Demand side management of electrical energy efficiency and environmental sustainability in India

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.

This paper attempts to re-examine the relationship between economic growth and electricity consumption in India for the period 1971-72 – 2016-17 for the country as a whole and for the agricultural and industrial sectors separately. Using gross value added (GVA) and per capita net national product (NNP) as indicators of economic growth techniques like cointegration, error correction model and Granger causality tests are applied for the study. The results indicate that there is a long run positive relationship between economic growth and electricity consumption when GVA is the indicator of growth. However, the short run coefficients are not statistically significant. Per capita NNP does not have any long run relationship with per capita electricity consumption but there is a unidirectional Granger-cause from log per capita NNP to log per capita electricity consumption when lag length is three. There is unidirectional Granger-causality from log GVA to log electricity consumption in the agricultural sector also. For the industrial sector, however, neither variable Granger causes the other. The cross section analysis for thirty two states and union territories of India reveals that per capita net state domestic product (NSDP) positively and significantly affects per capita electricity consumption of states in each of the years from 2012-13 to 2016-17. But the responsiveness of electricity consumption with respect to NSDP declines over the years.

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 paper explores the nexus between energy consumption (oil and electricity) and economic growth in the five SAARC countries over the period 1970-2006. Using cointegration and Error Correction Model (ECM), the paper finds a unidirectional short run and long run causality from oil consumption to economic growth in Bangladesh and Nepal, a unidirectional short run and long run causality from electricity consumption to economic growth in Pakistan and Sri Lanka, a unidirectional short run and long run causality from economic growth to oil consumption in India and Sri Lanka, and a unidirectional causality from economic growth to electricity consumption in India and Nepal. It also finds the bidirectional causality between electricity consumption and economic growth in Bangladesh and between oil consumption and economic growth in Pakistan. The paper at the end suggests that energy and environmental policies should recognize the differences in the energy consumption-growth nexus in order to maintain sustainable economic growth in the region.

Towards sustainable development: The impact of transport infrastructure expenditure on the ecological footprint in India

India is one of the largest producer and consumer of electricity in the world owing to being one of the most populous country in the world signifying the demand for electricity is only set to grow further. World has witnessed an era of economic growth aided pertinently by electricity consumption and growing demand. With FDI indorsed downright to this vital utilities sector, it becomes imperative to cognize the relationship of Electricity Consumption, Economic Growth and FDI in India. In this study we investigate the causal direction of relationship among Foreign Direct Investment, Electricity Consumption and Economic Growth in India by using time-series data for the period 1986–2021 and employing econometric models. We find two uni-directional causalities running from Electricity Consumption to Economic Growth and Economic Growth to FDI and a bi-directional causality between Electricity Consumption and FDI. The results of the study provide a novel perspective for policy makers while formulating policies related to the power sector and foreign direct investments in India. The focus of Policy makers should be on enabling electricity service providers to offer best services to commercial and non-commercial participants as it aids in Economic growth of the country. For enhanced economic growth a country like India must have good and world-class infrastructure, efficient and effective regulatory mechanism equitable for all stakeholders, an improved living standard for people of all economic strata and a stable, healthy business friendly environment coupled with policy stability through stable government.

The present paper tries to examine the Granger causality between per capita electricity consumption and per capita gross domestic product (GDP) at 2004-2005 prices for India using annual data covering the period 1970-1971 to 2015-2016. It applies error-correction model to examine the causal relationship between these two variables. The estimated results indicate that the per capita real GDP and per capita electricity consumption are co-integrated and there is unidirectional Granger causality running from real GDP to electricity consumption but not vice-versa. In the short run, the results of the causality test show that bidirectional causality flow from economic growth to electricity consumption in India. Thus the Government of India has to face the numerous energy challenges in the future.

The purpose of this study is to analyse the long-run causal relationship among the per capita electricity consumption ( PCEC) and per capita gross domestic product ( PCGDP), urban population ( UP) and employment ( EMP) pattern in India over the period of 1991–2018. To analyse the long-run association Johansen co-integration test has been used. The results of the Granger-causality test imply that there exists a bidirectional causal relationship between the PCEC and PCGDP whereas there exist unidirectional causality from EMP and UP to PCGDP. Jel Codes: L52, C53, P1

Effects of utility demand-side management programs on uncertainty

Electric utilities face a variety of uncertainties that complicate their long-term resource planning and acquisition. These uncertainties include future economic and load growths, fuel prices, environmental regulations, economic regulations, performance and construction cost of existing power plants, cost and availability of purchased power, and the costs and performance of new demand and supply resources. As utilities increasingly turn to demand-side management (DSM) programs to provide energy and capacity resources, it becomes more important to analyze the interactions between these programs and the uncertainties facing utilities. This report uses a new planning model (DIAMOND, developed at Oak Ridge National Laboratory) to explore quantitatively the uncertainty implications of supply-only vs DSM + supply resource portfolios. The analysis focuses on risks to society, with only limited attention to the allocation of risks among customers, shareholders, and others. Four sets of uncertainties are considered in these analyses: economic growth, fuel prices, the costs to build new power plants, and the costs to operate DSM programs. These four types of uncertainties serve as proxies for the many others that face utilities, including delays in completing power plants (proxied by cost of completing plants) and the energy and load reductions caused by DSM programs (proxied by cost of DSM programs). The two types of resource portfolios are tested against these four sets of uncertainties for the period 1990 to 2010. Sensitivity, scenario, and worst-case analysis methods are used. Results show that it is feasible to analyze the effects on uncertainty of including DSM programs in a utility`s resource mix. In light of these results, utilities, which to date have done very little such analysis, should conduct such studies as part of their integrated-resource planning activities.

