Despite India's progress in reducing national poverty rates, pockets of severe poverty persist in the mountainous states comprising the Indian Himalayan Region (IHR). This paper examines the geographic patterns and dynamics of consumption as well as multidimensional poverty in the IHR, drawing insights from nationally representative household surveys. It explores the multifaceted factors influencing poverty, including geography, accessibility, social structures, economic activities, and environmental conditions. There is a significant variation in the incidence of consumption poverty across the IHR. While some states exhibit poverty rates lower than the national average, others, such as Assam, Arunachal Pradesh, and Manipur, record higher rates, emphasizing the need for tailored poverty alleviation strategies. Multidimensional poverty in the IHR slightly exceeds the national average, with deprivations spread across various dimensions, including health, education, living standards, economic opportunities, and inaccessibility. Both types of poverty are highly correlated with larger household size and dependency ratio, and schedule caste/tribes. The important factors that could help reduce poverty appear to be education, access to clean energy including electricity, better sanitation services, and access to mobile phone services. To address poverty effectively in the IHR, comprehensive strategies are essential, including the development of farm and non-farm sectors, the provision of essential services, and targeted interventions tailored to local contexts. The paper underscores the importance of recognizing the unique challenges faced by mountainous regions and calls for region-specific policy interventions to achieve sustainable poverty reduction.
With the transformation of the global energy structure, photovoltaic power generation, as a clean and renewable energy form, is receiving increasing attention and from many countries. Especially in the agricultural sector, integrating the planting of traditional Chinese medicinal plants with clean energy construction and environmental protection plays a significant role. This not provides the electricity needed for agricultural facilities but also helps to achieve energy conservation and emission reduction, promoting sustainable agricultural development.
The availability of properly analyzed energy resource potential data is a prerequisite in energy planning and development. However, this was sparsely applied in Ethiopia’s renewable energy turnkey project development strategies. This study focuses on developing a solar energy resource map of Tigray to accelerate the expansion of solar energy to improve electricity access through on-grid and off-grid development schemes. This study uses monthly sunshine hour data from sixteen meteorological stations, measured at a 2 m height, and average yearly solar radiation data from twenty-two satellite stations, validated by solar radiation data and measured at three sites at 10 and 30 m heights. The solar energy potential was analyzed by taking relevant atmospheric and meteorological factors to produce solar radiation components. Accordingly, the average annual solar radiation of Tigray was found to be 6.1 kWh/m<sup>2</sup>/day and 5.3 kWh/m<sup>2</sup>/day based on meteorological and satellite data, respectively. The meteorological result gave a closer estimate to Ethiopia’s ESMAP Global Solar result of 5.83 kWh/m<sup>2</sup>/day. Finally, monthly and annual average solar radiation maps of the region were developed using ArcGIS10.5. The study’s results could contribute to assisting various solar energy developers in preparing better solar energy development plans to alleviate the chronic energy poverty of the region.
In the context of large-scale and medium-and-long distance offshore wind power development， a comprehensive economic comparison has been made between fractional frequency transmission system （FFTS） and other transmission systems. An economic evaluation model based on the levelized cost of electricity （LCOE） for the FFTS system. This model takes into account the lifecycle， initial resource investment， operational losses， routine maintenance， decommissioning costs， and tax liabilities. By using an offshore wind farm as a case study， the paper analyzes the economic intervals of the FFTS and economic variability under various scenarios. The findings reveal that， for a 500 MW offshore wind farm， the economic interval extends from 80 to 250 kilometers； moreover， this range exhibits a notable degree of stability and demonstrates superior economic viability in contrast to traditional transmission systems across multiple scenarios.
Wan Aina Syahirah Wan Abdullah, Mardhiah Wahab, Yang Zeyu
et al.
Malaysia possesses significant potential for solar power generation due to its tropical weather and high levels of solar irradiance. This climate condition implies that solar technology, such as photovoltaic (PV) systems enable to generate more electricity per unit area, making it more economically viable for businesses and households’ applications. As Malaysia pledge to support the Net Zero Emissions (NZE) by 2050 Scenario, pre and continuous evaluation on the opportunities and challenges confronting solar technology penetration as a clean and affordable energy is of significant. This work aims to perform preliminary assessment of large scale of solar technology in Malaysia via integrated SWOT (Strengths, Weaknesses, Opportunities, and Threats) and PESTLE (the Political, Economic, Social, Technical, Legal, and Environmental) approaches, combine with analytic hierarchy process (AHP) method. It can be concluded that solar energy is one of the alternative energy sources that should be developed more in the future in terms of technology to ensure clean energy can be promoted. In AHP analysis, the economic aspect has shown the highest priority. Cost of investment and operation exhibited a huge factor that may hinder the large-scale solar project in Malaysia. The semi-empirical result of this paper presents a reality check on the solar technology feasibility in Malaysia while formulate a decision-making framework for addressing clean energy technology.
