Demand response and smart grids—A survey

Siano, Pierluigi

doi:10.1016/j.rser.2013.10.022

Cited by 1,973 publications

(914 citation statements)

References 53 publications

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“…Demand-side management (e.g., [2], [3]) and demand-response programs [4] provide incentives to domestic customers to adapt their behavior, or directly control their appliances. Commonly in these programs, customers have so-called smart appliances that can be steered within such a framework.…”

Section: Introductionmentioning

confidence: 99%

On the value of device flexibility in smart grid applications

Gerards

Hurink

2017

2017 IEEE Manchester PowerTech

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Abstract-Demand-side management and demand response are proposed as a means to solve different objectives in smart grids, such as, e.g., maximizing self-consumption of a house or peak shaving. Crucial components in these approaches are load shiftable/steerable devices, so-called smart appliances. Although several studies already use these devices and determine how to use their flexibility, their impact on-or value for-the overall system is not studied. This paper provides a methodology to calculate the value of flexibility of smart devices. The methodology makes it possible to quantitatively compare the impact of these devices for different kinds of objectives.The developed methodology is applied in a case study to compare the flexibility of white goods, home batteries and electric vehicles. The results indicate among others that smart white goods may not always be that important for smart grids.

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Section: Introductionmentioning

confidence: 99%

On the value of device flexibility in smart grid applications

Gerards

Hurink

2017

2017 IEEE Manchester PowerTech

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“…Demand response is defined as the changes in electric usage by end-use customers from their normal consumption patterns in response to changes in the price of electricity over time, or to incentive payments designed to induce lower electricity use at times of high wholesale market prices or when system reliability is jeopardized [39]. In order to coordinate different DR programs, DR providers [32] emerged in the smart structure of power system.…”

Section: Energy Management In Retail Electricity Marketmentioning

confidence: 99%

Retail Energy Management in Electricity Markets: Structure, Challenges and Economic Aspects- a Review

Golmohamadi

Keypour

2017

Technol Econ Smart Grids Sustain Energy

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In the rapidly growing global energy consumption, electrical energy plays the important role. Environmental concerns about air pollution, fossil fuels depletion and energy crisis have led policy makers of energy systems to increase the portion of electricity in the energy portfolio. On the other hand, economic crises, especially in recent years, have increased the electricity price. With decreased purchasing power, end-use consumers are encouraged to participate in Demand Side Management (DSM) programs, e.g. Demand Response Programs (DRPs), to decrease their electricity bills. In such situation, retail energy management attracts attention in both development and improvement. This paper reviews the concept of retail energy management in modern structure of electricity markets. The objectives of this study are: a) review techno-economic studies in the literature to identify the main structure of retail energy management; b) review the different retail market studies for assessing economic performance; c) present a comprehensive evaluation about the role of DRPs in retail energy management; d) carry out an extensive survey of optimization approaches, mathematical modeling and optimization software about the retail energy management. This paper provides a template for market participants to optimize energy management in the retail side of electricity markets. The proposed structure encourages the efficient development of retail electricity market while eliminating

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Section: Theory Of Load Managementmentioning

confidence: 99%

“…However, this tariff scheme requires fast response service levels and increased levels of granularity of control and of the speed of telemetry (Siano, 2014). The appointed DR benefit for the transmission and distribution operators of deferring investment in network reinforcement or increased long-term network reliability stated by Siano (2014) is worth investigating. The need for this study is strengthened by the existence of studies defending that DR can cause new demand peaks for electric utilities to deal with when day-ahead hourly prices are applied (Gottwalt, Ketter, Block, Collins, & Weinhardt, 2011).…”

Section: Theory Of Load Managementmentioning

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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Demand response and smart grids—A survey

Cited by 1,973 publications

References 53 publications

On the value of device flexibility in smart grid applications

On the value of device flexibility in smart grid applications

Retail Energy Management in Electricity Markets: Structure, Challenges and Economic Aspects- a Review

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

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