Quantifying the Effect of Demand Response on Electricity Markets

By C. Su, Daniel S. Kirschen. IEEE Transactions on Power Systems, 2007

501 citations recorded by the source corpus.

Subfields: Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/bce526fcaa7eb0572956c70ea1cea032e28e23f0

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In Electrical and Electronic Engineering

Citations in the corpus

Stochastic Unit Commitment With Uncertain Demand Response (2013, unknown): “[3].”
The rise of electric vehicles—2020 status and future expectations (2021, unknown): “Demand response and other forms of demand-side flexibility can be of value for power-system planning and operations (Albadi and El-Saadany 2007, 2008, Su and Kirschen 2009, Muratori et al 2014).”
Optimal demand response based on utility maximization in power networks (2011, background): “The modeling of cost function is an active research issue [11], [10], [7].”
An overview of Demand Response: Key-elements and international experience (2017, background): “The e ﬀ ect of price responsive demand on the market clearing prices was investigated in [106].”
Demand response in electrical energy supply: An optimal real time pricing approach (2011, background): “This group includes the 6 programs listed below [25,26]:”
Multi-Stage Robust Unit Commitment Considering Wind and Demand Response Uncertainties (2013, background): “Since the inelastic demand part has an infinite marginal value, we assume that the consumer surplus for the inelastic demand part is a constant as defined in [14].”
Influence of Price Responsive Demand Shifting Bidding on Congestion and LMP in Pool-Based Day-Ahead Electricity Markets (2011, methodology): “market clearing mechanisms developed in [9] do not take into account the operational and security constraints of transmission networks.”
Hourly Demand Response in Day-Ahead Scheduling Considering Generating Unit Ramping Cost (2013, background): “The first term in the objective function (4) is the customer’s gross surplus, which is constant for price-taking loads and not considered in the day-ahead scheduling [22].”
Optimal Planning to Include Storage Devices in Power Systems (2011, background): “Demand-side management has been proposed for relieving market volatility and for improving market efficiency [9]–[12].”
Challenges and barriers to demand response deployment and evaluation (2015, methodology): “A method is developed in [60] for quantifying the effect increasing penetration of DR resources providing load shifting can have on electricity markets.”