Scheduling demand response events with constraints on total number of events per year

Tyagi, R. K.; Black, Jason; Petersen, Jon

doi:10.1109/ecce.2010.5618246

Cited by 5 publications

(3 citation statements)

References 4 publications

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“…For example, Dominion Virginia Power fixes 25 times per year as a CPP period. Each time is about 5 hours 21 . CPP highlights some periods of the year, in which the price is higher compared to the rest.…”

Section: Dynamic Pricingmentioning

confidence: 99%

A systematical analysis on the dynamic pricing strategies and optimization methods for energy trading in smart grids

Alsalloum

Merghem-Boulahia

Rahim

2020

Int Trans Electr Energ Syst

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Summary The smart grid (SG) is an enhancement of the traditional electrical grid. Its main objectives are diverse, focusing mainly on minimizing the energy cost, as well as energy consumption. The smooth integration of renewable energy balances energy production and consumption. Dynamic pricing (DP) becomes one of the important integrated solutions, which comes in line with the global efficiency and reliability of smart grids. DP incentivizes the consumer to participate in the energy scheduling decision, mainly in the real‐time decision. Consumer represents the key challenge in the SG in perspective to make the energy system more efficient. Moreover, the success of smart grids relies mostly on the evolution of the widely used optimization methods. These include measures to encourage consumers and providers to be involved in the development of the SG. The main objective of this article is to review and analyze the recent research works regarding the pricing strategies and optimization methods utilized in the context of SG. A systematic analysis is thus performed by considering twofold views. First, it comprehensively approaches the pricing majors and visualizes the game theory used in real‐time pricing. Second, it describes the optimization methods used in the smart grid context and compares them in terms of their complexity.

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Section: Dynamic Pricingmentioning

confidence: 99%

A systematical analysis on the dynamic pricing strategies and optimization methods for energy trading in smart grids

Alsalloum

Merghem-Boulahia

Rahim

2020

Int Trans Electr Energ Syst

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“…These considerations, along with the availability of cheaper communication and control technologies, suggest that the provision of flexibility by the demand side might be a viable alternative [6]. Tyagi et al showed that the optimal scheduling of DSM during critical price periods, particularly thermal loads, results in a significant reduction in the need for flexible generation units [7]. Kowli and Gross demonstrated using a security-constrained unit commitment that introducing DSM would reduce both load curtailment (and the corresponding losses of profit or comfort) and the need for investments in grid reinforcements [8].…”

Section: Introductionmentioning

confidence: 99%

Flexibility from the demand side

Kirschen

Rosso

Jian

et al. 2012

2012 IEEE Power and Energy Society General Meeting

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-The stochastic nature of renewable energy sources such as wind and sun introduces a new form of uncertainty in power system operation. The standard answer to the concerns that this increase in uncertainty raises is that the system should become more "flexible". However, there is as yet no agreement on exactly how much flexibility is needed or even a commonly accepted measure of flexibility. There is agreement however on the fact that flexibility has a cost and that this cost should be minimized in a way that does not affect reliability to facilitate the integration of these renewable energy sources. This presentation will explore how flexibility from demandside resources compares with the flexibility that fast ramping generating units can provide. In order to take into account the associated investment costs, this comparison relies on an extended unit commitment optimization that considers both short-and long-term aspects.Index Terms--Flexibility, demand side management, integration of wind generation, long-term unit commitment, reserve requirements.

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“…The optimal scheduling of DSM during critical price periods, particularly thermal loads, was explored in [7], resulting in a significant reduction in the need for flexible generation units. Using a securityconstrained unit commitment approach, [8] showed that introducing DSM would reduce both load curtailment (and the corresponding losses of profit or comfort) and the need for investments in grid reinforcements.…”

Section: Introductionmentioning

confidence: 99%

Assessing the contribution of demand side management to power system flexibility

Rosso

Jian

Kirschen

et al. 2011

IEEE Conference on Decision and Control and European Control Conference

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Abstract--The increasing penetration of renewable energy sources, particularly wind power, raises concerns about the level of flexibility needed to cope with the inherent variability and uncertainty affecting these sources of energy. Departing from the common conception of providing flexibility using fossil-fuelled generators with fast ramp rates, this paper explores the use of demand-side resources. A technique to optimize the balance between the flexibility provided by fast generating units and the flexibility achievable from demand side management (DSM) is presented. This methodology is based on an extended unit commitment optimization that considers both short-and longterm aspects, i.e. operational and investment costs. The methodology is applied to the IEEE RTS (RTS-96), using actual demand and wind profiles from central Scotland.Index Terms--Flexibility, demand side management, integration of wind generation, long-term unit commitment, reserve requirements.

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Scheduling demand response events with constraints on total number of events per year

Cited by 5 publications

References 4 publications

A systematical analysis on the dynamic pricing strategies and optimization methods for energy trading in smart grids

A systematical analysis on the dynamic pricing strategies and optimization methods for energy trading in smart grids

Flexibility from the demand side

Assessing the contribution of demand side management to power system flexibility

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