raised against visual impacts, but most tourists felt that wind turbine deployment would not inconvenience or have major impacts on marine ecosystems. Furthermore, this study discussed the challenges related to stakeholder engagement in energy policy development. It also provided a contrast by comparing findings from other countries and identified potential knowledge gaps specific to the Indonesian case.
  Keywords: wind turbines; amenity; visual impact; coastal tourism; developing nation.
  DOI: 10.1504/IJGEI.2025.10067980
   
  

Special Issue on: The Analysis of Energy Efficiency Perspectives and Policies towards Sustainable Development

• Robust and efficient hybrid autoencoder-ADAM (HAA) algorithm for analysing anomalies in Indian electricity consumption data  
  by M. Ravinder, Vikram Kulkarni 
  Abstract: Anomaly detection in electricity-consumption data plays a crucial role in ensuring the reliability and stability of modern smart-grid systems. In this study, we propose the Hybrid Autoencoder-ADAM (HAA) algorithm, specifically designed for anomaly detection in Indian electricity consumption data from 2014 to 2023, considering distinct seasonal patterns. The HAA algorithm combines autoencoders with adaptive optimisation (ADAM) to effectively capture and reconstruct normal consumption patterns. Comparative analysis show that the HAA algorithm outperforms Long Short-Term Memory (LSTM) and XGBoost in accuracy and robustness for anomaly detection. It demonstrates adaptability across different seasons, regions and periods, offering valuable insights for advancing smart grid analytics and energy conservation strategies. Future research includes hyper-parameter optimisation and exploring ensemble methods to enhance its real-world applicability in operational smart-grid scenarios. The HAA algorithm presents a promising approach for large-scale smart grid anomaly detection, emphasising its efficiency and effectiveness in improving energy management and resource optimisation.
  Keywords: anomaly detection; HAA algorithm; smart grid; electricity consumption; LSTM; XGBoost; seasonal patterns.
  DOI: 10.1504/IJGEI.2024.10062681
   
  
• Collaborative planning method for integrated energy system based on improved compressed sensing algorithm  
  by Yan Li, Xiaojun Zhu, Qingshan Wang, Qiong Wang, Na Li, Yinzhe Xie, Zhu Chen 
  Abstract: Aiming at the problems of high-energy cost, high-energy consumption and environmental pollution in existing methods, a collaborative planning method for integrated energy systems based on improved compressed sensing algorithm is proposed. Build a comprehensive energy system architecture that includes modules for energy production, storage and conversion, transmission and distribution, consumption and management. Establish a collaborative planning mathematical model based on the characteristics of the architecture, set three objective functions: total energy consumption, total cost and total pollutant emissions, and set corresponding energy consumption, cost and environmental protection constraints. The improved compressed sensing algorithm is used for the integrated energy system collaborative planning, and the optimal solution is output, which is the optimal integrated energy system collaborative planning scheme. The experimental results show that the proposed method effectively reduces energy costs and energy consumption, and significantly reduces carbon dioxide emissions, indicating that the proposed method has practical value.
  Keywords: improved compressed sensing algorithm; integrated energy system; search for updates; constraint condition.
  DOI: 10.1504/IJGEI.2024.10063314
   
  
• A data-driven energy consumption prediction method for building electrical equipment based on data-driven  
  by Xiulan Yin, Huiting Liang 
  Abstract: A data-driven energy consumption prediction method for building electrical equipment based on data-driven is proposed to address the issues of unstable prediction results and low accuracy in existing methods. Multiple sensors are selected to collect voltage, power, temperature and humidity data of electrical equipment. The mean filling method is used to fill in the missing values of the collected data. The K-means algorithm is used to detect anomalies in the filled data, identify and remove abnormal clusters or samples. Based on the data processing results, particle swarm optimisation algorithm is used to train energy consumption data, construct an energy consumption prediction model and achieve energy consumption detection through this model. The experimental results show that the highest prediction accuracy of this method is 98.5%, and the difference between the predicted results and actual energy consumption is small, indicating that the stability and robustness of this method are strong.
  Keywords: data-driven; electrical equipment; energy consumption prediction; multiple sensors; k-means algorithm; particle swarm optimisation.
  DOI: 10.1504/IJGEI.2024.10063315
   
