scholarly journals Energy Demand Management and Social Norms

Energies ◽  
2020 ◽  
Vol 13 (15) ◽  
pp. 3779
Author(s):  
Bernadeta Gołębiowska ◽  
Anna Bartczak ◽  
Mikołaj Czajkowski

The main objective of our study was investigating the impact of norms and financial motivation on the disutility of energy management for Polish households. We analyzed consumer preferences and willingness to accept demand-side management (DSM) programs. Choice experiment was applied for electricity contracts including external control of electricity consumption. Ajzen’s theory of planned behavior provided the theoretical framework of the study, which tested hypotheses about the impact of social norms on consumer choices of electricity contracts. We show that people with higher descriptive social norms about electricity consumption are less sensitive to the level of compensation and more responsive to the number of blackouts. People willing to sign a contract for financial reasons were less sensitive to the external control of electricity consumption and less inclined toward the status quo option. Injunctive social norms and personal norms had a non-significant impact on consumer decisions. We conclude that financial incentives can reduce the effect of the norms. Social and personal norms seem to be more important when we analyze the revealed preferences. European countries face significant challenges related to changes in energy policy. This study contributes to understanding the decisions of households and provides insights into the implementation of DSM.

2021 ◽  
Vol 13 (13) ◽  
pp. 7251
Author(s):  
Mushk Bughio ◽  
Muhammad Shoaib Khan ◽  
Waqas Ahmed Mahar ◽  
Thorsten Schuetze

Electric appliances for cooling and lighting are responsible for most of the increase in electricity consumption in Karachi, Pakistan. This study aims to investigate the impact of passive energy efficiency measures (PEEMs) on the potential reduction of indoor temperature and cooling energy demand of an architectural campus building (ACB) in Karachi, Pakistan. PEEMs focus on the building envelope’s design and construction, which is a key factor of influence on a building’s cooling energy demand. The existing architectural campus building was modeled using the building information modeling (BIM) software Autodesk Revit. Data related to the electricity consumption for cooling, building masses, occupancy conditions, utility bills, energy use intensity, as well as space types, were collected and analyzed to develop a virtual ACB model. The utility bill data were used to calibrate the DesignBuilder and EnergyPlus base case models of the existing ACB. The cooling energy demand was compared with different alternative building envelope compositions applied as PEEMs in the renovation of the existing exemplary ACB. Finally, cooling energy demand reduction potentials and the related potential electricity demand savings were determined. The quantification of the cooling energy demand facilitates the definition of the building’s electricity consumption benchmarks for cooling with specific technologies.


Energies ◽  
2020 ◽  
Vol 13 (16) ◽  
pp. 4154 ◽  
Author(s):  
Anthony Faustine ◽  
Lucas Pereira

The advance in energy-sensing and smart-meter technologies have motivated the use of a Non-Intrusive Load Monitoring (NILM), a data-driven technique that recognizes active end-use appliances by analyzing the data streams coming from these devices. NILM offers an electricity consumption pattern of individual loads at consumer premises, which is crucial in the design of energy efficiency and energy demand management strategies in buildings. Appliance classification, also known as load identification is an essential sub-task for identifying the type and status of an unknown load from appliance features extracted from the aggregate power signal. Most of the existing work for appliance recognition in NILM uses a single-label learning strategy which, assumes only one appliance is active at a time. This assumption ignores the fact that multiple devices can be active simultaneously and requires a perfect event detector to recognize the appliance. In this paper proposes the Convolutional Neural Network (CNN)-based multi-label learning approach, which links multiple loads to an observed aggregate current signal. Our approach applies the Fryze power theory to decompose the current features into active and non-active components and use the Euclidean distance similarity function to transform the decomposed current into an image-like representation which, is used as input to the CNN. Experimental results suggest that the proposed approach is sufficient for recognizing multiple appliances from aggregated measurements.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Timothy King Avordeh ◽  
Samuel Gyamfi ◽  
Alex Akwasi Opoku

