Template-Type: ReDIF-Article 1.0 Author-Name: Brijesh Bhatt Author-X-Name-First: Brijesh Author-X-Name-Last: Bhatt Author-Name: A.K. Tripathi Author-X-Name-First: A.K. Author-X-Name-Last: Tripathi Author-Name: G.C. Tripathi Author-X-Name-First: G.C. Author-X-Name-Last: Tripathi Title: The convoluted path of power sector reforms: underutilised generation capacity - a new challenge for Indian thermal power generators Abstract: India embarked upon the path of power sector reforms in 1991. With subsequent steps like opening up of private investment in generation, unbundling, open access, power trading and many other structural % policy initiatives for generation, transmission and distribution, it aimed to promote competition in the sector. In a country facing chronic power shortages, one of the key objectives of these reform initiatives has been to ensure an optimal investment in generation capacity as well as optimal capacity utilisation for the generation sector. Against this backdrop, we studied the evolution of generation capacity in the country, with focus on three aspects, namely, fuel-source wise, ownership wise, and region wise capacity addition. We also analysed how effectively the capacities are being utilised. The analysis revealed two significant results: (1) there is considerable stranded capacity which does not get through to the grid and (2) there is also significant capacity which is grid connected and commercially available, but is producing at very low Plant Load Factor (PLF). In a country which faces power deficit, such a situation is a matter of great concern. To ensure sustainable energy supply system, these issues need to be addressed through appropriate interventions. Journal: Int. J. of Global Energy Issues Pages: 328-362 Issue: 4 Volume: 44 Year: 2022 Keywords: Indian power sector; reform; generation; capacity; private investment; regulation. File-URL: http://www.inderscience.com/link.php?id=123947 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijgeni:v:44:y:2022:i:4:p:328-362 Template-Type: ReDIF-Article 1.0 Author-Name: Umair Kashif Author-X-Name-First: Umair Author-X-Name-Last: Kashif Author-Name: Chen Hong Author-X-Name-First: Chen Author-X-Name-Last: Hong Author-Name: Snovia Naseem Author-X-Name-First: Snovia Author-X-Name-Last: Naseem Author-Name: Muhammad Waqar Akram Author-X-Name-First: Muhammad Waqar Author-X-Name-Last: Akram Author-Name: Muhammad Saeed Meo Author-X-Name-First: Muhammad Saeed Author-X-Name-Last: Meo Title: Impact of oil price fluctuations on food prices: fresh insight from asymmetric ARDL approach of co-integration Abstract: The current study analyses the asymmetric effects of oil prices on food prices in Pakistan from 1977 to 2017. ADF, PP, and KPSS root unit tests were used to substantiate data stationarity, while nonlinear autoregressive distributed lags (NARDL) were utilised for asymmetry testing. The NARDL results confirm co-integration and show a strong positive impression of oil price rise to food prices in the long-run. In the meantime, a decline in oil prices relationship with food prices is absent and inconsequential. Additionally, positive changes in oil prices have a considerable role in food prices only in the short-run. Due to the absence of the significant influence of oil prices reduction at food prices in the short-run and long-run, market strength could be essential for forming Pakistan's food value behaviour. Journal: Int. J. of Global Energy Issues Pages: 264-280 Issue: 2/3 Volume: 44 Year: 2022 Keywords: oil price; food price behaviour; exchange rates; asymmetry; NARDL. File-URL: http://www.inderscience.com/link.php?id=121389 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijgeni:v:44:y:2022:i:2/3:p:264-280 Template-Type: ReDIF-Article 1.0 Author-Name: You Zhou Author-X-Name-First: You Author-X-Name-Last: Zhou Author-Name: Yu Liu Author-X-Name-First: Yu Author-X-Name-Last: Liu Author-Name: Yuan Li Author-X-Name-First: Yuan Author-X-Name-Last: Li Title: Research on the energy-saving effect evaluation of open-pit coal mines based on energy audit Abstract: Energy conservation is a long-term strategic policy of China's economic development, and the issue of energy resources has become a strategic issue in country's economic development. At present, the management level of open-pit coal mine is relatively low, and energy audit is less carried out, energy audit provides data analysis, benchmarking management, technical reform suggestions and other contents for the current energy consumption of enterprises, which can increase the energy management of enterprises and reduce energy waste. This study takes the open-pit coal mine as an example, the research shows that energy consumption in the transportation process of an open-pit mine is the highest, most of which comes from diesel oil. Optimising truck transportation routes and reducing truck waiting time are the most important ways to save energy in open-pit mines. The highest are the annual transportation volume of trucks, the lowest the annual average diesel fuel consumption. The energy consumption monitoring of large electric shovels is necessary. Electric-driven mining and stripping equipment can replace oil with electricity and reduce energy consumption. Journal: Int. J. of Global Energy Issues Pages: 363-378 Issue: 4 Volume: 44 Year: 2022 Keywords: open pit coal mine; energy audit; energy-saving evaluation; energy-saving effect evaluation. File-URL: http://www.inderscience.com/link.php?id=123954 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijgeni:v:44:y:2022:i:4:p:363-378 Template-Type: ReDIF-Article 1.0 Author-Name: Chongyu Cui Author-X-Name-First: Chongyu Author-X-Name-Last: Cui Author-Name: Zhaoxia Li Author-X-Name-First: Zhaoxia Author-X-Name-Last: Li Author-Name: Junjie Zhang Author-X-Name-First: Junjie Author-X-Name-Last: Zhang Title: Building a prediction model of solar power generation based on improved Grey Markov Chain Abstract: In order to improve the prediction ability and reliability management ability of solar power generation, a solar power generation prediction model based on Improved Grey Markov chain is proposed. The constrained parameter model of solar power generation prediction is established, and the disturbance characteristics of solar power generation are analysed. On this basis, the improved grey Markov chain model is applied to the big data fusion analysis of solar power generation, and the reliability prediction of solar power generation is realised. The results show that the prediction accuracy of this method is high, up to 1, which improves the quality and stability of output power, and has certain application value. Journal: Int. J. of Global Energy Issues Pages: 139-149 Issue: 2/3 Volume: 44 Year: 2022 Keywords: grey Markov