The Critical Minimum Effort for Energy Poverty Challenge in India

The Socio-Economic and Caste Census of 2011 shows the extent of deprivations of rural India. Around 73.4 % of families are residing in rural India, where over 77 million households depend on kerosene for lighting; 1 million use wood and as many as 1.2 million households in India remain completely in the dark. Improvement in - Access, Availability, Adequacy, and Quality of energy can contribute to poverty reduction from various aspects. From a policy-making perspective increasing access to modern energy services require, first, the integration of energy access into national development strategies, and then strong and sustainable financial, institutional, and technology frameworks must be set up. The restatement of the theory of critical minimum effort is to make a plan for the effort that needs to break the environment of inertia of energy poverty. This paper discusses the minimum effort necessary to achieve a steady secular supply of basic energy requirements for people in need. It is alarming fact that today billions of people lack access to the most basic energy services, electricity, and clean cooking facilities, and, worse, this situation is set to change very little over the next 20 years. This paper explains how to set the needed change in the orientation and execution for the service delivery mechanism of energy. Aims: The restatement of the theory of critical minimum effort as a plan to achieve a steady secular supply of basic energy requirements for people in need. Study Design: Descriptive analysis. Place and Duration of Study: Macro-level analysis on India based on Socio-Economic and caste census of 2011. Methodology: Review-driven theoretical analysis. Conclusion: Restates those large-scale actions are needed to take people out of the vicious circle of energy poverty.

Perceived unknowns about gridless water, sanitation and energy services

This SEI report outlines issues that stakeholders in water, sanitation and energy sectors believe are holding back wider uptake of gridless technologies that have potential to extend access to needed services worldwide.

Contribution of Bioenergy to the Modern Energy Services in Ethiopia

Biomass based traditional energy has been the main energy supply in Ethiopia. Efforts are being made to shift to modern bioenergy utilization but the level of contribution of modern bioenergy to the total energy supply of the country’s supply is not computed. In this synthesis we described the contribution of bioenergy to modern energy utilization in the country. Data used here was retrieved from the country’s official reports and published literatures. Access to modern cooking services in the country was particularly focused on and both biogas feedstock productivities and biogas processing efficiencies were calculated. Herfindahl Index (HI) was calculated to observe the change in the diversity of the total primary energy supply due to bioenergy in the country. Results indicated that only a few households, 10%, had access to modern bioenergy services. Less than 0.10% of households have a biogas digester. The HI values showed the low diversity of the energy supply and the very limited contribution of modern bioenergy. This synthesis indicated that the contribution of modern bioenergy to the energy supply of the country is very low. Very low difference was observed between Herfindahl Indexes with and without considering modern bioenergy in the total primary energy supply (TPES) of the country is also found to be insignificant. Results found indicated lower diversity of the energy supply of Ethiopia and very limited contribution of modern bioenergy to the diversity and security of the energy supply.

Costing the cold: Connecting fuel poverty & supplier switching in Wellington, New Zealand

<p>Fuel poverty describes the inability of households to afford adequate energy services, such as space heating. In New Zealand, where 25% of households are estimated to be ‘fuel poor’, high electricity prices in a restructured electricity market have an important influence on fuel poverty. However, the ability of the New Zealand Government to regulate these high electricity prices is constrained. Consequently, there is a strong reliance on consumers to switch energy suppliers, which promotes competitive prices and in turn regulates the price of electricity. In contrast to energy efficiency improvements, switching offers fuel poor households a low-cost opportunity to improve the short-term affordability of energy services. Yet, switching is suggested to not benefit fuel poor households who are in most need of affordable energy. This thesis explored the relationship between fuel poverty and supplier switching in Wellington, New Zealand through a geographic lens. First, a new approach to identifying fuel poverty in New Zealand was applied. Using geographic information systems (GIS), a fuel poverty index was calculated to identify fuel poverty in Wellington at meshblock level. Spatial analysis of the index revealed the complexity of identifying fuel poverty and the extent to which the spatial distribution of fuel poverty in Wellington is shaped by the city’s colonial history. The index was then used to identify survey participants through which a survey was conducted exploring Wellington households’ switching behaviours. In a competitive market, consumers are expected to switch according to economically rational behaviours. However, switching behaviours in the survey sample were influenced by factors other than these economically rational behaviours. Integrating the findings of this thesis supports suggestions that switching is not benefiting the fuel poor. Finally, this thesis sheds light on the extent to which an understanding of the geography of fuel poverty can be applied towards improving the effectiveness of policy and equitable outcomes for fuel poor households.</p>

Costing the cold: Connecting fuel poverty & supplier switching in Wellington, New Zealand

