Visualizing energy consumption activities as a tool for making everyday life more sustainable

Ellegård, Kajsa; Palm, Jenny

doi:10.1016/j.apenergy.2010.11.019

Cited by 124 publications

(65 citation statements)

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“…However, many of the survey participants owned multiple appliances and demonstrated high levels of appliance use and demonstrated high levels of appliance use, with obvious implications for electricity consumption. This is supported by Ellegard and Palm, who argue that increasing environmental awareness and knowledge of energy saving may not be sufficient on its own to reduce energy consumption in households [61]. One reason for this is the rapid growth in ownership of household appliances and poor levels of understanding amongst residents of how much energy each of these devices consume, even amongst those who are knowledgeable about energy and environmental issues [61].…”

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confidence: 95%

Environmental knowledge, pro-environmental behaviour and energy savings in households: An empirical study

2016

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Energy consumption in households comprises over a quarter of total energy use in the UK [1]. Human behaviour is one of the main factors that can influence domestic energy consumption, together with the physical properties of the dwelling, climate, number and demographic profile of occupants, household income, lifestyle, and appliance ownership and use [2][3][4][5]. Indeed, variation in residents' behaviour can cause significant differences in energy consumption between dwellings with otherwise similar characteristics (e.g. household size, income, and building energy performance) [3,6]. It is therefore important to understand influences upon behaviour in households as these in turn have implications for domestic energy use. In this respect, strategies to stimulate pro-environmental behaviour represent one means of modifying behaviour in households in order to promote energy conservation and reduce environmental impact [7].Pro-environmental behaviour is a form of environmental action that 'consciously seeks to minimize the negative impact of one's actions on the natural and built world ' [8, p.240], and 'only refers to those personal actions that are directly related to environmental improvement ' [9, p.325]. Such environmental actions can be performed individually or collectively, and may be direct or indirect in their approach to mitigating harm to, and improving, the environment [9]. Pro-environmental behaviours can also be influenced by internal factors such as environmental awareness, values and attitudes [10] and external factors such as social norms, interaction with other individuals and financial constraints [11,12].In this study we assess how environmental knowledge influences pro-environmental behaviour in households. We establish and confirm links between knowledge about the environment and energy, actions on Environmental knowledge, pro-environmental behaviour and energy savings in households: An empirical study AbstractIn this paper we evaluate the impact of knowledge about environmental and energy issues on potential pro-environmental behaviour in households, specifically relating to behaviours, attitudes and habits towards energy use. Our results are based on an empirical survey and we find significant correlations which indicate that residents with positive environmental values and greater environmental knowledge are more likely to demonstrate energy behaviours, attitudes and habits which lead to energy saving activities in households. This is further supported through a Principal Component Analysis (PCA), which suggests that energy saving behaviour may also vary according to gender and employment status. Conversely, we find only limited evidence of statistical associations between environmental predisposition and knowledge, and ownership and frequency of use of household appliances. We argue that our results contribute to the significant body of literature supporting the role of knowledge in active engagement with energy issues. This study is timely following closely policy developments in activ...

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confidence: 95%

Environmental knowledge, pro-environmental behaviour and energy savings in households: An empirical study

2016

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“…The evaluation of DR potential must be based on the knowledge of end-uses. A first approach, presented in the literature to investigate energy conservation potential, is to obtain activity patterns of customers, at the aggregate level, to identify customer activities (the so called "functional model" defined in [17]), for instance, customers requesting high amounts of energy and thus might have a significantly potential market for efficiency [34]. An alternative is the use ICT and NILM technologies, see for example [15].…”

Section: Characteristics Of the Customers: End-usesmentioning

confidence: 99%

“…Different variations on Equation (10) can be found in the literature [56,57] but they present some problems. For example: they do not consider some constraints in end-use flexibility due to electrical or service characteristics irrespective of energy price (it is not possible to switch-off or reduce demand for all the loads, for instance in the case of non-dimmable lights or washing machines, i.e., a change on switching times is possible but not a modulation of demand); load patterns or service requirements are not the same throughout the day (see Figure 3, or references [15,34]); some loads need a certain recovery period (to restore steady state service after control or to recover production schedule in the case of the industrial segment but this process is usually misunderstand and oversimplified [25,27]); the customer can apply some response previous to price peak periods but not during all the periods (for example precooling or preheating options are effective but only in periods near to peak-price response periods, i.e., E ik do not exists for none or many time periods); or the fact that changes in demand, due to substitution elasticity, involve an additional use of energy (i.e., thermal losses due to the switching of WH from service periods to 8-10 h before use). For these reasons, it seems more accurate (and complex) to apply a model for the evaluation of demand changes on each specific end-use (eu), D PDR k,eu linked with PBLM models that gives some feedback to model.…”