chain; solar energy; electricity generation; prediction; charge volatility; power grid. File-URL: http://www.inderscience.com/link.php?id=121396 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijgeni:v:44:y:2022:i:2/3:p:139-149 Template-Type: ReDIF-Article 1.0 Author-Name: Feng Liu Author-X-Name-First: Feng Author-X-Name-Last: Liu Title: Real-time monitoring method for working state of decentralised municipal sewage treatment system Abstract: In order to overcome the problems of high monitoring cost and inaccurate monitoring results, a real-time monitoring method for working state of decentralised municipal sewage treatment system is proposed. The experimental platform is used to collect the historical operation data of the decentralised municipal sewage treatment system and obtain the state characteristic parameters of the sewage treatment system. Wavelet transform and principal component analysis are used to pre-process the data of state characteristic parameters. The principal component analysis method is used for multi information fusion, and the fusion information is input into the hidden semi-Markov model to realise the real-time monitoring of the working state of the decentralised municipal sewage treatment system. Simulation results show that the maximum average error and maximum relative error of this method are 0.115 and 0.118, the monitoring cost varies from 10,900 to 12,900 yuan, and the monitoring error and monitoring cost are low. Journal: Int. J. of Global Energy Issues Pages: 247-263 Issue: 2/3 Volume: 44 Year: 2022 Keywords: decentralised; municipal sewage; treatment system; working state; real-time monitoring; hidden semi-Markov model. File-URL: http://www.inderscience.com/link.php?id=121397 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijgeni:v:44:y:2022:i:2/3:p:247-263 Template-Type: ReDIF-Article 1.0 Author-Name: Zhongfeng Jiang Author-X-Name-First: Zhongfeng Author-X-Name-Last: Jiang Author-Name: Hongbin Gao Author-X-Name-First: Hongbin Author-X-Name-Last: Gao Author-Name: Li Wu Author-X-Name-First: Li Author-X-Name-Last: Wu Author-Name: Yanan Li Author-X-Name-First: Yanan Author-X-Name-Last: Li Author-Name: Bifeng Cui Author-X-Name-First: Bifeng Author-X-Name-Last: Cui Title: Purification and recycling of municipal wastewater based on MBR process Abstract: In order to overcome the problems of low purification efficiency and recycling efficiency in traditional municipal wastewater purification and recycling methods, a new municipal wastewater purification and recycling method based on MBR process is proposed in this paper. This paper analyses the principle of MBR process, applies MBR to the design of municipal sewage purification treatment device, uses the device to filter macromolecular pollutants, and realises the municipal sewage purification treatment. Based on the purified municipal wastewater, the municipal wastewater was recycled from three aspects: pH adjustment, phosphorus precipitant selection and sediment SEM analysis. The experimental results show that, compared with the traditional method, this method has higher efficiency of municipal sewage purification and higher recovery rate of water resources, and the total cost of sewage purification and recycling is lower, and the comprehensive benefits are better. Journal: Int. J. of Global Energy Issues Pages: 150-165 Issue: 2/3 Volume: 44 Year: 2022 Keywords: MBR process; municipal wastewater; purification treatment; recycling; pH regulation; phosphorus precipitator; scanning electron microscope. File-URL: http://www.inderscience.com/link.php?id=121398 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijgeni:v:44:y:2022:i:2/3:p:150-165 Template-Type: ReDIF-Article 1.0 Author-Name: Zhe Dong Author-X-Name-First: Zhe Author-X-Name-Last: Dong Author-Name: Xiongying Wang Author-X-Name-First: Xiongying Author-X-Name-Last: Wang Title: Velocity control method of water supply and drainage for multi-functional stadium based on predictive function algorithm Abstract: In order to solve the problems of low calculation accuracy and poor control accuracy of the traditional velocity control methods for water supply and drainage in gymnasiums, a new speed control method for water supply and drainage of multi-functional gymnasiums based on predictive function algorithm is proposed in this paper. In this method, the basis function of water supply and drainage velocity control of multi-functional stadium is constructed, and the reference trajectory of water control is drawn by using predictive function algorithm. The multi-function water supply and drainage model is built to predict and optimise the water supply and drainage capacity of the stadium. The experimental results show that the proposed water supply and drainage velocity control method has a high accuracy of water supply and drainage velocity control, and can accurately calculate the water supply and drainage velocity. Journal: Int. J. of Global Energy Issues Pages: 233-246 Issue: 2/3 Volume: 44 Year: 2022 Keywords: predictive function algorithm; multifunctional stadium; water supply and drainage velocity; control method; reference trajectory. File-URL: http://www.inderscience.com/link.php?id=121399 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijgeni:v:44:y:2022:i:2/3:p:233-246 Template-Type: ReDIF-Article 1.0 Author-Name: Xiaolong Wen Author-X-Name-First: Xiaolong Author-X-Name-Last: Wen Title: Research on an optimisation control method of large-scale buildings energy saving based on particle swarm optimisation Abstract: Aiming at the problems of high energy consumption and low day-lighting coefficient in traditional building energy-saving control methods, an energy-saving optimisation control method for large-scale buildings based on particle swarm optimisation is proposed. Using Autodesk Revit in BIM modelling software the software constructs the large-scale building model, extracts the characteristics of large-scale building organisation information by SIFT method; uses multiple linear regression analysis method to obtain the large-scale building model wall, external window heat transfer coefficient and other parameters, completes the large-scale building operation state analysis; uses particle swarm optimisation algorithm to optimise the large-scale building energy-saving parameters, and obtains its objective function to obtain the large-scale construction Building the optimal energy consumption parameters to achieve large-scale building automation energy-saving control. The experimental results show that: after the energy-saving control of large-scale buildings, the day-lighting coefficient is higher. Journal: Int. J. of Global Energy Issues Pages: 166-181 Issue: 2/3 Volume: 44 Year: 2022 Keywords: BIM technology; large-scale building; automation; energy