Measuring the Capacity Impacts of Demand Response

Earle, Robert; Kahn, Edward; Macan, Edo

doi:10.1016/j.tej.2009.05.014

Cited by 58 publications

(34 citation statements)

References 2 publications

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“…However, this effect generally appears a few hours after the event, associated with a rebound effect, at a time when the level of demand is still high. The rebound effect occurs due to massive load-shifting, creating another peak in demand which undermines system reliability (Earle et al, 2009). Under rebound and reconnection effects, the positive impacts of load-shedding may be reduced or altogether reversed.…”

Section: Load-shedding and The Rebound Effectmentioning

confidence: 99%

Demand-side management and European environmental and energy goals: An optimal complementary approach

2014

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To cite this version:Claire Bergaentzlé, Cédric Clastres, Haikel Khalfallah. Demand-side management and European environmental and energy goals: an optimal complementary approach. Energy Policy, Elsevier, 2014, 67 (April) AbstractDemand side management (DSM) in electricity markets could improve energy efficiency and achieve environmental targets through controlled consumption. For the past 10 years or so DSM programmes have registered significant results. However, detailed analysis of its real impact as observed by a large number of pilot studies suggests that such programmes need to be fine-tuned to suit clearly identified conditions. This study aims to provide recommendations for the instruments to be used to prompt demand response with a view to maximizing energy and environmental efficiencies of various countries. The present study suggests that different DSM models should be deployed depending on the specific generation mix in any given country. Beside the natural benefits from crossborders infrastructures, DSM improves the flexibility and reliability of the energy system, absorbing some shock on generation mix. We show efficiency increases with demand response but at a decreasing rate. So, according to rebound and report effects, simple DSM tools could be preferred.

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Section: Load-shedding and The Rebound Effectmentioning

confidence: 99%

Demand-side management and European environmental and energy goals: An optimal complementary approach

2014

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“…The capacity impacts of demand response were discussed in [24], which concluded that although more flexible DR programs can improve the decreasing returns of scale in capacity value, excessive amounts of DR also possess decreasing returns to scale. In [25], the authors integrated the DR programs into three expansion models with wind power, and both the own-and cross-elasticities of DR were considered.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Further, constraint (23) implies that DR capacity is also allowed to be part of the operating reserves in the hours of load shifting, and also sets the DR capacity as the limit of the total load shifted plus the DR capacity that accounts for part of the operating reserves. The new model includes constraints (1), (2), (6) - (12), and (20) - (24).…”

Section: B Demand Response Modeled As Operating Reservementioning

confidence: 99%

Impact of demand response on thermal generation investment with high wind penetration

Jin

Botterud

Ryan

2014

2014 IEEE PES General Meeting | Conference &Amp; Exposition

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We present a stochastic programming model for investments in thermal generation capacity to study the impact of demand response (DR) at high wind penetration levels. The investment model combines continuous operational constraints and wind scenarios to represent the implications of wind variability and uncertainty at the operational level. DR is represented in terms of linear price-responsive demand functions. A numerical case study based on load and wind profiles of Illinois is constructed with 20 candidate generating units of various types. Numerical results show the impact of DR on both investment and operational decisions. We also propose a model in which DR provides operating reserves and discuss its impact on lowering the total capacity needed in the system. We observe that a relatively small amount of DR capacity is sufficient to enhance the system reliability. When compared to the case with no DR, a modest level of DR results in less wind curtailment and better satisfaction of reserve requirements, as well as improvements in both the social surplus and generator utilization, as measured by capacity factors. The authors acknowledge the U.S. Department of Energy's Wind Power Program, for funding the research presented in this paper. The submitted manuscript has been created by UChicago Argonne, LLC, Operator of Argonne National Laboratory (''Argonne''). Argonne, a U.S. Department of Energy Office of Science laboratory, is operated under Contract No. DE-AC02-06CH11357. The U.S. Government retains for itself, and others acting on its behalf, a paid-up non-exclusive, irrevocable worldwide license in said article to reproduce, prepare derivative works, distribute copies to the public, and perform publicly and display publicly, by or on behalf of the Government.Shan

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“…This contribution of DR to real-time balancing, coupled with the fact that DR can help compensate supply shortages with load reductions in case of generation outages, may entail a reduction in the requirements of operating reserves for a certain level of short-term reliability of supply (or to increase short-term reliability of supply for a certain level of operating reserves) [23].…”

Section: Potential Benefits Of Demand Responsementioning

confidence: 99%

The Economic Impact of Demand-Response Programs on Power Systems. A Survey of the State of the Art

Conchado

Linares

2011

Energy Systems

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Demand Response (DR) programs, which aim to reduce electricity consumption in times of high energy cost or network constraints by allowing customers to respond to price or quantity signals, are becoming very popular in many electricity systems, frequently associated to smart-grid developments. These programs could entail significant benefits for power systems and the society as a whole. Assessing the magnitude of these benefits is crucial to determine their convenience, especially when there are non negligible costs associated to their implementation (if advanced metering infrastructure or control technologies are needed). Quantifying DR benefits requires first to estimate the changes in demand patterns that can potentially be achieved and then to evaluate the effects of those changes on the complex behavior of power systems, neither of these analyses being trivial. This paper presents a survey of the state of the art of these assessments.

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Measuring the Capacity Impacts of Demand Response

Cited by 58 publications

References 2 publications

Demand-side management and European environmental and energy goals: An optimal complementary approach

Demand-side management and European environmental and energy goals: An optimal complementary approach

Impact of demand response on thermal generation investment with high wind penetration

The Economic Impact of Demand-Response Programs on Power Systems. A Survey of the State of the Art

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