Section: Evaluation Of Pdr: An Economic Model To Evaluate the Size Ofmentioning

confidence: 99%

“…This behaviour has been taken into account together with overall demand to define approximate end-use profiles (notice that it is important to give customers and aggregators a broad portfolio of options, ranging from simple DR&EE options to more complex options). In this case, feedback from everyday activities [34] of the customer is important to refine profiles, improve DR&EE success and gain customer interest in energy concerns. Figure 4 shows the proposed end-use profiles for an average customer.…”

Section: Characteristics Of the Customers: End-usesmentioning

confidence: 99%

“…An interesting way to evaluate this response is through Physically Based Load Models (PBLM), a methodology first proposed to solve cold load pickup in [17]. This is the same idea proposed in thermal design software such as EnergyPlus or eQuest [18] but this approach is too complex to evaluate load response (EnergyPlus works high order state-space models, e.g., model order around [30][31][32][33][34][35][36][37][38][39][40] and it needs some simplification to make costs affordable and efforts feasible to engage DR. Some software, for example the toolbox BRCM is proposed in the VIRGIL platform, to simplify thermal models from EnergyPlus software, see [19].…”

Section: Introductionmentioning

confidence: 99%

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Abstract:The objectives of improving the efficiency, and integration, of renewable sources by are complex in practice and should be linked to an increase of demand-side flexibility. The main challenges to achieving this flexibility are the lack of incentives and an adequate framework. For instance, customers' revenue is usually low, the volatility of prices is high and there is not any practical feedback to customers from smart meters. The possibility of increasing customer revenue could reduce the uncertainty with respect to economic concerns, improving investments in efficiency, enabling technology and thus, engaging more customers in these policies. This objective could be achieved by the participation of customers in several markets. Moreover, Demand Response and Energy Efficiency can share ICT technologies but this participation needs to perform an aggregation of demand. The idea of this paper is to present some methodologies for facilitating the definition and evaluation of energy versus cost curves; and subsequently to estimate potential revenues due to Demand Response. This can be accomplished by models that estimate: demand and energy aggregation; economic opportunities and benefits; impacts on customer convenience; customer feedback and price analysis. By doing so, we would have comprehensive information that can help customers and aggregators to define energy packages and their monetary value with the objective of fostering their market participation.

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et al. 2024

Energy Science & Engineering

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Recently, energy has been a research area due to increasing awareness of its advantages. Energy is essential for all daily activities and helps the mind and body grows; it has the ability to determine the growth of an economy and the development of a country. However, energy has its disadvantages. Nonrenewable energy is energy such as fossil fuel, which is the main cause of air pollutant emissions, such as carbon dioxide, synthetic fluorinated gases, water vapor, and methane gases; and nuclear energy, its wastes are the main cause of air pollutant. They are also the main cause of global warming, human health, climate change, and environmental degradation from the extraction up to use. Nowadays, fossil fuel energy is used in production and use of energy in all sectors of the world. Nuclear energy is the most powerful energy source. Renewable energy, such as solar, wind, hydropower, geothermal, tidal, wave, and hydrogen energy, produces zero greenhouse gas emissions compared to fossil fuels, reducing air pollution and combating climate change, improving public health, mitigating smog and acid rain, and long‐term sustainability. The production and use of this renewable energy has been increasing, but it is not sufficient to meet the demand of all sectors in the world. Hydrogen energy is the future of fossil fuels and nuclear energy, free of CO2 emissions, and radioactive waste. The hydrogen economy envisions using hydrogen as a clean, versatile, and sustainable energy carrier to replace fossil fuels and reduce greenhouse gas emissions. We must control the impacts of energy first by knowing the types of energy and their impact, and then totally replace nonrenewable energy with renewable energy in the future by increasing the efficiency of renewable energy. To increase the efficiency of energy production, energy storage (storing high amount of energy in a small space) uses nanomaterials and green nanomaterial technologies. International cooperation and policy alignment will be essential for driving global transition to a sustainable energy future. By leveraging Artificial Intelligence (AI) and machine learning (ML), the energy sector becomes more sustainable, efficient, and resilient, supporting the transition toward a low‐carbon future. Harmonizing energy policies, sharing best practices, and aligning climate commitments can facilitate the development of a coordinated approach to addressing energy challenges on a global scale. By incorporating these considerations into energy planning and decision‐making, stakeholders can work toward building a future energy system that is sustainable, resilient, and capable of meeting the energy needs of a rapidly changing world. In this study, a critical review of the type, form, storage, advantages, efficiency, respective, and their impact are reviewed. The amounts of energy produced by each type in different years are discussed.

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Visualizing energy consumption activities as a tool for making everyday life more sustainable

Cited by 124 publications

References 21 publications

Environmental knowledge, pro-environmental behaviour and energy savings in households: An empirical study

Environmental knowledge, pro-environmental behaviour and energy savings in households: An empirical study

Integration of Methodologies for the Evaluation of Offer Curves in Energy and Capacity Markets through Energy Efficiency and Demand Response

Energy: An Overview of Type, Form, Storage, Advantages, Efficiency, and Their Impact

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