A survey of transmission technologies for planning long distance bulk transmission overlay in US

The purpose of this study is to determine the relationship between electric power consumption per capita (kWh) and real GDP per capita (PEN, constant 2007 prices), in Peru, during the period 1971–2014. The four theoretical hypotheses behind this relationship are the growth hypothesis –electricity consumption explains economic growth–, the conservation hypothesis –economic growth explains electricity consumption–, the feedback hypothesis –mutually affecting explanation between electricity consumption and economic growth–, and neutrality hypothesis –electricity consumption does not explain economic growth and vice versa–. Empirically, we initially conclude that the conservation hypothesis can be confirmed using the Granger Causality test, after estimating the dynamic impacts of the long-run equilibrium and short-run models. We highlight the inelastic behavior of electric power consumption per capita with regard to real GDP per capita. These results have implications for electricity conservation, expansive and security policies. We also discussed investments in electricity generation, transmission and distribution from renewable energy sources such as hydro, wind and solar. These eco-sustainable energies also called green and clean energies, are necessary for the sustainability of the electric power demand and the level of national electrification.

Electricity has been a key driver of global socioeconomic development and sustainability for both developed and developing nations. In Malaysia, electricity is primarily generated by burning fossil fuels, emitting greenhouse gases (GHG) that adversely impact the environment and public health. Therefore, accurately predicting electricity consumption is crucial for economic management, security analysis, facility scheduling for generation and distribution, and maintenance planning. This study aimed to develop a modified stacked ensemble multivariable Artificial Intelligence (AI)-based predictive algorithm, specifically Stacked Simple Linear Regression and Multiple Linear Regression (SLR-MLR), and Stacked Simple Linear Regression and Multiple Non-Linear Regression (SLR-MNLR) utilizing the Cross Industry Standard Process for Data Mining (CRISPDM) data science methodology. The proposed AI-based predictive algorithm aimed to provide predictive insights and interpret the impact of significant economic, environmental, and social clustered determinants on electricity consumption in Malaysia. The analysis revealed that the SLR-MLR predictive algorithm better fits Malaysias limited electricity consumption dataset compared to the existing Stacked SLR and e-Support Vector Regression (SLR-e-SVR) and SLR-MNLR predictive algorithms. It identified key economic and environmental clustered determinants that significantly impact electricity consumption in Malaysia. In academia, this study proposed an innovative SLR-MLR predictive algorithm and utilized a novel statistical approach to evaluate and select the superior predictive algorithm. Practically, it offered valuable insights for policymakers to craft efficient regulations, manage the energy sector proactively, and anticipate electricity generation and consumption trends. These contributions align with Malaysias economic and environmental sustainability goals outlined in the Twelfth Malaysia Plan, the Madani Economy Framework, the National Energy Policy 2022-2040, and the National Energy Transition Roadmap (NETR) agenda.

Electricity has a peculiar characteristic that it cannot be economically stored in large quantities. Electricity demand is the fastest growing form of energy consumed worldwide and it is predicted that the world's net electricity consumption will double by 2030. Therefore its generation and consumption need to be matched at all times. Demand side management (DSM) refers to the ability to alter end user electrical consumption in response to system conditions. It aims at improving energy efficiency through reduction of Kilowatt hours of energy consumption for the same service or activity. Other benefits of DSM could include higher end-use energy efficiency, improvement in quality and reduction in cost of power. Energy-efficiency improvements can slow the growth in energy consumption, save consumers money and reduce capital expenses for energy infrastructure. Innovative and efficiency improvements through DSM programmes have been carried out in a more open energy market. At the same time, government intervention has also been strengthened by the worsening of environmental situation and the need to significantly reduce emissions of greenhouse gases. DSM programmes are used to eliminate or reduce the need for additional peak or base load generating capacity and/or distribution facilities. Losing this opportunity to build efficiency into new economies would have serious financial, environmental and social consequences in the future. India is the world's sixth largest energy consumer. The power generating capacity increased from 66086 MW to 97846 MW during 1990-91 to 1999-2000 at an annual rate of 4.5%. The installed capacity of the power sector increased 60 fold between 1950 and 2000 at an annual growth rate of 8.5%. The per capita electricity consumption in India increased from 354.75 kWh in 1999-2000 to nearly 704.00 kWh in 2007-2008. The CO2 production in India has been showing an increasing trend in the new millennium in consonance with the rate of growth of Indian economy. Emissions per unit of electricity supplied from fossil fuels are estimated at 167 tonnes of carbon per GWh in 2005. In India power plants burn mostly coal with approximately 10-30% excess air. The national inventory of green house gases indicates that 55% of the total emissions in India come from energy sector. While public is interested in using energy more efficiently, there are several market barriers that prevent it from making rational investments in efficient technologies and practices. As the economy develops, households switch over from traditional fuels to modern and cleaner energy. Hence it is certain that household consumption of electricity is expected to increase rapidly with the increase in the growth of the economy and rise in per capita income. Urbanisation and increased flow of income call for ever-expanding sets of diverse needs. If those appliances are used efficiently, they will augment electric supply. Energy conservation potential for the economy as a whole has been assessed as 23% with maximum potential in industrial and agricultural sectors. At present new rare-earth phosphors have been developed to provide a warm light that is close in quality to the light of an incandescent. The new phosphors improve the colour of fluorescents with the same efficiency. Electricity for lighting represents approximately 34% of Indian peak power and roughly 17% of the electrical energy consumed. Incandescent lighting is estimated to constitute at least 17% of the peak demand, and roughly 10% of the national electricity consumption (135 TWh in 1984-85). Experts suggest that transferring subsidies from electricity to compact fluorescent lamps (CFLs) is a good proposition. Energy labelling provides information in a form that is objective and easy to understand for customers. The specified products are required to supply and declare energy data that has been determined when tested to the relevant Standard. The operating cost is also known as the 'second price tag,' and can help customers choose between models. Both energy labelling and standards stimulate technological change or innovation. This paper aims to examine electricity production and consumption at the All-India level and analyse the social and environmental aspects of electricity in the household sector.