Electric utilities face a variety of uncertainties that complicate their long-term resource planning and acquisition. These uncertainties include future economic and load growths, fuel prices, environmental regulations, economic regulations, performance and construction cost of existing power plants, cost and availability of purchased power, and the costs and performance of new demand and supply resources. As utilities increasingly turn to demand-side management (DSM) programs to provide energy and capacity resources, it becomes more important to analyze the interactions between these programs and the uncertainties facing utilities. This report uses a new planning model (DIAMOND, developed at Oak Ridge National Laboratory) to explore quantitatively the uncertainty implications of supply-only vs DSM + supply resource portfolios. The analysis focuses on risks to society, with only limited attention to the allocation of risks among customers, shareholders, and others. Four sets of uncertainties are considered in these analyses: economic growth, fuel prices, the costs to build new power plants, and the costs to operate DSM programs. These four types of uncertainties serve as proxies for the many others that face utilities, including delays in completing power plants (proxied by cost of completing plants) and the energy and load reductions caused by DSM programs (proxied by cost of DSM programs). The two types of resource portfolios are tested against these four sets of uncertainties for the period 1990 to 2010. Sensitivity, scenario, and worst-case analysis methods are used. Results show that it is feasible to analyze the effects on uncertainty of including DSM programs in a utility's resource mix. In light of these results, utilities, which to date have done very little such analysis, should conduct such studies as part of their integrated-resource planning activities.

Precise electricity forecasting is a pertinent challenge in effectively controlling the supply and demand of power. This is due to the inherent volatility of electricity, which cannot be stored and must be utilised promptly. Thus, this study develops a framework integrating canonical cointegrating regressions (CCR), time series artificial neural network (ANN) and a multilayer perceptron ANN model for analysing and projecting India's gross electricity consumption to 2030. Annual data for the years 1961–2020 have been collected for variables like gross domestic product (GDP), population, inflation GDP deflator (annual %), annual average temperature and electricity consumption. The study was conducted in three phases. In the first phase of the study, the CCR method was used to check the significance of the selected variables. In the second phase, the projected values of independent variables (GDP, population, inflation GDP deflator [annual %] and annual average temperature) were predicted using the time series ANN model. Finally, a multilayer perceptron ANN model with independent variables was used to forecast the gross electricity consumption in India by 2030. The result shows that the electricity consumption in India will increase by around 50% in the next 10 years, reaching over 1800 TWh in 2030. The proposed approach can be utilised to effectively implement energy policies, as an accurate prediction of energy consumption can help capture future demand.

Currently, there is a significant gap between electricity generation and consumption in Cameroon. Research has shown that electricity consumption in the country is estimated to increase by 965.7 GWh in five years, from 2020 to 2024 due to demographic and economic growth. Hence, this study aims to find methods that can be useful in developing strategies to balance the energy supply and demand in the country. This is done by developing models that can predict future electrical power consumption and generation. Correlation analysis and regression analysis were performed by using data obtained from various databases, and related models were developed accordingly. The model parameters were carbon dioxide emissions, electricity consumption per capita, final consumption expenditures, electricity installed capacity, fossil fuel installed capacity, labor force, and GDP. The models' results demonstrated excellent performance coefficients with RMSE of 0.17041, 0.23893, 0.27571, and 0.2465 for hydroelectricity generation, fossil fuel electricity generation, net electricity generation, and net electricity consumption respectively. Also, hydroelectricity generation, net electricity generation, and net electricity consumption models showed very good RRMSE performance indicating that the models can make predictions with only 4.26%, 5.26%, and 5.77% deviation from the mean values of hydroelectricity generation, net electricity generation, and net electricity consumption, respectively.

PurposeThe purpose of this paper is to examine potential demand side management (DSM) programs in terms of their impacts to the overall economy in Thailand.Design/methodology/approachA multi‐sector computable general equilibrium (CGE) model of Thailand has been developed to accomplish the objectives of this study. The potential DSM program considered refers to replacement of less efficient electrical appliances with their efficient counterparts in the household sector in Thailand.FindingsThe study finds that the economy‐wide impacts of the DSM program (e.g., economic welfare, GDP, international trade) depend on three key factors: the project economics of the DSM option or the ratio of unit cost of electricity savings to price of electricity (CPR); the implementation strategy of the DSM option; and scale or size of the DSM option. This paper shows that the welfare impacts of the DSM programs would improve along with the project economics of the DSM programs. If the DSM program is implemented under the CDM, the welfare impacts would increase along with the price for certified emission reductions units. On the other hand, the welfare impacts would increase up to the optimal size or scale of the program, but would start to deteriorate if the size is increased further.Research limitations/implicationsThe welfare function considered in this paper does not account for benefits of local air pollution reductions. The study provides crucial insights on designing DSM projects in Thailand to ensure that DSM programs are beneficial for the economy as a whole.Originality/valueAnalyses of DSM options under the CDM using CGE models are not available in the literature. This is the first paper in this area.

Domestic renewable electricity generation vs electricity imports: Meeting India’s long-run electricity consumption