  
• Optimisation of solar thermal photovoltaic heating systems for buildings considering stability  
  by Hongwei Jia 
  Abstract: In order to improve its power generation efficiency and output power, and ensure the sustainability and stability of the system, the optimisation study of building solar thermal photovoltaic heating system considering stability is carried out this time. This method first analyses the operating principle of photovoltaic heating systems used in buildings, then constructs an output power model of the photovoltaic heating system, and fully considers the stability of the heating system operation to design an objective function. Finally, based on the improved Particle Swarm Optimisation with Adaptive Elite Strategy Algorithm (PSO-AESA) algorithm, the output power model of the photovoltaic heating system is solved, Realise optimal control of photothermal photovoltaic heating systems for buildings. The experimental results show that the total power generation efficiency and output power of the heating system are higher after the proposed method is used to optimise the control. The system control is better than the comparison method, and has high-application value.
  Keywords: stability; photothermal photovoltaics; heating system; control optimisation; source load energy storage.
  DOI: 10.1504/IJGEI.2024.10063316
   
  
• Intelligent scheduling optimisation strategy for comprehensive energy systems  
  by Kun Yan, Hongwei Dong, Tao Han, Jin Zhu 
  Abstract: In order to improve the output of integrated energy system and reduce the high-operation cost, a coordinated optimal scheduling method based on improved genetic algorithm was proposed. Aiming at the problems of poor output and high operating cost after the application of existing energy system scheduling methods, an integrated coordinated optimal scheduling method based on improved genetic algorithm is proposed. Firstly, the structure of the integrated energy system is analysed, and then the output of wind turbine, incentive demand response, gas turbine, etc., is analysed, and the output model of the integrated energy system is built. Finally, the optimal scheduling model of the energy system is established, and the improved genetic algorithm is used to solve it, and the optimal scheduling of the integrated energy system is realised. The experimental results show that the system output is the best, the operation cost is the lowest, and it can meet the operation requirements of the integrated energy system.
  Keywords: improved genetic algorithm; integrated energy system; coordination and optimisation; scheduling algorithm.
  DOI: 10.1504/IJGEI.2024.10063317
   
  
• Capacity configuration method for new energy storage system based on segmented peak shaving  
  by Zesen Li, Bingjie Li, Guojing Liu 
  Abstract: To overcome the problems of low accuracy in capacity estimation, low balancing degree and low utilisation rate in traditional methods, a capacity configuration method for new energy storage system based on segmented peak shaving is proposed. The battery internal resistance and terminal voltage signals of the new energy storage system are taken as inputs, and the capacity estimation is the output. A capacity estimation model based on an improved fuzzy neural network is established. The capacity configuration objective function is constructed by combining segmented peak shaving and economic cost. Hybrid frog-leaping algorithm is used to obtain the optimal parameters for segmented peak shaving and economic cost through population initialisation, position updates and frog swarm sorting to determine the optimal configuration scheme. Experimental results show that the average accuracy of capacity estimation using this method is 97.31%, the maximum balancing degree is 0.98 and the minimum utilisation rate is only 90.9%.
  Keywords: segmented peak shaving; new energy storage system; capacity configuration; improved fuzzy neural network; hybrid frog-leaping algorithm.
  DOI: 10.1504/IJGEI.2024.10063318
   
  
• A demand side energy scheduling method for energy-saving buildings based on priority weights  
  by Yining Sun 
  Abstract: In order to improve the voltage stability of energy scheduling and shorten scheduling time, a priority weighted demand side energy scheduling method for energy-saving buildings is proposed. Firstly, analyse the demand side incentive response behaviour of energy-saving buildings through load superposition. Secondly, construct priority decision-making indicators for energy scheduling. Construct a hesitant fuzzy matrix and calculate the membership score, and calculate the correlation coefficient between priority indicators. Finally, based on the correlation coefficient of the indicators, priority weights are calculated, and on the basis of normalised calculation of priority weights, an energy scheduling function is constructed to transform the scheduling engineering problem into a mathematical problem, solving the scheduling function to complete the demand side energy scheduling of energy-saving buildings. The experimental results show that the proposed method can shorten the time of energy scheduling, and the maximum scheduling time of the proposed method does not exceed 4 minutes.
  Keywords: priority weight; energy-saving building; demand side; energy scheduling.
  DOI: 10.1504/IJGEI.2024.10063319
   