Electricity has a peculiar characteristic that it cannot be economically stored in large quantities. Electricity demand is the fastest growing form of energy consumed worldwide and it is predicted that the world's net electricity consumption will double by 2030. Therefore its generation and consumption need to be matched at all times. Demand side management (DSM) refers to the ability to alter end user electrical consumption in response to system conditions. It aims at improving energy efficiency through reduction of Kilowatt hours of energy consumption for the same service or activity. Other benefits of DSM could include higher end-use energy efficiency, improvement in quality and reduction in cost of power. Energy-efficiency improvements can slow the growth in energy consumption, save consumers money and reduce capital expenses for energy infrastructure. Innovative and efficiency improvements through DSM programmes have been carried out in a more open energy market. At the same time, government intervention has also been strengthened by the worsening of environmental situation and the need to significantly reduce emissions of greenhouse gases. DSM programmes are used to eliminate or reduce the need for additional peak or base load generating capacity and/or distribution facilities. Losing this opportunity to build efficiency into new economies would have serious financial, environmental and social consequences in the future. India is the world's sixth largest energy consumer. The power generating capacity increased from 66086 MW to 97846 MW during 1990-91 to 1999-2000 at an annual rate of 4.5%. The installed capacity of the power sector increased 60 fold between 1950 and 2000 at an annual growth rate of 8.5%. The per capita electricity consumption in India increased from 354.75 kWh in 1999-2000 to nearly 704.00 kWh in 2007-2008. The CO2 production in India has been showing an increasing trend in the new millennium in consonance with the rate of growth of Indian economy. Emissions per unit of electricity supplied from fossil fuels are estimated at 167 tonnes of carbon per GWh in 2005. In India power plants burn mostly coal with approximately 10-30% excess air. The national inventory of green house gases indicates that 55% of the total emissions in India come from energy sector. While public is interested in using energy more efficiently, there are several market barriers that prevent it from making rational investments in efficient technologies and practices. As the economy develops, households switch over from traditional fuels to modern and cleaner energy. Hence it is certain that household consumption of electricity is expected to increase rapidly with the increase in the growth of the economy and rise in per capita income. Urbanisation and increased flow of income call for ever-expanding sets of diverse needs. If those appliances are used efficiently, they will augment electric supply. Energy conservation potential for the economy as a whole has been assessed as 23% with maximum potential in industrial and agricultural sectors. At present new rare-earth phosphors have been developed to provide a warm light that is close in quality to the light of an incandescent. The new phosphors improve the colour of fluorescents with the same efficiency. Electricity for lighting represents approximately 34% of Indian peak power and roughly 17% of the electrical energy consumed. Incandescent lighting is estimated to constitute at least 17% of the peak demand, and roughly 10% of the national electricity consumption (135 TWh in 1984-85). Experts suggest that transferring subsidies from electricity to compact fluorescent lamps (CFLs) is a good proposition. Energy labelling provides information in a form that is objective and easy to understand for customers. The specified products are required to supply and declare energy data that has been determined when tested to the relevant Standard. The operating cost is also known as the 'second price tag,' and can help customers choose between models. Both energy labelling and standards stimulate technological change or innovation. This paper aims to examine electricity production and consumption at the All-India level and analyse the social and environmental aspects of electricity in the household sector.