saving control; multiple linear regression; particle swarm optimisation algorithm. File-URL: http://www.inderscience.com/link.php?id=121400 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijgeni:v:44:y:2022:i:2/3:p:166-181 Template-Type: ReDIF-Article 1.0 Author-Name: Li Wang Author-X-Name-First: Li Author-X-Name-Last: Wang Author-Name: Jing Zhong Author-X-Name-First: Jing Author-X-Name-Last: Zhong Author-Name: Peng Zhang Author-X-Name-First: Peng Author-X-Name-Last: Zhang Title: Collaborative design of large-scale building's energy saving structure based on green BIM concept Abstract: Aiming at the problems of low energy-saving sustainability coefficient, low energy utilisation rate and high carbon emission coefficient existing in traditional structural design methods, a collaborative design of large-scale building's energy-saving structure based on green BIM concept is proposed. Combined with green BIM concept, the design of building application platform is based on BIM. In the BIM building application platform, the building energy consumption monitoring, safety evacuation and space management functions are set in the BIM building application platform. The experimental results show that: the energy-saving sustainability coefficient of large-scale building's energy-saving structure designed by this method is above 8, the highest energy utilisation rate is 95%, and the carbon emission coefficient is lower than 0.2, which has certain feasible significance. Journal: Int. J. of Global Energy Issues Pages: 217-232 Issue: 2/3 Volume: 44 Year: 2022 Keywords: green BIM concept; large-scale building; building application platform; energy consumption monitoring; collaborative design of energy saving structure. File-URL: http://www.inderscience.com/link.php?id=121401 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijgeni:v:44:y:2022:i:2/3:p:217-232 Template-Type: ReDIF-Article 1.0 Author-Name: Ilyes Abid Author-X-Name-First: Ilyes Author-X-Name-Last: Abid Author-Name: Amine Ben Amar Author-X-Name-First: Amine Ben Author-X-Name-Last: Amar Author-Name: Khaled Guesmi Author-X-Name-First: Khaled Author-X-Name-Last: Guesmi Author-Name: Thomas Porcher Author-X-Name-First: Thomas Author-X-Name-Last: Porcher Title: COVID-19 and oil price shocks: the case of Republic of the Congo Abstract: The downturn in the global economy following the outbreak of COVID-19 pandemic has caused a fall in demand and a huge decline in oil prices. To examine the impact of negative exogenous shocks including oil price shocks, most studies focus on how it impacts on a country's economic growth. Focusing on the Republic of the Congo, our paper incorporates the modalities of sharing oil rents between the State and the oil exploration companies. In particular, our analysis is based on the rent sharing modalities of the fifteen oil contracts in this country. We demonstrate that the Republic of the Congo suffers three shocks: declining oil price shocks, diminishing share of oil rents with the exploration companies and a reduction in production volumes. Our work offers a better assessment of the needs of the country and the necessary aid that may promote stability and a reduction in the risk of a food crisis. Journal: Int. J. of Global Energy Issues Pages: 281-291 Issue: 4 Volume: 44 Year: 2022 Keywords: oil resources; economic development; Africa; Congo; COVID-19. File-URL: http://www.inderscience.com/link.php?id=123961 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijgeni:v:44:y:2022:i:4:p:281-291 Template-Type: ReDIF-Article 1.0 Author-Name: Qi Wu Author-X-Name-First: Qi Author-X-Name-Last: Wu Author-Name: Aina Qi Author-X-Name-First: Aina Author-X-Name-Last: Qi Author-Name: Guanglei Zhao Author-X-Name-First: Guanglei Author-X-Name-Last: Zhao Title: Evaluation of energy utilisation efficiency of central air conditioning in large buildings based on entropy weight-cloud model Abstract: In the evaluation of the energy use efficiency of the existing large air conditioners, the problems of low accuracy and high time cost are presented. The structure and movement mechanism of air conditioners in large buildings are analysed to obtain efficiency evaluation results. The covariance matrix was used to obtain the evaluation index of energy utilisation potency in air conditioners. Through proportion of influencing factors, the function relationship between indoor temperature change and cooling load change was determined based on the distribution of cooling load in large buildings. The entropy weight-cloud evaluation model was built to complete the evaluation and analysis of utilisation potency. Through comparative analysis, we can see that error of energy evaluation for air conditioner is less than 3%, and that need time cost is small. Journal: Int. J. of Global Energy Issues Pages: 198-216 Issue: 2/3 Volume: 44 Year: 2022 Keywords: entropy weight-cloud model; large building; central air conditioning; energy utilisation efficiency; consumption data; entropy weight method. File-URL: http://www.inderscience.com/link.php?id=121402 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijgeni:v:44:y:2022:i:2/3:p:198-216 Template-Type: ReDIF-Article 1.0 Author-Name: Jing Zhong Author-X-Name-First: Jing Author-X-Name-Last: Zhong Author-Name: Peng Zhang Author-X-Name-First: Peng Author-X-Name-Last: Zhang Author-Name: Li Wang Author-X-Name-First: Li Author-X-Name-Last: Wang Title: An energy consumption calculation model of prefabricated building envelope system based on BIM technology Abstract: There are problems of poor accuracy and long time in the calculation of prefabricated building envelope system, a model for getting resources consumption of prefabricated building envelope system is designed by means of BIM technology. The building information is obtained by classification, and the information of building envelope system is integrated by BIM Technology. The BIM model of prefabricated building envelope system is constructed by using comprehensive building information. Through the finite difference calculation, the design of calculation model is completed. By designing the experiment, accuracy of this method can reach 99%, and calculation time is less than 0.4 min. Journal: Int. J. of Global Energy Issues Pages: 121-138 Issue: 2/3 Volume: 44 Year: 2022 Keywords: BIM technology; information integration; prefabricated building envelope system; BIM model; energy consumption calculation model. File-URL: http://www.inderscience.com/link.php?id=121403 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijgeni:v:44:y:2022:i:2/3:p:121-138 Template-Type: ReDIF-Article 1.0 Author-Name: Qiuhong Zhao Author-X-Name-First: Qiuhong Author-X-Name-Last: Zhao Title: A short-term prediction method of building energy consumption based on gradient