Chemical engineering, Computer engineering. Computer hardware
Jeffrey M. Bielicki, Martina Leveni, Jeremiah X. Johnson
et al.
Summary: Achieving ambitious greenhouse gas mitigation targets will require technological advances and cost reductions in dispatchable carbon-free power generation sources that can provide load following flexibility to integrate high penetrations of variable wind and solar power. Several other sectors may be difficult to decarbonize and a net-zero or net-negative carbon economy may require the deployment of geologic carbon dioxide (CO2) storage. Utilizing CO2 as a working fluid for geothermal energy production and energy storage can achieve both goals: isolating CO2 from the atmosphere and providing valuable power system services to enable high penetrations of variable carbon-free electricity production. The use of CO2 as a working fluid facilitates access to low-grade heat in sedimentary basins, which are widely available and could allow for strategic citing near CO2 sources or where power system flexibility is needed. In this perspective piece, we summarize the state of knowledge for sedimentary basin CO2-geothermal, sometimes referred to as CO2 plume geothermal, and explore how it could support decarbonization of the energy sector. We also present the potential for using geologically stored CO2 for bulk energy storage which could provide valuable time-shifting and other services to the power grid. We explore the promise and challenges of these technologies, identify key research gaps, and offer a critical appraisal of the role that policy for a technology at the intersection of renewable energy, energy storage, and geologic CO2 storage may play in achieving broad deployment.
Renewable Energy Sources (RES) have been gaining popularity on a continuous basis and the current global political situation is only accelerating energy transformation in many countries. Objectives related to environmental protection and use of RES set by different countries all over the world as well as the European Union (EU) are becoming priorities. In Poland, after years of a boom in photovoltaic (PV) installations, the Renewable Energy Sources Act has been amended, resulting in a change to the billing system for electricity produced by individual prosumers. The change in the billing method, also in pursuance to the provisions of EU laws, has contributed to the inhibition of the PV installation market for fear of energy prices and investment payback time. In this paper, by using the Net Present Value (NPV) method, three mechanisms of billing of electricity from prosumer micro-installations—based on the net-metering principle and net-billing principle (using monthly and hourly prices)—have been analysed. Particular attention has also been paid to the aspects of electricity self-consumption and energy storages, which play a significant role in the economy of PV installations in the net-billing system.
The cooperation between Russia and China has been developing successfully in recent years. Both countries have agreed on several strategically important investment projects. The realization of investment projects determines the future expectation for developing Russian and Chinese economies. The article aims to investigate the trends and perspectives of economic cooperation between China and Russia in the field of mutual investments. The research methodology includes structuring, comparison, generalization, induction, deduction, and synthesis. Based on the research, the author concludes that the main segments of Russian-Chinese economic cooperation between state-owned enterprises are the energy sector, nuclear power engineering, agriculture, science, technology, and infrastructure. Also, there are good prospects for the investment segment of economic cooperation between Russia and China in banking, payment systems, and electricity sectors.
Leela McKinnon, David R Samson, Charles L Nunn
et al.
Sleep duration, quality, and rest-activity pattern-a measure for inferring circadian rhythm-are influenced by multiple factors including access to electricity. Recent findings suggest that the safety and comfort afforded by technology may improve sleep but negatively impact rest-activity stability. According to the circadian entrainment hypothesis, increased access to electric lighting should lead to weaker and less uniform circadian rhythms, measured by stability of rest-activity patterns. Here, we investigate sleep in a Maya community in Guatemala who are in a transitional stage of industrialization. We predicted that (i) sleep will be shorter and less efficient in this population than in industrial settings, and that (ii) rest-activity patterns will be weaker and less stable than in contexts with greater exposure to the natural environment and stronger and more stable than in settings more buffered by technologic infrastructure. Our results were mixed. Compared to more industrialized settings, in our study population sleep was 4.87% less efficient (78.39% vs 83.26%). We found no significant difference in sleep duration. Rest-activity patterns were more uniform and less variable than in industrial settings (interdaily stability = 0.58 vs 0.43; intradaily variability = 0.53 vs 0.60). Our results suggest that industrialization does not inherently reduce characteristics of sleep quality; instead, the safety and comfort afforded by technological development may improve sleep, and an intermediate degree of environmental exposure and technological buffering may support circadian rhythm strength and stability.
