Household Energy Consumption

Our research investigates the magnitude of the effect of residential energy efficiency audit programs on later household electricity consumption. These programs are designed to increase awareness of household energy consumption with personalized feedback that will eventually lead to behavioral changes. In this type of survey, there is only a one-time interaction between households, which participate voluntarily, and the surveyors. The objective of this study is to determine whether and to what extent such surveys lead to behavioral changes. We argue that the perceived complexity of the survey feedback will determine whether the subsequent behavior is sustainable. Then we analyze how persistent the intervention is over time and whether the effects decay or intensify. However, the main evaluation problem involving these surveys is self-selection bias. To correct for this bias, we propose two non-parametric estimators by using a kernel-based propensity score matching approach. In the first method, we use “difference-in-differences” (DID) estimations. The second estimator is quantile DID, which produces estimates on distributions. The comparison group consists of households who were not yet participating in the survey but participated later. The evidence suggest that the customers who participated in the survey reduced their electricity consumption by 6.7%, compared with customers who had not yet participated in the survey. In addition, as the quantiles of the distribution increase, the effect of the program decreases.

Demand-side flexibility has been suggested as a tool for peak demand reduction and large-scale integration of low-carbon electricity sources. Deeper insight into the activities and energy services performed in households could help to understand the scope and limitations of demand-side flexibility. Measuring and Evaluating Time-and Energy-use Relationships (METER) is a 5-year, UK-based research project and the first study to collect activity data and electricity use in parallel at this scale. We present statistical analyses of these new data, including more than 6250 activities reported by 450 individuals in 173 households, and their relationship to electricity use patterns. We use a regular-ization technique to select influential variables in regression models of average electricity use over a day and of discretionary use across 4-h time periods to compare intra-day variations. We find that dwelling and appliance variables show the strongest associations to average electricity consumption and can explain 49% of the variance in mean daily usage. For models of 4-h average Bde-minned^ consumption, we find that activity variables are consistently influential, both in terms of coefficient magnitudes and contributions to increased model explanatory power. Activities relating to food preparation and eating, household chores, and recreation show the strongest associations. We conclude that occupant activity data can advance our understanding of the temporal characteristics of electricity demand and inform approaches to shift or reduce it. We stress the importance of considering consumption as a function of time of day, and we use our findings to argue that a more nuanced understanding of this relationship can yield useful insights for residential demand flexibility.

This paper presents a study called the Energy Battle, a game aimed at encouraging home occupants to save energy. Twenty student-households were provided with direct feedback and an online platform with energy feedback over time, ranking of the competing teams, tips and a game. The study showed that the game context strongly influenced the motivation to save energy. Overall, savings averaged 24%, with the highest savings level at 45%. Directly after completion of the Energy Battle, energy consumption increased among most of the households, although consumption levels tended to stay below the baseline measurement level taken before the Energy Battle. Follow-up interviews indicated that some of the behaviours developed in the game had transformed into habits. A game such as the Energy Battle appears to provide a powerful means to stimulate energy saving in the short term. The potential to achieve long term effects appears possible, however further research is required to understand long-term implications for an Energy Battle game.

A B S T R A C T In a new environment marked by the growing importance of Green House Gas emissions, fuel poverty, and energy efficiency in the different national agendas, the comprehension of energy demand factors appears to be crucial for the effectiveness of energy policies. We consider the latter could be improved by targeting specific household groups rather than looking to follow a single energy consumption level target. This article explores the scope of having a disaggregated energy consumption market to design policies aimed at curbing residential energy consumption or lowering its carbon intensity. Using a clustering method based on the CHAID (Chi Square Automatic Interaction Detection) methodology, we find that the different levels of energy consumption in the French residential sector are related to socioeconomic , dwelling and regional characteristics. Then, we build a typology of energy-consuming households where targeted groups (fuel poor, high income and high consuming households) are clearly and separately identified through a simple and transparent set of characteristics. This classification represents an efficient tool for energy efficiency programs and energy poverty policies, but also for potential investors, which could provide specific and tailor made financial tools for the different consumer groups. Furthermore, our approach helps designing some energy efficiency score that could reduce the rebound effect uncertainty for each identified household group.

