Hedging risks with interruptible load programs for a load serving entity

Hatami, Alireza; Seifi, Hossein; Sheikh‐El‐Eslami, Mohammad Kazem

doi:10.1016/j.dss.2009.07.007

Cited by 25 publications

(9 citation statements)

References 30 publications

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“…Valogianni and Ketter (2016) discuss the design of effective demand response programs based on a real-world pilot program. Other OR/MS work in this area focus on the design and valuation of interruptible service contracts 4 (Baldick et al 2006, Hatami et al 2009, Oren 2001, design of energy buy-back programs to reduce peak demand (Ding et al 2012), and consumer level decision making (Zakeri et al 2014).…”

Section: Electricity Marketsmentioning

confidence: 99%

Electric Power Industry: Operational and Public Policy Challenges and Opportunities

Parker

Tan

Kazan

2019

Production and Operations Management

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The electric power industry is undergoing dramatic change driven by rapid technological transformation, concern over climate change, and evolving market structures. As a result, there is a need for new models to help the industry better utilize resources in a time of increasing uncertainty and to help government policy makers better understand the impacts of their regulatory decisions. We provide a structured review of the operations research and management science literatures to describe the current operational and policy issues in the electric power industry, with a particular focus on issues surrounding electricity market design, renewable integration, effects of climate policy on electric power infrastructure, rise of electric powered vehicles, energy storage, and the growing interdependence between natural gas and electric power sectors. We identify the current research frontier and classify the existing research into clusters with respect to managerial issues addressed. We offer a forecast for where the electric power industry is going and describe some important public policy issues. Finally, we highlight research opportunities and discuss how the management science community can contribute by considering the interaction between operational considerations and electric power policy.

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Section: Electricity Marketsmentioning

confidence: 99%

Electric Power Industry: Operational and Public Policy Challenges and Opportunities

Parker

Tan

Kazan

2019

Production and Operations Management

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“…The stochastic ED can be solved by imposing a set of risk constraints, in the form of chance constraints in Fu and McCalley (2001) or mean-excess constraints in Ghosh et al (2011), to balance risk of shortfalls due to uncertain generation against cost of provisioning corrective generation sources such as peakers. Hatami et al (2009) propose a stochastic programming framework to determine the optimal procurement of interruptible load in order to minimize the risk of a shortfall over multiple periods. Hatami et al (2009) propose a stochastic programming framework to determine the optimal procurement of interruptible load in order to minimize the risk of a shortfall over multiple periods.…”

Section: Economic Dispatch With Renewable Resourcesmentioning

confidence: 99%

Optimization and Security Challenges in Smart Power Grids

Pappu¹,

Carvalho²,

Pardalos³

2013

Energy Systems

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“…The study in [10] considers an economic environmental dispatching model where wind and solar energy are both included but constrained to be no more than 30% of the total dispatched capacity. This is recognized in [11] where the authors propose a stochastic programming framework to determine the optimal procurement of interruptible load in order to minimize the risk of a shortfall over multiple periods. In [12], a set of risk constraints, in the form of chance-constraints, is imposed to balance risk of shortfalls due to uncertain generation against cost of provisioning corrective generation sources such a peakers.…”

Section: Introductionmentioning

confidence: 99%

Integration of demand response and renewable resources for power generation management

et al. 2011

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A single-period optimal dispatching problem is considered for a network of energy utilities connected via multiple transmission lines, where we seek to find the lowest operationalcost dispatching of various energy sources to satisfy demand. Our model includes traditional thermal resources and renewable energy resources available generation capabilities within the grid.A key novel addition is the consideration of demand reduction as a virtual generation source that can be dispatched quickly to hedge against the risk of unforeseen shortfall in supply. Demand reduction is dispatched in response to incentive signals sent to consumers. The control options of our optimization model consist of the dispatching order and dispatching amount of the thermal generators together with the rebate signals sent to end-users at each node of the network under a simple demand response policy. Numerical experiments based on our analysis of representative data are presented to illustrate the effectiveness of demand response as a hedging option.

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Hedging risks with interruptible load programs for a load serving entity

Cited by 25 publications

References 30 publications

Electric Power Industry: Operational and Public Policy Challenges and Opportunities

Electric Power Industry: Operational and Public Policy Challenges and Opportunities

Optimization and Security Challenges in Smart Power Grids

Integration of demand response and renewable resources for power generation management

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