Bezzar Nour El-Houda, Laimeche Lakhdar, Meraoumia Abdallah
et al.
Recently, electricity consumption forecasting has attracted much research due to its importance in our daily life as well as in economic activities. This process is seen as one of the ways to manage future electricity needs, including anticipating the supply-demand balance, especially at peak times, and helping the customer make real-time decisions about their consumption. Therefore, based on statistical techniques (ST) and/or artificial intelligence (AI), many forecasting models have been developed in the literature, but unfortunately, in addition to poor choice of the appropriate model, time series datasets were used directly without being seriously analyzed. In this article, we have proposed an efficient electricity consumption prediction model that takes into account the shortcomings mentioned earlier. Therefore, the database was analyzed to address all anomalies such as non-numeric values, aberrant, and missing values. In addition, by analyzing the correlation between the data, the possible periods for forecasting electricity consumption were determined. The experimental results carried out on the Individual Household Electricity Power Consumption dataset showed a clear superiority of the proposed model over most of the ST and/or AI-based models proposed in the literature.
The grey model, which is abbreviated as GM (1, 1), has been widely applied in the fields of decision and prediction, particularly in the prediction of time series with few observations, referred to as the poor information and small sample in the literature related to grey model. Previous studies focus on improving the accuracy of prediction but pay less attention to the robustness of the grey model to outliers, which often occur in practice due to an incorrect record by chance or an accidental failure in equipment. To fill that void, we develop a robust grey model, whose structural parameters are obtained from the least trim squares, to forecast Chinese electricity demand. Also, we use the last value in the first-order accumulative generating time series as the initial value, according to the new information priority criterion. We name the novel grey model, proposed in this paper, the novel robust grey model integrating the new information priority criterion, which could be abbreviated as NIPC-GM (1, 1). In addition, we introduce a novel approach, that is, the bootstrapping test, to investigate the robustness against outliers for the novel robust grey model and the classical grey model, respectively. Using the data on Chinese electricity demand from 2011 to 2021, we find that not only does the novel robust grey model integrating the new information priority criterion have a better robustness to outliers than the classical grey model, but it also has a higher accuracy of prediction than the classical grey model. Finally, we apply the novel robust grey model integrating the new information priority criterion to forecasting the future values in Chinese electricity demand during the period 2022 to 2025. We see that Chinese electricity demand would continue to rise in the next four years.
Hirotaka Takano, Naohiro Yoshida, Hiroshi Asano
et al.
Demand response programs (DRs) can be implemented with less investment costs than those in power plants or facilities and enable us to control power demand. Therefore, they are highly expected as an efficient option for power supply–demand-balancing operations. On the other hand, DRs bring new difficulties on how to evaluate the cooperation of consumers and to decide electricity prices or rebate levels with reflecting its results. This paper presents a theoretical approach that calculates electricity prices and rebate levels in DRs based on the framework of social welfare maximization. In the authors’ proposal, the DR-originated changes in the utility functions of power suppliers and consumers are used to set a guide for DR requests. Moreover, optimal electricity prices and rebate levels are defined from the standpoint of minimal burden in DRs. Through numerical simulations and discussion on their results, the validity of the authors’ proposal is verified.
Cristian Bovo, Valentin Ilea, Enrico Maria Carlini
et al.
In this paper an optimization problem designed to calculate electric grid specific indicators to be used within model-based methodologies for the definition of alternative electricity market bidding zone configurations is designed. The approach integrates within the framework of a bidding zone review process aligned to the specifications of the Commission Regulation (EU) 2015/1222 (CACM) and Regulation (EU) 2019/943 of the European Parliament and of the Council (CEP). The calculated solution of the optimization provides locational marginal prices and allows to determine, outside the optimization problem, the power transfer distribution factors for critical elements. Both indicators can be used as inputs by specially designed clustering algorithms to identify model-based electricity market bidding zone configurations, as alternative to the current experience-based configurations. The novelty of the optimization problem studied in this paper consists in integrating the N-1 security criteria for transmission network operation in an explicit manner, rather than in a simplified and inaccurate manner, as encountered in the literature. The optimization problem is evaluated on a set of historical and significant operating scenarios of the Italian transmission network, carefully selected by the Italian transmission system operator. The results show the optimization problem capability to produce insightful results for supporting a bidding zone review process and its advantages with respect to simplified methodologies encountered in the literature.