Environmental problems in the energy system often originate from everyday activities and choices. Everyday activities in the home are part of the private sphere, that can be contested in relation to energy policies. This article discusses the public-private divide in energy policies and how Swedish municipal energy consultants understand the divide. By analyzing the actions of energy consultants and their efforts to influence households, as well as how households perceive this guidance, I will discuss the public-private discourse in relation to energy policy and how this discourse can be a restriction for the energy consultants to reach their full potential.

The consultants found it problematic to discuss behavioral issues because they did not know how to relate to peoples everyday life activities without intruding on private and personal matters. For the households tailored information and feedback was not perceived as the consultant trespassing in the private sphere. Instead, the householders highlight the possibilities of such mapping. Lessoned learned from Sweden is that state subsidies to local energy consultants is a good way to reach households, but that they need to develop their methods and use more tailored information.

This paper tackles the problem of integrating household energy prosumers in Smart Energy Grids by analyzing a set of state-of-the-art energy forecasting techniques that allow individual or aggregated prosumers to evaluate their future energy demand and inform the Distributed System Operator (DSO) about potential grid imbalances. Thus, the DSO can perform a proactive strategy to manage the grid and avoid problems before they appear. The key element of this approach is the prediction technique, that must be accurate enough such that the resulting grid imbalances can be compensated in real-time. The paper evaluates a set of state-of-the-art statistical and Machine Learning (ML) prediction techniques, such as SARIMA, feed-forward and recurrent neural networks, support vector regression or ensemble prediction models, on real household historical energy demand logs by performing a feature selection process for each ML algorithm as to identify the best elements that influence the energy demand of a house. A set of experiments are performed on the REFIT Electrical Load Measurements data set evaluating each model's performance with respect to the selected features. Among the evaluated algorithms, the Ensemble Prediction Model gives best prediction accuracy, showing a Mean Absolute Percentage Error (MAPE) of 14.4% followed by the SVM model with a MAPE of 15.4%.

Authors: Trotta, Gianluca, Lorek, Sylvia, Spangenberg, Joachim H.
Abstract: Improving residential energy efficiency is widely recognised as one of the best strategies for reducing energy demand, combating climate change, and increasing security of energy supply. However, progress has been slow to date due to a number of market and behavioural barriers that have not been adequately addressed by energy efficiency policies and programmes.
This study is based on updated findings of the European Futures for Energy Efficiency Project that responds to the EU Horizon 2020 Work Programme 2014–2015 theme ‘Secure, clean and efficient energy’. This article draws on five case studies from selected European countries—Finland, Italy, Hungary, Spain, and the UK—and evaluates recent energy efficiency developments in terms of indicators, private initiatives, and policy measures in the residential sector. Our analysis shows that the UK government has implemented a better range of policies, coupled with initiatives from the private sector, aimed at improving energy efficiency. However, its existing conditions appear to be more problematic than the other countries. On the other hand, the lack of effective and targeted policies in Finland resulted in increased energy consumption, while in Hungary, Spain and Italy some interesting initiatives, especially in terms of financial and fiscal incentives, have been found.