Purpose The purpose of this paper is to investigate the impact of temperature on residential electricity demand in the city of Greater Accra, Ghana. It is believed that the increasing trend of temperatures may significantly affect people’s lives and demand for electricity from the national grid. Given the recurrent electricity crisis in Ghana, this study will investigate both the current and future residential energy demands in the light of temperature fluctuations. This will inform future power generation using renewable energy resources mix to find a sustainable solution to the recurrent energy demand challenges in Ghana. This study will help the Government of Ghana to better understand the temperature dependence of residential energy demand, which in turn will help in developing behavioral modification programs aimed at reducing energy consumption. Monthly data for the temperature and residential electricity consumption for Greater Accra Region from January 2007 to December 2018 obtained from the Ghana Meteorological Service (GMS) and Ghana Grid Company (Gridco), respectively, are used for the analysis. Design/methodology/approach This study used monthly time series data from 2007 to 2018. Data on monthly electricity demand and temperature are obtained from the Ghana Grid Company and GMS. The theoretical framework for residential electricity consumption, the log-linear demand equation and time series regression approaches was used for this study. To demonstrate certain desirable properties and to produce good estimators in this study, an analysis technique of ordinary least squares measurement was also applied. Findings This study showed an impact on residential electricity requirements in the selected regions of Greater Accra owing to temperature change. The analysis suggests a substantial positive response to an increase in temperature demand for residential electricity and thus indicates a growth of the region’s demand for electricity in the future because of temperature changes. As this analysis projects, the growth in the electricity demand seems too small for concern, perhaps because of the incoherence of the mechanisms used to regulate the temperature by the residents. However, two points should be considered when drawing any conclusions even in the case of Greater Accra alone. First, the growth in the demand for electricity shown in the present study is the growth of demand due only to increasing temperatures that do not consider changes in all the other factors driving the growth of demand. The electricity demand will in the future increase beyond what is induced by temperature, due to increasing demand, population and mechanization and other socioeconomic factors. Second, power consumption understated genuine electricity demand, owing to the massive shedding of loads (Dumsor) which occurred in Ghana from 2012 to 2015 in the analysis period that also applies in the Greater Accra region. Given both of these factors, the growth in demand for electricity is set to increase in response to climate change, which draws on the authorities to prepare more critically on capacity building which loads balancing. The results also revealed that monthly total residential electricity consumption, particularly the monthly peak electricity consumption in the city of Accra is highly sensitive to temperature. Therefore, the rise in temperature under different climate change scenarios would have a high impact on residential electricity consumption. This study reveals that the monthly total residential electricity demand in Greater Accra will increase by up to 3.1%. Research limitations/implications The research data was largely restricted to only one region in Ghana because of the inconsistencies in the data from the other regions. The only climate variable use was temperature because it was proven in the literature that it was the most dominant variable that affects electricity demand, so it was not out of place to use only this variable. The research, however, can be extended to capture the entire regions of the country if sponsorship and accurate data can be obtained. Practical implications The government as the policy and law-making authority has to play the most influential role to ensure adaptation at all levels toward the impact of climate change for residential consumers. It is the main responsibility of the government to arrange enough supports to help residential consumers adapt to climate change and try to make consumers self-sufficient by modification of certain behaviors rather than supply dependent. Government bodies need to carefully define their climate adaptation supports and incentive programs to influence residential-level consumption practices and demand management. Here, energy policies and investments need to be more strategic. The most critical problem is to identify the appropriate adaptation policies that favor the most vulnerable sectors such as the residential sector. Social implications To evaluate both mitigation and adaptation policies, it is important to estimate the effect of climate change on energy usage around the world. Existing empirical figures, however, are concentrated in Western nations, especially the USA. To predict how electricity usage will shift in the city of Greater Accra, Ghana, the authors used regular household electricity consumption data. Originality/value The motivation for this paper and in particular the empirical analysis for Ghana is originality for the literature. This paper demonstrates an adequate understanding of the relevant literature in modern times.


Author(s):  
S.G Priyadharshini ◽  
C. Subramani ◽  
J. Preetha Roselyn

<p>The worldwide energy demand is increasing and hence necessity measures need to be taken to reduce the energy wastage with proper metering infrastructure in the buildings. A Smart meter can be used to monitor electricity consumption of customers in the smart grid technology. For allocating the available resources proper energy demand management is required. During the past years, various methods are being utilized for energy demand management to precisely calculate the requirements of energy that is yet to come. A large system presents a potential esteem to execute energy conservation as well as additional services linked to energy services, extended as a competent with end user is executed. The supervising system at the utilities determines the interface of devices with significant advantages, while the communication with the household is frequently proposing particular structures for appropriate buyer-oriented implementation of a smart meter network. Also, this paper concentrates on the estimation of vitality utilization. In this paper energy is measured in units and also product arrangement is given to create bill for energy consumption and implementing in LabVIEW software. An IOT based platform is created for remote monitoring of the metering infrastructure in the real time. The data visualization is also carried out in webpage and the data packet loss is investigated in the remote monitoring of the parameters.</p>


Author(s):  
Jiaming Li ◽  
Glenn Platt ◽  
Geoff James

Management of a very large number of distributed energy resources, energy loads, and generators, is a hot research topic. Such energy demand management techniques enable appliances to control and defer their electricity consumption when price soars and can be used to cope with the unpredictability of the energy market or provide response when supply is strained by demand. We consider a multi-agent system comprising multiple energy loads, each with a dedicated controller. This paper introduces our latest research in self-organization of coordinated behavior of multiple agents. Energy resource agents (RAs) coordinate with each other to achieve a balance between the overall consumption by the multi-agent collective and the stress on the community. In order to reduce the overall communication load while permitting efficient coordinated responses, information exchange is through indirect communications between RAs and a broker agent (BA). This gives a decentralized coordination approach that does not rely on intensive computation by a central processor. The algorithm presented here can coordinate different types of loads by controlling their set-points. The coordination strategy is optimized by a genetic algorithm (GA) and a fast coordination convergence has been achieved.


