Clustering Methods for Electricity Consumers: An Empirical Study in Hvaler-Norway

The development of Smart Grid in Norway in specific and Europe/US in general will shortly lead to the availability of massive amount of fine-grained spatio-temporal consumption data from domestic households. This enables the application of data mining techniques for traditional problems in power system. Clustering customers into appropriate groups is extremely useful for operators or retailers to address each group differently through dedicated tariffs or customer-tailored services. Currently, the task is done based on demographic data collected through questionnaire, which is error-prone. In this paper, we used three different clustering techniques (together with their variants) to automatically segment electricity consumers based on their consumption patterns. We also proposed a good way to extract consumption patterns for each consumer. The grouping results were assessed using four common internal validity indexes. We found that the combination of Self Organizing Map (SOM) and k-means algorithms produce the most insightful and useful grouping. We also discovered that grouping quality cannot be measured effectively by automatic indicators, which goes against common suggestions in literature.Comment: 12 pages, 3 figure

Perspectives on subnational carbon and climate footprints: A case study of Southampton, UK

Sub-national governments are increasingly interested in local-level climate change management. Carbon- (CO2 and CH4) and climate-footprints—(Kyoto Basket GHGs) (effectively single impact category LCA metrics, for global warming potential) provide an opportunity to develop models to facilitate effective mitigation. Three approaches are available for the footprinting of sub-national communities. Territorial-based approaches, which focus on production emissions within the geo-political boundaries, are useful for highlighting local emission sources but do not reflect the transboundary nature of sub-national community infrastructures. Transboundary approaches, which extend territorial footprints through the inclusion of key cross boundary flows of materials and energy, are more representative of community structures and processes but there are concerns regarding comparability between studies. The third option, consumption-based, considers global GHG emissions that result from final consumption (households, governments, and investment). Using a case study of Southampton, UK, this chapter develops the data and methods required for a sub-national territorial, transboundary, and consumption-based carbon and climate footprints. The results and implication of each footprinting perspective are discussed in the context of emerging international standards. The study clearly shows that the carbon footprint (CO2 and CH4 only) offers a low-cost, low-data, universal metric of anthropogenic GHG emission and subsequent management

Coffee maker patterns and the design of energy feedback artefacts

Smart electricity meters and home displays are being installed in people’s homes with the assumption that households will make the necessary efforts to reduce their electricity consumption. However, present solutions do not sufficiently account for the social implications of design. There is a potential for greater savings if we can better understand how such designs affect behaviour. In this paper, we describe our design of an energy awareness artefact – the Energy AWARE Clock – and discuss it in relation to behavioural processes in the home. A user study is carried out to study the deployment of the prototype in real domestic contexts for three months. Results indicate that the Energy AWARE Clock played a significant role in drawing households’ attention to their electricity use. It became a natural part of the household and conceptions of electricity became naturalized into informants’ everyday language

(Position Paper) Characterizing the Behavior of Small Producers in Smart Grids:A Data Sanity Analysis

Renewable energy production throughout low-voltage grids has gradually increased in electrical distribution systems, therefore introducing small energy producers - prosumers. This paradigm challenges the traditional unidirectional energy distribution flow to include disperse power production from renewables. To understand how energy usage can be optimized in the dynamic electrical grid, it is important to understand the behavior of prosumers and their impact on the grid’s operational procedures. The main focus of this study is to investigate how grid operators can obtain an automatic data-driven system for the low-voltage electrical grid management, by analyzing the available grid topology and time-series consumption data from a real-life test area. The aim is to argue for how different consumer profiles, clustering and prediction methods contribute to the grid-related operations. Ultimately, this work is intended for future research directions that can contribute to improving the trade-off between systematic and scalable data models and software computational challenges.This work is financially supported by the Danish project RemoteGRID, which is a ForskEL program under Energinet.dk with grant agreement no. 2016-1-12399.Peer ReviewedPostprint (published version

Internet of Things-aided Smart Grid: Technologies, Architectures, Applications, Prototypes, and Future Research Directions

Traditional power grids are being transformed into Smart Grids (SGs) to address the issues in existing power system due to uni-directional information flow, energy wastage, growing energy demand, reliability and security. SGs offer bi-directional energy flow between service providers and consumers, involving power generation, transmission, distribution and utilization systems. SGs employ various devices for the monitoring, analysis and control of the grid, deployed at power plants, distribution centers and in consumers' premises in a very large number. Hence, an SG requires connectivity, automation and the tracking of such devices. This is achieved with the help of Internet of Things (IoT). IoT helps SG systems to support various network functions throughout the generation, transmission, distribution and consumption of energy by incorporating IoT devices (such as sensors, actuators and smart meters), as well as by providing the connectivity, automation and tracking for such devices. In this paper, we provide a comprehensive survey on IoT-aided SG systems, which includes the existing architectures, applications and prototypes of IoT-aided SG systems. This survey also highlights the open issues, challenges and future research directions for IoT-aided SG systems

Current and forthcoming issues in the South African electricity sector

One of the contentious issues in electricity reform is whether there are significant gains from restructuring systems that are moderately well run. South Africa's electricity system is a case in point. The sector's state-owned utility, Eskom, has been generating some of the lowest-priced electricity in the world, has largely achieved revenue adequacy, and has financed the bulk of the government's ambitious electrification program. Moreover, the key technical performance indicators of Eskom's generation plants have reached world-class levels. Yet the sector is confronted today with serious challenges. South Africa's electricity system is currently facing a tight demand/supply balance, and the distribution segment of the industry is in serious financial trouble. This paper provides a careful diagnostic assessment of the industry and identifies a range of policy and restructuring options to improve its performance. It suggests removing distribution from municipal control and privatizing it, calls for vertical and horizontal unbundling, and argues that the cost-benefit analysis of different structural options should focus on investment incentives and not just current operating efficiency.Energy Production and Transportation,Electric Power,Environment and Energy Efficiency,Energy and Environment,Infrastructure Economics

The Impact of Trade Liberalization on Household Welfare and Poverty in India

A 28-sector, 3-factor and 9-household group Computable General Equilibrium (CGE) model for India is constructed to analyze the impacts of Tariffs and Non-tariff Barriers (NTBs) on the welfare and poverty of socio-economic household groups. A general cut in tariffs leads to a decrease in overall welfare and reduction in poverty, which urban households are in a relatively better position to address. The choice of a fiscal compensatory mechanism with indirect tax on domestic consumption does not substantially change the pattern of impact except that it increases overall poverty in the economy. On the other hand, quota reductions on agriculture and food products result in a gain in welfare and a bigger reduction of poverty, with rural households doing better than urban households.Computable general equilibrium (CGE) model, microsimulations, International trade, poverty, India

The Fiscal Implications of Energy Transition in the Transport Sector: A Case Study of the Basque Country

Master in Economics: Empirical Applications and Policies. Academic Year 2022/23.This Master Thesis analyses the socioeconomic and fiscal challenges that arise from the transition towards a climate-neutral economy by 2050 in the Basque Country. The research focuses on the gradual elimination of fossil fuels in the transport sector and evaluates the socioeconomic and fiscal implications of the decarbonization policy proposed. The study also highlights the importance of sensitivity analysis and household’s consumption patterns in analyzing the socioeconomic and fiscal impact of the energy transition. Overall, this Master’s Thesis provides valuable insights into the fiscal implications of the energy transition in the transport sector and offers policy recommendations for a sustainable and climate-neutral economy