Location is one of the key drivers of the consumption and mobility behaviour of people. Agglomeration results in concentrated activity nodes, better provision of public transportation and superior environmental infrastructure, and smaller living spaces that may decrease the environmental load of mobility and energy use. On the other hand, urbanized areas are the nodes of growth and consumption
that provide better accessibility to a wide spectre of commodities. This may in turn increase the environmental load of households living in more urbanized areas.
The thesis addresses the dilemma between the environmental benefits and disadvantages of urbanization across the settlement hierarchy of Estonia, aiming to receive new insights about the effect of location on the environmental load of final consumption. It explores the environmental load of the consumption and mobility behaviour of Estonian residents and analyses the carbon load of business travel along the travel needs and management in knowledge-intensive
business service sector.
The thesis applies environmentally extended input-output methodology to analyse the ecological footprint or carbon load of final consumption based on the data collected from high school students (2009) or acquired from Household Budget Survey that was conducted by Statistics Estonia (2012). The carbon load of business travel is explored with the help of data gained from active mobile positioning and individual interviews with business travellers, and focus group
interviews with organizations (2013). The concept of settlement hierarchy is used as a proxy for geographical location of residents and businesses.
The environmental load of the final consumption of households derives in majority from shelter-related consumption and is considerably lower in Estonia than in European countries of higher wealth. The differences in disposable income levels between the compared countries could lead to even higher differences in the environmental load. However, the high share of expenditure on domestic energy use among Estonian households due to the climatic conditions and poor insulation of dwellings as well as the carbon intensity of the energy sector in Estonia decrease the expectable environmental benefits deriving from lower overall expenditure volume. The size of the environmental load of Estonian residents could not be compared to other Eastern European countries due to the lack of conducted research available.
The findings of the thesis confirm the benefits of dense urban settlements over suburban or rural areas in terms of the environmental load from mobility.
Higher level urban settlements, nevertheless, do not show advantages in front of smaller towns, although it could be expected on the basis of previous research.
The benefits of higher level urban areas are evident only in case of business travel due to the economic agglomeration and concentration of businesses as professionals working in locations that are more distant need to put more efforts on reaching their business network in the main economic centres.
On the other hand, the thesis points out the lifestyle environmental impacts of additional consumption that occurs along higher degrees of urbanization both in dense urban cores and in their surrounding hinterland. Better availability and accessibility of various commodities, especially leisure-related goods and services, in higher hierarchy level settlements favour their consumption and the consequent environmental load also when differences in income levels and
other socio-demographic aspects of households are considered.
The thesis reveals the exceptional position of the residents of regional
industrial centres in Estonian settlement hierarchy considering their significantly low environmental load from final consumption. The very conservative consumption and mobility pattern of the households residing in the Eastern Estonian industrial cities is only partially explained by lower affluence level and different ethnical composition of the population when compared to the rest of the country. It may be assumed that the industrial character, founding and development peculiarities when compared to other cities in Estonia, environmental
problems, remnants of Soviet period scarcity-determined consumption
culture, lack of opportunities for self-expression, and low rate of social relations with the hinterland areas have hindered these regional centres to develop towards contemporary urban cores of active lifestyle.
The study on business travel showed that the need for business travel in
knowledge-intensive service sector considerably depends on the phase of the business cycle at hand. While the success of marketing and sales especially depends on physical co-presence, then core business processes, where the need for travel and communication is the highest, provide opportunities for some travel substitution with virtual modes of communication. Established trust relationships in business partnership are one of the main prerequisites for such substitution  and its environmental benefits.

The aim of this research is estimating the relationship between energy consumption, carbon (iv) oxide emission and industrial production. This relationship would be established for both Nigeria and South Africa. Time series data inputs sourced from the International Bank for Reconstruction and Development (IBRD) between 1980 and 2015 were used on the project. The usual preliminary analysis and formal tests were performed on the data before the Autoregressive Distributed Lag (ARDL) was applied in the model estimation. The choice of the ARDL was due to the results obtained from the formal tests, especially the unit root tests. The model estimation for the data took into account the need to lag the data to be able to achieve stationary property. Both short run and long run estimates were generated. Diagnostic tests were also carried out on the estimated models. The results coefficients for energy consumption and carbon (iv) oxide emission were obtained for short and long run for Nigeria and for only short run for South Africa. Conclusions and policy recommendations were then made to the government in line with the results of the model estimation. Top of the list is the regulation of energy consumption and carbon footprint via policies in the effort to increase industrial production.
Keywords: Energy Consumption,CO2 Emissions,Industrial production,Nigeria,South Africa,Models

Energy-saving is a very important issue that affects the end-users, power system quality and the global environment. Through the periodic energy bills of various energy agencies in Oman, it is possible to search for the causes of excessive consumption to reduce it with the search for the optimal solution with alternative energy sources. The main task of this research work is to help to reduce the electricity and energy costs by using Demand Side Management (DSM) approaches represented by the application of certain rationalization principles of energy usage and by using a model predictive control (MCP). As a result of that, an optimization algorithm for large-scale dynamic systems that take account of electricity costs, the work cycle, user requirements, system constraints and other input information is developed. The work used qualitative data from the perspective of the consumer, which was collected directly by the researcher or obtained from various sources related to the problem. An energy side management or simply energy demand response is proposed which ensures the optimum use of the equipments in the frame of a smart house.