progressive regression tree Abstract: In order to overcome the large error of traditional methods in predicting building energy consumption, a short-term prediction method of building energy consumption based on gradient progressive regression tree is proposed. Building benchmark model is constructed by using eQuest software to obtain the main parameters affecting building energy consumption, build the impact index system of building energy consumption, and extract the main impact factors. Genetic algorithm is used to extract the characteristics of building energy consumption, combined with gradient progressive regression tree method to build a short-term prediction model of building energy consumption, and complete the short-term prediction of building energy consumption. The experimental results show that the minimum relative error of the proposed method is about 0.1, the absolute error is about 0.2, and the maximum standard deviation is 0.41. Journal: Int. J. of Global Energy Issues Pages: 182-197 Issue: 2/3 Volume: 44 Year: 2022 Keywords: gradient regression tree; building benchmark model; influencing factors of energy consumption; genetic algorithm; building energy consumption prediction. File-URL: http://www.inderscience.com/link.php?id=121404 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijgeni:v:44:y:2022:i:2/3:p:182-197 Template-Type: ReDIF-Article 1.0 Author-Name: Mohammad Movahedi Author-X-Name-First: Mohammad Author-X-Name-Last: Movahedi Author-Name: Kiumars Shahbazi Author-X-Name-First: Kiumars Author-X-Name-Last: Shahbazi Author-Name: Samad Hekmati Farid Author-X-Name-First: Samad Hekmati Author-X-Name-Last: Farid Title: The effect of government expenditure on energy intensity: a panel smooth transition regression (PSTR) approach Abstract: Energy is considered a significant factor for sustainable development, and governments are faced some challenges such as the expenses involved in running the economy and how to perform such costs for reducing the energy intensity and provide energy efficiency. This article investigates government expenditure impact on the energy intensity on top ten European crude oil-exporting countries during 1995-2014. The results confirm the non-linear effect of government expenditure per GDP on the energy intensity with one threshold parameter. Findings indicate that government expenditure impact per GDP on energy intensity is significantly negative at low government expenditure (at first regime) and positive at the high government expenditure (at second regime). The positive and increasing effect of government expenditure on the energy sector in the second regime shows that the government intervention at macro-programs and the high government size can hike up energy intensity. Journal: Int. J. of Global Energy Issues Pages: 292-310 Issue: 4 Volume: 44 Year: 2022 Keywords: government expenditure per GDP; energy intensity; PSTR; European crude oil-exporting countries. File-URL: http://www.inderscience.com/link.php?id=123975 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijgeni:v:44:y:2022:i:4:p:292-310 Template-Type: ReDIF-Article 1.0 Author-Name: Carlos Díaz-Rodríguez Author-X-Name-First: Carlos Author-X-Name-Last: Díaz-Rodríguez Author-Name: Abdénago Yate-Arévalo Author-X-Name-First: Abdénago Author-X-Name-Last: Yate-Arévalo Author-Name: Mónica Bustamante-Salamanca Author-X-Name-First: Mónica Author-X-Name-Last: Bustamante-Salamanca Title: Contributions of bioethics towards a new paradigm of energy Abstract: Adequate access to energy services contribute to economic development, overcoming poverty, and improving quality of life. The generation and use of energy based on fossil fuels are some of the main causes of anthropogenic pollution. The objective is to develop an energy paradigm with a bioethical perspective that supports technical and economic approaches and allows the transition to a low-carbon energy regime. Etymologically, 'energy ethics' and 'ethics of energy' are addressed, from a theoretical-practical literature review on energy. The traditional energy paradigm discussed in this research is based on energy principles and values that reduce natural and human processes to energy conversions achieved through scientific control of the forces of nature. A new energy paradigm is proposed based on bioethical aspects such as the precautionary principle, justice as equity, protection and the principle of responsibility, which allows the management of the nature of problems in the energetic sector. Journal: Int. J. of Global Energy Issues Pages: 311-327 Issue: 4 Volume: 44 Year: 2022 Keywords: energy ethics; ethics of energy; energy paradigm; bioethics. File-URL: http://www.inderscience.com/link.php?id=123978 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijgeni:v:44:y:2022:i:4:p:311-327 Template-Type: ReDIF-Article 1.0 Author-Name: Ugochukwu K. Okoro Author-X-Name-First: Ugochukwu K. Author-X-Name-Last: Okoro Author-Name: Chizomam I. Usoh Author-X-Name-First: Chizomam I. Author-X-Name-Last: Usoh Author-Name: Cecily O. Nwokocha Author-X-Name-First: Cecily O. Author-X-Name-Last: Nwokocha Author-Name: Wen Chen Author-X-Name-First: Wen Author-X-Name-Last: Chen Title: Temperature range across Nigeria to the end of 21st century: prospects for photovoltaics based on CMIP5 and CORDEX perspectives Abstract: Temperature range (TR) data from the Climate Research Unit (CRU) has been validated by the Nigeria Meteorological Agency observations. The horizontal solar radiation (Gh) is estimated from the TR using the Annandale method and validated by the Photovoltaic Geographical Information System, which presents it as a proxy to Gh in such data-sparse area. CMIP5 and CORDEX-Africa estimated Gh and Surface Downwelling Shortwave Radiation, respectively, are compared with the estimated Gh. The models' historical outputs for the estimated Gh show a significant correlation (99.9% confidence level from the t-test) with the CRU proxy. The models' estimated Gh projections have two epochs, from 2006 to 2038 and from 2039 to 2089. Compared to the historical, the first epoch has all models projecting a Gh decrease in RCP 4.5 (CCCMa = &minus;0.28%, DMI = &minus;0.31%, KNMI = &minus;0.43%), whereas, CCCMa (0.47%) and DMI (0.06%) projects increment in the RCP 8.5. In contrast, the second epoch reveals a greater projected decrease in the RCP 4.5 from CCCMa (&minus;0.45%) and KNMI (&minus;1.81%), whereas, a greater projected increment from CCCMa (1.40%) and DMI (0.35%) in the RCP 8.5. Our findings are imperative in PV planning, siting and management across Nigeria. Journal: Int. J. of Global Energy Issues Pages: 1-27 Issue: 1 Volume: 44 Year: 2022 Keywords: Nigeria; temperature range; solar radiation; CMIP5; CORDEX-Africa. File-URL: http://www.inderscience.com/link.php?id=120769 