Household response to dynamic pricing of electricity: a survey of 15 experiments

Faruqui, Ahmad; Sergici, Sanem

doi:10.1007/s11149-010-9127-y

Cited by 566 publications

(307 citation statements)

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“…A peak reduction of 0.23% is achieved as results and peak-to-valley is only decreased by 0.31%. These results do not match well with the results obtained in several pilots with Time-of-Use (ToU) and Critical-Peak Price (CPP) tariffs (about 6% in ToU and up to 20% in CPP, see [3]). In [52] a limit is considered for the so called "deferrable loads."…”

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

confidence: 58%

“…On the other hand, the consumer can also obtain interesting benefits from their participation in electricity markets, basically However, despite this considerable potential for DR&EE, electricity markets remain primarily driven by supply-side characteristics (for example, minimum level of energy offers and bids, or the requirements for monitoring and reporting energy changes). The idea being presented in this paper is that customers can benefit from future market opportunities and increased participation in retail (price-response with dynamic or critical price pricing tariffs [3]) and wholesale markets (incentive based DR and EE through, for instance, availability payments [4]) through aggregation while contributing to energy policies, market competitiveness and social welfare. The hypothesis is that demand resources should participate in the market on an equal footing as supply resources.…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2018

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

confidence: 58%

Section: Introductionmentioning

confidence: 99%

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

et al. 2018

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“…These communications will allow the residential sector response to real time pricing or RTP (Faruqui & Sergici, August, 2010). According to the European Commission vision, the introduction of AMR and bi-directional communications will enable RTP.…”

Section: Simulation Based Approachesmentioning

confidence: 99%

Methodology to simulate the impact of a large deployment of a residential energy management system in the electricity grid

Miguel

Neves

Martins

2014

Electric Power Systems Research

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This work proposes a methodology to evaluate the energy and power resources that can be made available through the deployment and use of a residential energy management system, as the Energy Box (EB) proposed by Livengood & Larson (2009). The impact on the electricity distribution system of such technology will result of changes in the electricity usage by end-use customers in response to stimuli like real-time changes in the electricity price, corresponding to the widely known demand response (DR). However, due to the dispersed and uncontrolled nature of the management of end-use appliances, estimating the energy and power output of the aggregation of a high number of EB's requires a specific approach which can take into account the random nature of load response.The approach that was followed simulated a certain universe of consumers from one particular city, using information regarding total electricity consumption as well as the segregated consumption per main appliance. The proposed methodology makes use of queried data regarding the willingness of consumers to postpone the start of appliances, as well as prototypes of hourly price diagrams. These prototypes were obtained through a data clustering exercise that was also proposed as part of the methodology. The possible environmental impact of the aggregated use of EB's was also estimated.The output of the methodology includes the range of released network capacity as well as load rebound, both caused by the aggregated EB response. In particular, load rebound is a relevant phenomenon that presents new challenges to the management of the grid, and for which some preventive measures are suggested.The analysis of the environmental significance of the aggregated EB resource shows that DR is not per se a tool to reduce CO 2 emissions, being strongly dependent of the generation technologies that are used to compensate demand variations. ResumoEste trabalho propõe uma metodologia para avaliar os recursos de energia e de potência que podem ser disponibilizados através da disseminação e utilização de um sistema de gestão de energia no sector residencial, como a Energy Box (EB) proposta por Livengood & Larson (2009). O impacto de tal tecnologia sobre o sistema de distribuição de energia elétrica irá resultar de mudanças no uso da eletricidade por utilização final de clientes em resposta a estímulos como mudanças em tempo real no preço da electricidade, correspondendo ao amplamente conhecido conceito de gestão da procura (DR). No entanto, a natureza dispersa e não controlada da gestão destas cargas exige uma abordagem que tenha em conta o caráter aleatório do comportamento desta procura para efetuar uma estimativa agregada do consumo de energia e da potência causados por um elevado número de dispositivos EB.A abordagem que foi seguida exigiu a simulação de um determinado universo de consumidores de uma determinada cidade, utilizando informações sobre o consumo total de energia eléctrica, bem como o consumo por eletrodoméstico. A metodologia proposta faz uso de...

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“…While industrial and commercial buildings make use of demand response opportunities all around the world, the vast majority of residential buildings cannot use these opportunities [11]. It is the opinion that dwelling comfort may be reduced and energy consumption habits are the biggest obstacle for the implementation of demand respond programs at homes [12]. However, intelligent home energy management systems have gained popularity in recent years with the aim of enhancing the dwelling comfort in parallel with the advances in information and internet technologies [13,14].…”

Section: Introductionmentioning

confidence: 99%

The Determination of Load Profiles and Power Consumptions of Home Appliances

Issi

Kaplan

2018

Energies

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Abstract:In recent years, the increment of distributed electricity generation based on renewable energy sources and improvement of communication technologies have caused the development of next-generation power grids known as smart grids. The structures of smart grids have bidirectional communication capability and enable the connection of energy generated from distributed sources to any point on the grid. They also support consumers in energy efficiency by creating opportunities for management of power consumption. The information on power consumption and load profiles of home appliances is essential to perform load management in the dwelling accurately. In this study, the power consumption data for all the basic home appliances, utilized in a two-person family in Çankırı, Turkey, was obtained with high resolution in one-second intervals. The detailed power consumption analysis and load profile were executed for each home appliance. The obtained data is not only the average power consumption of each appliance but also characterizes different operating modes or their cycles. In addition, the impact of these devices on home energy management studies and their standby power consumptions were also discussed. The acquired data is an important source to determine the load profile of individual home appliances precisely in home energy management studies. Although the results of this study do not completely reflect the energy consumption behavior of the people who live in this region, they can reveal the trends in load demands based on a real sample and customer consumption behavior of a typical two-person family.

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Household response to dynamic pricing of electricity: a survey of 15 experiments

Abstract: Dynamic pricing, Price elasticity, Elasticity of substitution, Demand models, Demand response, Rate design, L51, L94, D00,

Cited by 566 publications

References 9 publications

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

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

Methodology to simulate the impact of a large deployment of a residential energy management system in the electricity grid

The Determination of Load Profiles and Power Consumptions of Home Appliances

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