<p>Fuel poverty describes the inability of households to afford adequate energy services, such as space heating. In New Zealand, where 25% of households are estimated to be ‘fuel poor’, high electricity prices in a restructured electricity market have an important influence on fuel poverty. However, the ability of the New Zealand Government to regulate these high electricity prices is constrained. Consequently, there is a strong reliance on consumers to switch energy suppliers, which promotes competitive prices and in turn regulates the price of electricity. In contrast to energy efficiency improvements, switching offers fuel poor households a low-cost opportunity to improve the short-term affordability of energy services. Yet, switching is suggested to not benefit fuel poor households who are in most need of affordable energy. This thesis explored the relationship between fuel poverty and supplier switching in Wellington, New Zealand through a geographic lens. First, a new approach to identifying fuel poverty in New Zealand was applied. Using geographic information systems (GIS), a fuel poverty index was calculated to identify fuel poverty in Wellington at meshblock level. Spatial analysis of the index revealed the complexity of identifying fuel poverty and the extent to which the spatial distribution of fuel poverty in Wellington is shaped by the city’s colonial history. The index was then used to identify survey participants through which a survey was conducted exploring Wellington households’ switching behaviours. In a competitive market, consumers are expected to switch according to economically rational behaviours. However, switching behaviours in the survey sample were influenced by factors other than these economically rational behaviours. Integrating the findings of this thesis supports suggestions that switching is not benefiting the fuel poor. Finally, this thesis sheds light on the extent to which an understanding of the geography of fuel poverty can be applied towards improving the effectiveness of policy and equitable outcomes for fuel poor households.</p>

A GIS-Based Approach to Estimate Electricity Requirements for Small-Scale Groundwater Irrigation

Access to modern energy services is a precondition to improving livelihoods and building resilience against climate change. Still, electricity reaches only about half of the population in Sub-Saharan Africa (SSA), while about 40% live under the poverty line. Heavily reliant on the agriculture sector and increasingly affected by prolonged droughts, small-scale irrigation could be instrumental for development and climate change adaptation in SSA countries. A bottom-up understanding of the demand for irrigation and associated energy services is essential for designing viable energy supply options in an effective manner. Using Uganda as a case study, the study introduces a GIS-based methodology for the estimation of groundwater irrigation requirements through which energy demand is derived. Results are generated for two scenarios: (a) a reference scenario and (b) a drought scenario. The most critical need is observed in the northern and southern regions of the country. The total annual irrigation demand is estimated to be ca. 90 thousand m3, with the highest demand observed in the months of December through February, with an average irrigation demand of 445 mm per month. The highest energy demand is observed in the northern part of the study area in January, reaching 48 kWh/ha. The average energy demand increases by 67% in the drought scenario. The study contributes to current gaps in the existing literature by providing a replicable methodological framework and data aimed at facilitating energy system planning through the consideration of location-specific characteristics at the nexus of energy–water–agriculture.

METHODOLOGICAL APPROACH TO ASSESSING THE MANAGEMENT MODEL OF PROMOTING GREEN ENERGY SERVICES IN THE CONTEXT OF DEVELOPMENT SMART ENERGY GRIDS

The transformation of the energy sector towards the development of the green energy sector provides a transition to climate-neutral economic development. In the presence of reserves of natural energy sources, a tendency towards a decrease in their use is monitored as a result of an increase in the share of consumption of green energy obtained from renewable energy sources (e.g. solar, wind). Taking this into account, the role of building an effective management model for the provision of green energy services is growing. The article proposes a methodological approach to assessing the effectiveness of the management model for promoting green energy services in the context of smart energy network development, based on the use of optimization methods and models. The promoting chain of green energy services is based on the rating assessment of energy service companies, the level of digitalization of business processes of enterprises and the formation of digital skills among consumers of various segments of the energy market, as well as a cybernetic approach to determining the ability to provide innovative energy services. For this, the peculiarities of artificial intelligence integration into socio-economic processes and the smart energy network constructions have been identified. The analysis of digital technology use level in the promotion of green energy services in the energy market of Ukraine is carried out. The determination of optimization criteria for assessing the effectiveness of the management model for promoting green energy services has been established. The determination of the optimization criteria for assessing the management model is based on obtaining an ecological effect, which made it possible to single out such criteria as maximizing the decarbonization rate of the environment and minimizing energy consumption costs. The using of such a methodological approach to assessing the effectiveness of the management model for promoting green energy services at energy enterprises will help to ensure a balance between production, distribution, supply of green energy and rational consumption of energy by different segments of consumers. Keywords: energy efficiency, energy saving, alternative energy, renewable energy sources, green electric power industry, energy enterprises, decarbonization. JEL Classification D29, L19, M31, Q21, Q40 Formulas: 10; fig.: 1; tabl.: 1; bibl.: 19.