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijgeni:v:44:y:2022:i:1:p:1-27 Template-Type: ReDIF-Article 1.0 Author-Name: Pery Francisco Assis Shikida Author-X-Name-First: Pery Francisco Assis Author-X-Name-Last: Shikida Author-Name: Marco Antonio Montoya Author-X-Name-First: Marco Antonio Author-X-Name-Last: Montoya Author-Name: Giovani Richard Pitilin Author-X-Name-First: Giovani Richard Author-X-Name-Last: Pitilin Author-Name: Bianca Grando Giordani Author-X-Name-First: Bianca Grando Author-X-Name-Last: Giordani Title: Energy consumption and CO2 emissions in the sugarcane chain in Brazil: an input-output approach (2000-2014) Abstract: This paper sought to evaluate the sugarcane chain in Brazil using input-output matrices for energy consumption and CO<SUB align=right><SMALL>2</SMALL></SUB> emissions from either renewable or non-renewable sources, in the years 2000, 2005, 2010 and 2014. For this purpose, energy and emission matrices were harmonised and disaggregated vis-à-vis the country's monetary matrices. As a result, energy consumption by the said chain grew by 6.7% a year, having accounted for nearly 25% of consumption by the Brazilian agribusiness industry in 2014. However, energy consumption from renewable sources not only prevailed but also rose from 73% in 2000 to 88% in 2014. Therefore, emissions from the sugarcane chain are becoming increasingly suitable for preserving the environment. Journal: Int. J. of Global Energy Issues Pages: 28-46 Issue: 1 Volume: 44 Year: 2022 Keywords: agribusiness; sugarcane agroindustry; renewable sources. File-URL: http://www.inderscience.com/link.php?id=120773 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijgeni:v:44:y:2022:i:1:p:28-46 Template-Type: ReDIF-Article 1.0 Author-Name: Mas'ud Ibrahim Author-X-Name-First: Mas'ud Author-X-Name-Last: Ibrahim Author-Name: Kamil Omoteso Author-X-Name-First: Kamil Author-X-Name-Last: Omoteso Title: Cheating behaviour among OPEC member-states and oil price fairness and stability: an empirical analysis Abstract: Within the context of a target oil price band regime, this paper posits that cheating behaviour in OPEC has ethical and accountability implications for the organisation. It also impacts on its reputation and ability to ensure stable and fair oil prices in the oil markets. Based on data sets covering the period from 2000 to 2012 (i.e. production quota era), analysed using the Vector Auto-Regression/Vector Error Correction (VAR-VEC) framework, the study's results indicate that OPEC cheating, mainly instigated by the amount of spare production capacity available to OPEC members, does not seem to have a significant direct effect on international oil prices. However, the degree of cheating by OPEC member-states might disrupt its ability to maintain surplus capacity enough to reduce price speculation in the oil markets. Should cheating behaviour in OPEC continue unabated, this could jeopardise an effective energy regulatory framework and market transparency. The paper, therefore, recommends a policy action in OPEC to support the redesigning of the existing quota system that is fair and just to its members and capable of controlling any cheating behaviour. Journal: Int. J. of Global Energy Issues Pages: 98-119 Issue: 1 Volume: 44 Year: 2022 Keywords: OPEC cartel; cooperation; cheating; fairness and oil price stability. File-URL: http://www.inderscience.com/link.php?id=120775 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijgeni:v:44:y:2022:i:1:p:98-119 Template-Type: ReDIF-Article 1.0 Author-Name: Tao Xiao Author-X-Name-First: Tao Author-X-Name-Last: Xiao Author-Name: Tao Zhang Author-X-Name-First: Tao Author-X-Name-Last: Zhang Author-Name: Ning Zhang Author-X-Name-First: Ning Author-X-Name-Last: Zhang Title: Research on energy supply chain risk prediction based on the fuzzy C-means clustering algorithm Abstract: In order to improve the ability of risk prediction, a risk prediction method of energy supply chain based on fuzzy C-means clustering algorithm is proposed. Based on the regression analysis results of risk data samples, panel data fusion is carried out to extract the correlation feature of risk panel data of energy supply chain. Using the prior information distributed detection method to construct the statistical characteristic quantity of energy supply chain risk prediction. According to the prior sample regression analysis results of risk prediction of energy supply chain, the risk characteristics of energy supply chain are extracted, and the fuzzy C-means clustering method is used to cluster the risk characteristics, and the risk prediction of energy supply chain is carried out. The simulation results show that this method has high accuracy and credibility for energy supply chain risk prediction, and improves the risk management ability of energy supply chain. Journal: Int. J. of Global Energy Issues Pages: 65-75 Issue: 1 Volume: 44 Year: 2022 Keywords: fuzzy C-means; clustering; energy supply chain; risk prediction. File-URL: http://www.inderscience.com/link.php?id=120781 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijgeni:v:44:y:2022:i:1:p:65-75 Template-Type: ReDIF-Article 1.0 Author-Name: Lei Zhang Author-X-Name-First: Lei Author-X-Name-Last: Zhang Author-Name: Huaxi Chen Author-X-Name-First: Huaxi Author-X-Name-Last: Chen Author-Name: Mali Zheng Author-X-Name-First: Mali Author-X-Name-Last: Zheng Title: Research on risk assessment method of energy system based on data mining Abstract: In order to overcome the problem of data index confusion and index weight ambiguity in the traditional energy system risk assessment process, this paper proposes an energy system risk assessment method based on data mining. This method USES data mining technology and quantitative index processing method to select risk assessment index of energy system, construct risk assessment index system of energy system, determine the weight of risk assessment index of energy system, and build risk assessment model of energy system on this basis. The experimental results show that the weighing accuracy and evaluation accuracy of the proposed method are above 90%, and the skewness coefficient is always close to 0. The method has a high degree of rationality in energy risk index selection, high precision in index weight and high accuracy in evaluation results, which can effectively guarantee the safety of urban energy system. Journal: Int. J. of Global Energy Issues Pages: 47-64 Issue: 1 Volume: 44 Year: 2022 Keywords: data mining; energy system; indicator system; risk assessment. File-URL: http://www.inderscience.com/link.php?id=120782 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijgeni:v:44:y:2022:i:1:p:47-64 Template-Type: ReDIF-Article 1.0 Author-Name: Bamadev Mahapatra