En este texto se reconoce la importancia de los indicadores urbanos sustentables, así como del amplio y muy recorrido contexto, que a través de los años ha tenido el desarrollo sustentable, que junto con el cambio climático son los requirentes y, al mismo tiempo, promotores de indicadores que contribuyan al mejoramiento de la calidad de vida de las personas que habitan en las ciudades. La energía es fundamental para el desarrollo de las sociedades; el objetivo de desarrollo sostenible número siete es el interés oficial de la ONU en esta materia, el marco es la agenda 2030. Del conjunto de energías renovables, es la opción solar en conjunto con el aditamento tecnológico panel solar, la opción que cuenta con el mayor potencial para su implementación en el ámbito doméstico. Entonces, de acuerdo al panorama descrito, ha sido tarea desarrollar un indicador exploratorio para conocer la cobertura de la energía solar en los hogares mexicanos por estado de la República, utilizando como primer insumo hogares con energía eléctrica por panel solar. Se retoma la propuesta de enfoque “eficiencia energética desde el contexto de las ‘buenas prácticas’ y las energías limpias”. Bajo el enfoque mencionado se agruparon los datos relativos, se normalizaron y se ponderaron. Se realiza una revisión nacional para el año 2014 utilizando datos de INEGI. Se obtiene entonces un ranking, Durango y Sonora son los primeros de la lista. Se proporcionan algunas reflexiones respecto del ejercicio y de las áreas de oportunidad existentes.

In recent years, sensor networks are often deployed in several geographical regions to study certain phenomena. In this case, it may therefore happen that it is necessary to send a message to all the nodes of one or more regions for example to ask them to go into sleep mode. This problem is known in the literature as geographical routing (geocast). Several works have been proposed to solve this problem. In this paper we propose an energy-efficient and secured geocast protocol for a WSN deployed in space with data guarantee delivery to all nodes placed in one or more geocast regions. Our protocol consists of two major parts which are complementary and in addition of being secured, it is energy-efficient due to the fact that few messages are exchanged between the sensors during the first part of the algorithm.

Wireless sensor network consists of thousand number of sensor nodes employed in a wide range of data gathering application such as environmental gathering, military applications etc. Each sensor node in WS N are powered by battery having limited energy so it is very difficult to replace there batteries for prolonged the network life time. Maximizing the network lifetime have been most important design goal for the network. In WSN channel fading and radio interference constitute a big dispute in design of energy efficient communication protocol. To reduce fading and energy consumption in WSN, MIMO MISO SISO scheme is employed but implement multiple antenna technology to sensor network is improbable because of the sensor node generally support a single antenna. Cooperative scheme are utilized in WSN by applying the collective nature of the sensor nodes to provide reliable communication links in order to lower the total energy consumption. In this paper, the cooperative technique are inspected and by comparing different cooperative techniques we can elect the best cooperative scheme for energy constrained WS N application.

As fossil fuels become less attractive due to its high prices and environmental impact, the need to look at the demand side management became imperative for
sustainable energy and environment. However, in Nigeria, inadequate supply of energy and low production capacity couple with the need to fuel the most
promising economy has necessitated the need for energy efficiency and conservation. Residential and commercial sectors consume up to 80% of the total energy
consumption in the country. As such, there is need for a considerable reduction in these high energy consuming sectors for sufficient energy in other sectors
especially industrial sector. Subsequently, Energy demand in the country were analysed using indicators of trends, demand elasticities, energy intensities, and
future energy trends for the demand side analysis. Consequently, Energy Reduction Programme was considered the most appropriate DSM measure in the
country, but massive awareness campaign, new capacity building and electric metres for all consumers have to be provided.

This paper considers the role of occupants' efforts on reducing space-heating costs of panel apartments linked to district heating systems. We present the findings of a questionnaire survey conducted among residents of North-West Budapest (Hungary). Our results show limited efforts in the panel housing context, but a greater access to appropriate information about (limited) opportunities could significantly alleviate the burden on the households trapped in an inadequate space-heating regime.