Hydrogen farm concept: A Perspective for Turkey

The article is dedicated to developing analytical tools for sustainable electric energy management in the energy savings system based on the consumer-regulator model and analytical and logistic approach principles. It has been established that one of the tools for sustainable electric energy management is energy efficiency and energy savings to increase efficiency in using the energy resources available to ensure the full functioning of the domestic energy system. Involving a household consumer in sustainable electric energy management processes as a business partner will allow one to balance all market participants’ interests in self-regulating the electricity consumption amount to meet their own needs. The features of new groups of household consumers of energy have been clarified and identified based on their readiness for technical participation in the electricity distribution system and load regulation, as well as their potential to attract funds to the development of the energy system. A complex model of a consumer involved in regulating electricity consumption has been proposed using an analytical and logistic approach. That proved it possible to reduce the power system load during the peak hours at 10:00 p.m. by 8.18 kWh, particularly for the «C-3» household type during the winter period, and to balance the nighttime declines in electricity consumption at the level of about 6 kW during the 11:00 p.m. to 7:00 a.m. period. It has been substantiated that consumers’ transition to nighttime consumption should be accompanied by improved tariff schemes to balance the interests of both household consumers and energy suppliers based on sustainable management principles.

The current electricity consumption information collection system collects the full amount of electrical parameters for large users with high frequency, while only very little data is collected for low-voltage residential users, which leads to the scale and quality of current low-voltage residential users' electricity consumption data to be improved and makes it difficult to discover phenomena such as electricity theft. In this paper, the electric power big data mining technology is used to model the electricity consumption behavior of low-voltage residential users. By using data extraction, de-duplication, completion, cleaning, conversion and other processing techniques, the value of electricity consumption data can be explored and the quality of data can be improved, so that the patterns of electricity consumption behavior under normal or abnormal conditions can be analyzed. Based on actual residential customers' electricity consumption scenarios, the clustering analysis of low-voltage residential customers' electricity consumption behavior patterns is carried out, and an accurate and stable electricity consumption pattern recognition algorithm is established, which greatly improves the utilization rate of electricity consumption data.

This paper mainly focuses on the future transmission technologies trend, such as regular long-distance transmission technology UHV AC and DC technology, flexible HVDC, DC grid, high $-T_{-}c$ superconductors DC, half wave-length AC transmission, Gas Insulated Line technology. The technology maturity assessment method is applied to evaluate the development of transmission technologies at different stage. Based on the analysis on future development trend of electric power transmission technology, three Asia power grids interconnection modes are proposed, which are UHV AC synchronous power grid, HVDC power supply and DC power grid. The relationship between transmission technology maturity and power grid structures is researched. According to the transmission technologies maturity assessment results, the future Asia power grid patterns are proposed in 2020, 2030 and 2050. Finally, the evolution law of future power grid is clarified by the correlation of key transmission technologies maturity value and power grid development situation.

In order to reach the peak of carbon emission in China by 2030 and to meet the low-carbon conversion of energy and the growing demand for electricity, this study aims to propose a more accurate and scientific method to calculate the carbon emissions of the entire power industry chain. This paper analyzes the historical actual operation data of the energy and power industry from 2000 to 2020, and originally proposes a carbon emission calculation model based on a multi-scenario simulation analysis of electricity consumption. This paper is an original study from the perspective of the whole industry chain of electricity production, transmission, and consumption. Firstly, a carbon emission model of the power system is established based on the carbon emission composition and transmission mechanism of the whole power industrial chain, which consists of calculation models for carbon emissions from overall electricity demand and carbon emissions from electricity network losses. Secondly, the concept of carbon emission coefficient is proposed, and the key parameters of the carbon emission coefficient of the power system are obtained through the econometric model. On this basis, the carbon emission coefficient is obtained by regression fitting of multiple key parameters according to historical data. Finally, electricity consumption per unit output value (ECPUOV) and per capita electricity consumption (PCEC) are used to predict electricity consumption in the next 15 years. This paper also makes a quantitative analysis of the relationship between CO2 emissions from the power system and electricity consumption. This paper takes G province, which ranks first in total energy consumption and economic aggregate in China, as an example and calculates its CO2 emissions and achievement of peak CO2 emissions by multi-scenario analysis. The case study results show that the low carbon scenario(LC) is the best route for G province to peak CO2 emissions from energy consumption. The method proposed in this paper can set an achievable goal of 2030 carbon peaking for the government and industry policymakers, and find a feasible implementation path.