2018 ◽  
Vol 49 ◽  
pp. 00013 ◽  
Author(s):  
Bartosz Chwieduk ◽  
Michał Chwieduk

The paper presents the results of calculations of energy consumption and economic analysis of the operation of micro photovoltaic installations. Calculations have been made for a single-family house with an energy demand based on real electricity consumption. Two cases have been considered. In the first one, the photovoltaic system contains only PV modules and an inverter. Energy produced is sent to the power grid. In the second case, the PV system also contains batteries. Because of existing regulation conditions, it is better to accumulate produced energy than to sell it to the grid. Costs of construction of the PV systems and money savings during operation of the PV systems have been compared. Conclusions of profitability of analyzed systems have been presented.


Energies ◽  
2020 ◽  
Vol 13 (20) ◽  
pp. 5360 ◽  
Author(s):  
Ha-Hyun Jo ◽  
Minwoo Jang ◽  
Jaehyeok Kim

Mounting evidence shows that economic and climate variables such as income, energy price, and temperature impact energy demand. We examined another variable, population age distribution, which has rarely been considered, that could affect energy demand. We employ population polynomials to account for the impact of population age distribution on residential electricity consumption in Korea. Using panel data from 1990 to 2016, we verify that populations aged 20~44, and those over 60, raise residential electricity consumption. We additionally evaluate the impact of population age distribution in forecasting future electricity consumption and conclude that age distribution effects dominate total population growth effects.


2018 ◽  
Vol 11 (1) ◽  
pp. 131-162
Author(s):  
Shimon Elbaz ◽  
Adriana Zaiț

AbstractThis research, based on a pilot study performed by the Israeli Electricity Company (IEC) in the framework of a demand management arrangement, focused on an economic approach for influencing domestic customers’ electricity consumption. The main objectives were to find out if monetary incentives in the form of a constant discount in the household consumer’s electricity bill (with no connection to consumption levels) influence consumers participating in a demand management arrangement with their electricity provider (here the IEC) and if such an incentive will lead to a decrease in the participants’ electricity consumption and/or a shift in their consumption from peak to low demand hours. The study examined also the monetary incentive’s influence on the participants’ willingness to join a future arrangement. The findings show that the participants who received a constant incentive increased their consumption, contrary to the expected behaviour, suggesting the presence of a “rebound effect”. One of the incentives that predicted a tendency to save electricity was the pro environmental attitude of the consumer, whereas financial incentives did not predict a tendency to save electricity. Damage to consumer comfort caused by load shedding exerted no significant influence. The economic incentive of a discount in the electricity bill increased the consumers’ willingness to join a future arrangement, even at the cost of compromising their privacy, although the possibility that this arrangement would lead to the loss of their control of home electric appliances as a result of load shedding drastically decreased this willingness. A positive financial incentive was found to have a minor influence on consumers’ willingness to participate in a demand management arrangement, while a negative incentive (the wish to avoid fines) was found to be very influential. Comparing to previous studies, the results are mixed, confirming some previous findings and contradicting others – and they offer an important contribution for the worldwide debate on energy conservation and household electricity reduction, through the Israeli dimension in a complex puzzle.


Author(s):  
Samuel Dunbar ◽  
Scott Ferguson

Abstract Demand Response (DR) is the implementation of a specific strategy or set of strategies, with the goal of altering consumer energy demand, such that some system level objectives are improved. These strategies typically include dynamic pricing, direct load control, policy implementation, or other financial incentives. DR will become a crucial tool for managing growing global energy demand in conjunction with higher penetration rates of intermittent renewable energy resources. Effective implementation of a DR strategy requires a realistic understanding of how consumers will respond to that strategy and how they will be affected by it. Here, a product-based decision model for residential consumers, that links consumer decisions directly to product-use, is revisited and adapted from a continuous time formulation to discrete time. The relationship between financial incentives, consumer preferences, and demand flexibility at the population level is then quantified. The model is used for exploring the tradeoffs between typical objectives for a dynamic pricing residential DR program and evaluating the characteristics of well-performing pricing solutions.


2010 ◽  
Vol 01 (03) ◽  
pp. 187-208 ◽  
Author(s):  
GUILHERME DEPAULA ◽  
ROBERT MENDELSOHN

This paper investigates the effects of climate on residential electricity use for households from different income classes in Brazil. Using cross-sectional data, the study finds that the temperature elasticity of electricity consumption varies significantly across income classes. The temperature elasticity of low income households is not significantly different from zero but middle and high income families have a long run temperature elasticity of 0.8 and 1.6 respectively. As emerging low latitude countries develop and incomes rise, the welfare damages of warming in the energy sector will become substantial.


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