  
• An evaluation of low-carbon collaborative emission reduction effect of new energy wind and solar power generation based on set pair analysis  
  by Peidong He, Xiaojun Li, Shijiong Yuan, Keli Liu, Xiaoxiao Yang 
  Abstract: In order to overcome the problems of poor accuracy and poor evaluation of emission reduction effects, this article introduces set pair analysis to evaluate the low-carbon collaborative emission reduction effect of new energy solar power generation. Firstly, construct an evaluation index system; Then, the subjective weight of the indicators is calculated using the intuitive fuzzy analytic hierarchy process, the objective weight is calculated using the entropy weight method and the comprehensive weight value of the indicators is calculated using game theory; Finally, the emission reduction effect evaluation function is constructed using set pair analysis theory, and the evaluation level is determined using confidence to obtain the final evaluation result. The results show that the evaluation accuracy of the method in this paper can reach 99.5%, and this method can accurately evaluate the low-carbon collaborative emission reduction effect of new energy wind power generation.
  Keywords: set pair analysis; new energy; wind and solar power generation; low carbon; collaborative emission reduction; effect evaluation.
  DOI: 10.1504/IJGEI.2024.10063320
   
  
• Optimisation method for economic dispatch of wind power connected to microgrid considering carbon emission  
  by Hui Li, Xin Wen, Zhengyang Peng, Jing Zhang, Shitao Chen 
  Abstract: In order to improve the economic dispatching effect of distribution network, the optimisation method of economic dispatching of wind power connected to microgrid considering carbon emissions is studied. Firstly, taking the minimum operating cost and environmental cost of wind power connected to microgrid as the design goal, and fully considering equality constraints and inequality constraints, an economic scheduling optimisation model of wind power connected to microgrid is constructed. Then, the improved particle swarm optimisation algorithm is used to solve the economic scheduling optimisation model of wind power connected to microgrid, and the economic scheduling optimisation is realised. Finally, the practicability of the proposed method is proved by experiments. The experimental results show that this method has strong calculation ability and good iterative performance in model solving, and the application of the proposed method can get more ideal economic dispatching effect and has high application value.
  Keywords: carbon emissions; wind power access; microgrid; economic dispatch optimisation; particle swarm optimisation; abandoned air volume.
  DOI: 10.1504/IJGEI.2024.10063321
   
  
• High proportion new energy grid voltage fluctuation tracking method based on double layer master slave game  
  by Yiming Peng, Mingdong Guan, Dongxu Li, Jia Wang, Hanzhi Zhang 
  Abstract: In order to reduce the error of voltage fluctuation tracking and shorten the tracking time, a high proportion new energy medium voltage power grid voltage fluctuation tracking method based on a double layer master slave game is proposed. Firstly, construct a two-layer master-slave game model, analyse the voltage regulation strategy of the high proportion new energy grid using the utility function, and collect operational data of the new energy grid. Secondly, wavelet transform is used to analyse the sudden changes in voltage signals and identify the sources of voltage fluctuations in the medium voltage power grid. Finally, the Hilbert Huang transform is used to decompose the voltage fluctuation source signal, obtain the instantaneous fluctuation frequency of the power grid voltage and complete the tracking of voltage fluctuations. The results show that the voltage fluctuation tracking error of the proposed method is significantly reduced, with a maximum error of only 1.3 V.
  Keywords: double layer master slave game; high proportion; new energy grid; voltage fluctuation tracking; medium voltage distribution network.
  DOI: 10.1504/IJGEI.2024.10063322