Importance of renewable resource variability for electricity mix transformation: A case study from Germany based on electricity market data

On electricity consumption and economic growth in China

California has established aggressive Renewables Portfolio Standard (RPS) goals to increase the fraction of electricity generated from renewable energy resources and to decrease greenhouse gas emissions. Legislation AB 32 requires 20% of California’s electricity to come from renewables by 2010. More recently, an executive order has set a goal of 33% by 2020. Most of this new renewable generation will require the electric grid for delivering its electricity to customers. Renewable generators will be integrated into the grid at both transmission and distribution levels, but most of this capacity is expected to connect to the transmission system in locations remote from load centers and existing transmission infrastructure. Consequently, new transmission extensions must be built. But permitting and constructing new transmission are taking considerably longer than they do for the power plants the new transmission will serve, creating a significant challenge for meeting the RPS goals. Once connected to the grid, some of this renewable generation will exhibit properties, such as intermittency, quite different from traditional generation and loads, which pose special challenges for providing timely grid delivery capacity, maintaining reliability, and avoiding economic inefficiencies. Finally, power flow constraints through existing transmission “gateways” into population centers must be relieved before the electricity from renewables can reach customers. Meeting these challenges will require new or expanded capabilities for the grid. At higher RPS levels, the conventional “build” solutions, namely new extension lines, expanding the capacity of existing transmission gateways to load centers, and building conventional power plants for support, will prove inadequate by themselves, either because they are not the most cost effective or can’t be permitted. New transmission technologies offer the prospect of providing a substantial portion of these new or expanded capabilities to supplement these build solutions. This paper provides a technology development survey for achieving an electric transmission infrastructure functionally capable of performing its role in meeting the Renewables Portfolio Standard goals. These new technologies were examined in the context of providing three new or expanded broad capabilities: (1) Provide physical access for each new power plant, (2) Reliably accommodate any unique renewable generator behaviors, and (3) Increase the grid’s power carrying capacity to handle the additional electric power flows. Many of these new capabilities will foster a more intelligent, robust and flexible transmission system as part of the Smart Grid. This intelligence also opens the prospects for an expanded role for distributed renewable generation to help meet the RPS goals and reduce some of the burden on transmission. Finally new physical capabilities must be added to turn the intelligence into actions.

This article examines the empirical relationship between electricity consumption, economic growth, energy prices and technology development for India by taking annual time series data from 1981 to 2017. By using the ARDL bounds testing approach to co-integration, the study found long-run equilibrium relationship does exist among the variables. The article reports the existence of positive and significant impact of economic growth on electricity consumption, whereas technological development negatively affects electricity consumption in both the long run and short run. The Granger causality results reveal the presence of unidirectional causality from economic growth and technological development to electricity consumption in India. Therefore, the present study suggests policy makers in India to increase investment in electricity infrastructure to support high economic growth in the country. Further, the policy makers and the government should encourage more technological innovation to minimise usage of fossil fuels and support the use of green energy. This action could help the economy achieve a sustainable economic growth with better environmental quality. JEL Codes: C22, O4, O13, Q43, Q48

The article carries out a general analysis of electric power technologies in industrial production in the course of this study. It substantiates the importance of the electric power industry in the world economy. The most developed directions of electricity generation are considered. Their peculiarities and characteristic features are highlighted. The article gives a general analysis of the structure of world electricity production by types of power plants. It was revealed on the basis of this analysis that the largest volume of electricity generation is produced at coal fired power stations. A negative impact of the operation of coal-fired thermal power plants on the environment is described. The dynamics of world investments in renewable energy sources, as well as world GDP statistics and the dynamics of world electricity production according to regions are considered. The article highlights such regions as China, Europe and the United States, which are leaders in both production and consumption of electricity. They receive the largest investments for the development of technologies for generating electricity from renewable energy resources. As a result of the study, the assumptions were made about the existing environmental problems in some regions leading in the production and consumption of electricity. Also the article speculates about the existing need to replace less environmentally friendly energy sources with more environmentally friendly energy resources.

Effectively addressing today’s energy challenges requires advanced technologies along with policies that influence economic markets while advancing the public good.