Author-X-Name-First: Bamadev Author-X-Name-Last: Mahapatra Author-Name: Diptimayee Jena Author-X-Name-First: Diptimayee Author-X-Name-Last: Jena Title: Examining the impact of COVID-19 on Indian energy exchange market: empirical evidence from a multi-regional panel data analysis Abstract: This study aims to explore the effect of coronavirus disease 2019 (COVID-19) on the Indian energy exchange market (IEX), especially on energy sell, energy buy, and energy price. The data used in this study is multi-regional panel data consisting of 13 regions observed through March to August 2020. To investigate the relationship, a panel cointegration, causality, and a Panel-Based Autoregressive Distributed Lag (PARDL) model is applied within a multivariate framework. The empirical outcomes confirm that a long-run equilibrium relationship is noticeable in the models. Results of the causality test suggest that there exists a unidirectional causality running from COVID-19 to the IEX. Based on the findings of long-run and short-run elasticities of the Pooled Mean Group (PMG) estimator, this study suggests the government and policymakers should provide aids and incentives to the power generating companies and to the investors which generate, sell and purchase energy from the energy exchange market. Journal: Int. J. of Global Energy Issues Pages: 76-97 Issue: 1 Volume: 44 Year: 2022 Keywords: COVID-19; energy exchange market; energy sell; energy buy; energy price; panel data; cointegration; causality; panel ARDL; India. File-URL: http://www.inderscience.com/link.php?id=120796 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijgeni:v:44:y:2022:i:1:p:76-97 Template-Type: ReDIF-Article 1.0 Author-Name: Xin Mao Author-X-Name-First: Xin Author-X-Name-Last: Mao Author-Name: Yufan Rao Author-X-Name-First: Yufan Author-X-Name-Last: Rao Author-Name: Min Gong Author-X-Name-First: Min Author-X-Name-Last: Gong Author-Name: Xuemin Song Author-X-Name-First: Xuemin Author-X-Name-Last: Song Author-Name: Lixing Zhou Author-X-Name-First: Lixing Author-X-Name-Last: Zhou Title: Optimisation of frequency response parameters of new energy distribution network based on linear correction Abstract: In order to overcome the problems of high response adjustment rate and low optimisation efficiency existing in the existing frequency response parameter optimisation methods of distribution network, a new optimisation method for frequency response parameter of new energy distribution network based on linear correction is proposed. Firstly, the frequency response demand of new energy distribution network is analysed, and the frequency regulation index of PV and wind power is obtained. Combined with linear correction algorithm, the frequency response parameter model of new energy distribution network is constructed. The fuzzy control theory and genetic algorithm are combined to solve the model to effectively optimise the frequency response parameters of new energy distribution network. Simulation results show that the proposed method cannot only effectively reduce the frequency response adjustment rate of distribution network, but also effectively reduce the optimisation time and cost. Journal: Int. J. of Global Energy Issues Pages: 454-470 Issue: 5/6 Volume: 44 Year: 2022 Keywords: linear correction; new energy distribution network; frequency response parameters; fuzzy control theory; genetic algorithm. File-URL: http://www.inderscience.com/link.php?id=125404 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijgeni:v:44:y:2022:i:5/6:p:454-470 Template-Type: ReDIF-Article 1.0 Author-Name: Xiaolong Wen Author-X-Name-First: Xiaolong Author-X-Name-Last: Wen Title: Energy consumption monitoring model of green energy-saving building based on fuzzy neural network Abstract: In order to overcome the problems of the traditional model, such as large monitoring data error and poor energy consumption control effect, the energy consumption monitoring model of green energy-saving building based on fuzzy neural network is designed. According to the data time series, the building energy consumption interval is calculated and the energy consumption load data is obtained. The actual energy consumption equipment parameters and energy consumption calculation results are taken as the input of the model, and the input parameters are optimised by using fuzzy neural network. The energy consumption monitoring model is constructed by using the optimised parameters, and the model is modified by using the correction coefficient to output the energy consumption monitoring results. The experimental results show that the monitoring error of the model is less than 0.7%, the energy consumption control effect is good and the building energy saving is high. Journal: Int. J. of Global Energy Issues Pages: 396-412 Issue: 5/6 Volume: 44 Year: 2022 Keywords: load interval; green energy-saving building; monitoring model; energy control. File-URL: http://www.inderscience.com/link.php?id=125405 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijgeni:v:44:y:2022:i:5/6:p:396-412 Template-Type: ReDIF-Article 1.0 Author-Name: Chuan He Author-X-Name-First: Chuan Author-X-Name-Last: He Author-Name: Ying Xiong Author-X-Name-First: Ying Author-X-Name-Last: Xiong Author-Name: Yeda Lin Author-X-Name-First: Yeda Author-X-Name-Last: Lin Author-Name: Lie Yu Author-X-Name-First: Lie Author-X-Name-Last: Yu Author-Name: Hui-Hua Xiong Author-X-Name-First: Hui-Hua Author-X-Name-Last: Xiong Title: Energy consumption prediction method of energy saving building based on deep reinforcement learning Abstract: In order to overcome the problems of low-prediction accuracy and long prediction time of traditional building energy consumption prediction methods, this paper proposes a new energy-saving building energy consumption prediction method based on deep reinforcement learning. Through the deep reinforcement learning algorithm, a number of energy consumption behaviour return information of specific value network and strategy network are calculated, respectively to build the energy consumption probability model of energy-saving building energy consumption equipment. The linear rectification function with leakage is used to update the probability model and parameters, and the linear relationship prediction function of energy consumption parameters is constructed by using the learning process and results to complete the dynamic prediction of energy consumption of energy-saving buildings. The experimental results show that the proposed method has fast prediction speed and high accuracy, which can provide reference for the implementation of energy-saving building. Journal: Int. J. of Global Energy Issues Pages: 524-536 Issue: 5/6 Volume: 44 Year: 2022 Keywords: deep intensive learning; energy saving building; energy