Demand Response Scheduling by Stochastic SCUC

By Masood Parvania, M. Fotuhi‐Firuzabad. IEEE Transactions on Smart Grid, 2010

487 citations recorded by the source corpus.

Subfields: Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/0c317e00059074a16cc107d7b4ee78b76c458cbd

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In Electrical and Electronic Engineering

Citations in the corpus

Unit Commitment With Continuous-Time Generation and Ramping Trajectory Models (2016, background): “, fuel switching and fuel-blending capabilities, combined cycle units), [6] modeled demand response assets used as contingency reserves to enhance system security, and many others.”
A bilevel model for electricity retailers' participation in a demand response market environment (2013, methodology): “…of demand response, which are often either heuristically approached, see Ilić et al. (2011a) and Ilić et al. (2011b), or simply discarded by making use of static elastic demand as in Parvania and Fotuhi-Firuzabad (2010), Sioshansi (2010), Algarni and Bhattacharya (2009) and Nguyen et al. (2011).”
Smart Grid — The New and Improved Power Grid: A Survey (2012, unknown): “Since the renewable energy supply is often a time-varying process, other optimization techniques such as stochastic programm ing [150, 178, 194, 192, 48, 49] and robust programming [53] are also widely used.”
Intelligent Multi-Microgrid Energy Management Based on Deep Neural Network and Model-Free Reinforcement Learning (2020, background): “that reside in the microgrid, where um(t) is a 0-1 binary variable indicating whether the zth demand response block qm(t) is dispatched or not, and ecm is the unit price [26].”
Spinning Reserve Estimation in Microgrids (2009, methodology): “Similar to the classification of the analytical SR optimization methods, the stochastic SR optimization methods include successive iteration of stochastic UC [28], reliability constrained stochastic UC [29], and stochastic programming based on the cost/benefit analysis [11, 30-34].”
Energy Pricing and Dispatch for Smart Grid Retailers Under Demand Response and Market Price Uncertainty (2015, methodology): “A stochastic SCUC approach is introduced in [9], considering both demand-side reserve bids provided by an aggregator, and random outages of generating units or transmission lines.”
A Review of Smart Cities Based on the Internet of Things Concept (2017, methodology): “Applying these methods will lead to reliability improvement, power quality enhancement and proﬁt growth [60].”
A Survey on Demand Response Programs in Smart Grids: Pricing Methods and Optimization Algorithms (2015, background): “DR programs can be further sub-categorized into classical programs and market-based programs, while they can be offered in both retail and wholesale markets [131].”
A Survey on Demand Response in Smart Grids: Mathematical Models and Approaches (2015, background): “Similarly, in the presence of load uncertainty as well as equipment failures, the authors in [84] and [85] formulate and solve the stochastic mixed-integer programming problem for demand response.”
Iot-based smart cities: A survey (2016, background): “consumers can adjust the electricity usage pattern with the aim of reliability enhancement or to prevent the power price spikes [32, 33].”