consumption forecasting; time series; multivariate linear regression. File-URL: http://www.inderscience.com/link.php?id=125406 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijgeni:v:44:y:2022:i:5/6:p:524-536 Template-Type: ReDIF-Article 1.0 Author-Name: Ke Qi Author-X-Name-First: Ke Author-X-Name-Last: Qi Title: A cross-regional joint operation control method of small power photovoltaic power grid and municipal power grid Abstract: Aiming at the problems of high-failure rate of transmission lines and large fluctuation of output waveform in traditional methods, a control method for cross-regional joint operation of low-power photovoltaic grid and municipal grid based on fuzzy logic control is designed. This method combines the overall topological structure of the power supply system and installs a protection circuit to reduce electricity costs. In the entire combined power supply system, the fuzzy logic control method is used to obtain the distance distribution function of the fault nodes in different areas of the power grid, and the effective control of the power grid is realised by adjusting the grid deviation coefficient. The results show that the failure rate of the transmission line is reduced from 6 to 3%, the output waveform fluctuates steadily and the grid operation status is relatively stable, which guarantees the safe operation of the grid. Journal: Int. J. of Global Energy Issues Pages: 511-523 Issue: 5/6 Volume: 44 Year: 2022 Keywords: small power photovoltaic grid; municipal grid; joint operation control; fuzzy logic control; distance distribution function. File-URL: http://www.inderscience.com/link.php?id=125407 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijgeni:v:44:y:2022:i:5/6:p:511-523 Template-Type: ReDIF-Article 1.0 Author-Name: Jingchen Shi Author-X-Name-First: Jingchen Author-X-Name-Last: Shi Title: Green building energy consumption data detection method based on Naive Bayesian algorithm Abstract: In order to overcome the accuracy of energy consumption data acquisition and the low timeliness of the detection process existing in the traditional detection methods, a green building energy consumption data detection method based on Naive Bayes algorithm is designed in this paper. After collecting energy consumption data, cluster processing is carried out. Then, on the basis of the analysis of Bayesian basic principle, the Naive Bayesian classification model was designed based on the fast clustering calculation results, and the green building energy usage was analysed, and the energy consumption data quota index was designed, and the energy consumption data verification was completed by combining the Naive Bayesian classification model. The experimental results show that the building energy consumption load collected by this method is closer to the actual energy consumption load, and the detection process takes less than 3.5 min, which fully demonstrates the effectiveness of this method. Journal: Int. J. of Global Energy Issues Pages: 379-395 Issue: 5/6 Volume: 44 Year: 2022 Keywords: Naive Bayes algorithm; building energy consumption data; data detection; energy consumption quota; data clustering. File-URL: http://www.inderscience.com/link.php?id=125408 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijgeni:v:44:y:2022:i:5/6:p:379-395 Template-Type: ReDIF-Article 1.0 Author-Name: Shaoqing Shi Author-X-Name-First: Shaoqing Author-X-Name-Last: Shi Author-Name: Zhuo Xu Author-X-Name-First: Zhuo Author-X-Name-Last: Xu Author-Name: Yong Xiao Author-X-Name-First: Yong Author-X-Name-Last: Xiao Title: Load identification method of household smart meter based on decision tree algorithm Abstract: In order to ensure the safe and economic operation of power grid, a load identification method of household smart meters based on decision tree algorithm is proposed. This paper pre-processes the missing data, noise data and inconsistent data in the load data of household smart meter, and uses the decision tree algorithm to predict the load data after pre-processing. According to the prediction results, combined with mathematical tools, from the PQ characteristics, current characteristics, V-I characteristics The load characteristics of household smart meters are extracted from the characteristics, harmonic characteristics and instantaneous characteristics and the objective function of load identification is constructed based on the combination of characteristics, so as to realise the load identification of household smart meters based on decision tree algorithm. Comparative results show that this method can reduce the error rate of load, to improve the efficiency of identification, identifying the shortest time of only 1.5 s. Journal: Int. J. of Global Energy Issues Pages: 440-453 Issue: 5/6 Volume: 44 Year: 2022 Keywords: decision tree; household smart meter; load data; feature combination. File-URL: http://www.inderscience.com/link.php?id=125409 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijgeni:v:44:y:2022:i:5/6:p:440-453 Template-Type: ReDIF-Article 1.0 Author-Name: Wenjia Song Author-X-Name-First: Wenjia Author-X-Name-Last: Song Title: Research on energy consumption parameter optimisation of green building based on single and double-layer hybrid optimisation Abstract: In order to solve the problems of poor extraction accuracy of energy consumption parameters existing in traditional optimisation methods, an optimisation method of green building energy consumption parameters based on single and double-layer hybrid optimisation was proposed. According to the optimisation principle of green building energy consumption parameters, the green building envelope energy consumption parameters, window energy consumption parameters and heating energy consumption parameters are determined. The objective function of green building energy consumption parameter optimisation was established by single and double-layer hybrid optimisation method. The energy consumption parameters were input into the function to obtain the optimal solution of each parameter and complete the parameter optimisation. The experimental results show that the minimum value of the sample building energy consumption parameters optimised by the method in this paper is about 1.9 J, and the maximum extraction accuracy of the sample building energy consumption parameters is about 97%. Journal: Int. J. of Global Energy Issues Pages: 471-483 Issue: 5/6 Volume: 44 Year: 2022 Keywords: single and double-layer hybrid optimisation method; green building; energy consumption parameters; parameter optimisation. File-URL: http://www.inderscience.com/link.php?id=125410 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijgeni:v:44:y:2022:i:5/6:p:471-483 Template-Type: ReDIF-Article 1.0 Author-Name: Lijun Yin Author-X-Name-First: Lijun Author-X-Name-Last: Yin Author-Name: Haoran Yin Author-X-Name-First: Haoran Author-X-Name-Last: Yin Title: Energy consumption parameter detection of green energy saving building based on artificial fish swarm algorithm Abstract: In order to overcome the low-detection accuracy of traditional methods, an artificial fish swarm algorithm was proposed to detect the energy consumption parameters of green and energy-saving buildings. The type of energy consumption equipment in green and energy-saving buildings is analysed, and the electricity consumption of building energy consumption equipment is taken as the building energy consumption parameter. The hierarchical clustering method was used to establish the classification model of energy consumption parameters, and the energy consumption parameters were classified and processed, and the energy consumption parameters detection model was built, and the preliminary detection results of energy consumption parameters were obtained. The artificial fish swarm algorithm was used to construct the optimisation function of building parameter detection results to obtain the optimal detection results of energy consumption parameters. Experimental results show that the accuracy of the proposed method is between 92.76% and 98.75%, and the practical application effect is good. Journal: Int. J. of Global Energy Issues Pages: 498-510 Issue: 5/6 Volume: 44 Year: 2022 Keywords: artificial fish swarm algorithm; green energy saving building; energy consumption parameters; hierarchical clustering. File-URL: http://www.inderscience.com/link.php?id=125411 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijgeni:v:44:y:2022:i:5/6:p:498-510 Template-Type: ReDIF-Article 1.0 Author-Name: Shulong Wu Author-X-Name-First: Shulong Author-X-Name-Last: Wu Author-Name: Fengjun Wang Author-X-Name-First: Fengjun Author-X-Name-Last: Wang Author-Name: Maosong Wan Author-X-Name-First: Maosong Author-X-Name-Last: Wan Title: Energy consumption prediction of new energy vehicles in smart city based on LSTM network Abstract: In order to overcome the traditional problems such as large prediction error and long prediction time, this paper proposes a new energy consumption prediction method of smart city new energy vehicles based on LSTM network. By analysing the energy operation process of new energy vehicles in smart city, the energy consumption prediction parameters such as vehicle battery energy, resistance energy consumption, rolling resistance and air resistance are determined. On this basis, the energy consumption prediction model of new energy vehicles is constructed, and the LSTM network is used to solve the energy consumption prediction model of new energy vehicles, and the energy consumption prediction results are obtained. Experimental results show that the prediction error of the proposed method is always less than 2%, and when the number of iterations is 50, the prediction time of the proposed method is only about 0.95 s, which is relatively short. Journal: Int. J. of Global Energy Issues Pages: 484-497 Issue: 5/6 Volume: 44 Year: 2022 Keywords: LSTM network; smart city; new energy vehicle; prediction parameters; prediction model. File-URL: http://www.inderscience.com/link.php?id=125412 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijgeni:v:44:y:2022:i:5/6:p:484-497 Template-Type: ReDIF-Article 1.0 Author-Name: Jia Liu Author-X-Name-First: Jia Author-X-Name-Last: Liu Author-Name: Jin Huang Author-X-Name-First: Jin Author-X-Name-Last: Huang Author-Name: Jinzhi Hu Author-X-Name-First: Jinzhi Author-X-Name-Last: Hu Title: Multi-objective optimisation method of electric vehicle charging station based on non-dominated sorting genetic algorithm Abstract: There are some problems in the existing objective optimisation planning methods of electric vehicle charging station, such as low accuracy and long optimisation time. By calculating the input cost, combined closure flow and minimum node voltage of the charging station through the objective function, the optimisation objective was determined. According to the determined optimisation objective, the multi-objective comprehensive planning model of the electric vehicle charging station is constructed. After the initial solution setting, coding, decoding and other iterative operations, the multi-objective comprehensive planning model of the electric vehicle charging station is solved and the optimisation result is obtained. The multi-objective optimisation of electric vehicle charging station is realised. The results show that the highest accuracy is about 95%. Journal: Int. J. of Global Energy Issues Pages: 413-426 Issue: 5/6 Volume: 44 Year: 2022 Keywords: non-dominated sorting genetic algorithm; electric vehicle charging station; multi-objective optimisation; decoding. File-URL: http://www.inderscience.com/link.php?id=125413 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijgeni:v:44:y:2022:i:5/6:p:413-426 Template-Type: ReDIF-Article 1.0 Author-Name: Haitong Gu Author-X-Name-First: Haitong Author-X-Name-Last: Gu Author-Name: Zhuo Cui Author-X-Name-First: Zhuo Author-X-Name-Last: Cui Author-Name: Kaiyan Chen Author-X-Name-First: Kaiyan Author-X-Name-Last: Chen Author-Name: Zhengyang Peng Author-X-Name-First: Zhengyang Author-X-Name-Last: Peng Author-Name: Shitao Chen Author-X-Name-First: Shitao Author-X-Name-Last: Chen Title: Power load monitoring method of high-power electrical appliances based on energy compensation Abstract: In order to overcome the problems of low monitoring accuracy and long monitoring time existing in traditional power load monitoring methods, a new power load monitoring method based on energy compensation is proposed. The basic framework of high-power electrical load monitoring method is given. According to Fourier series, the active power of high-power electrical equipment during operation is obtained, and the current waveforms under various operation states are obtained. The sliding double-sided window cumulative calculation method is used to determine the load switching event data. At the same time, the characteristic indexes of power load curve are extracted by similarity measurement index. In feature extraction based on the result using the energy to complete the electrical load monitoring compensation method. The research results show that the proposed method has higher monitoring accuracy and shorter monitoring time, the shortest time is 0.02 s. Journal: Int. J. of Global Energy Issues Pages: 427-439 Issue: 5/6 Volume: 44 Year: 2022 Keywords: energy compensation; high-power appliances; electrical load; active power; switching events. File-URL: http://www.inderscience.com/link.php?id=125414 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijgeni:v:44:y:2022:i:5/6:p:427-439