Optimal response of a thermal unit to an electricity spot market

By J. M. Arroyo, Antonio J. Conejo. 2000

588 citations recorded by the source corpus.

Subfields: Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/954bf892f8200f09c2a07a40c0a9b2bb802e465c

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In Electrical and Electronic Engineering

Citations in the corpus

A Stochastic Programming Approach to Electric Energy Procurement for Large Consumers (2007, background): “Constraints (13)–(17) are required to model the piecewise linear production cost of the self-production unit [5].”
Unit commitment by enhanced adaptive Lagrangian relaxation (2004, background): “Meanwhile, mixed integer linear programming (MILP) has been proposed to solve generation scheduling [10]–[12].”
Price-Taker Bidding Strategy under Price Uncertainty (2002, background): “Finally, the following set of linear constraints formulates the feasible operating region, , comprising power limits, ramp rate limits and minimum up and down time constraints [4]”
Application of information-gap decision theory to risk-constrained self-scheduling of GenCos (2013, methodology): “However, a start-up cost as a function of off-time duration can easily be implemented [3].”
ARIMA Models to Predict Next-Day Electricity Prices (2002, background): “With a good next-day price forecast, a producer can develop an appropriate strategy to maximize its own benefit, or a consumer can maximize its utility [1], [2].”
Information gap decision theory approach to deal with wind power uncertainty in unit commitment (2017, unknown): “This 225 UC model is adopted from [31] and is briefly expressed as follows.”
A State Transition MIP Formulation for the Unit Commitment Problem (2018, background): “[22] and [24] provide examples on how to formulate these requirements.”
A Centralized Energy Management System for Isolated Microgrids (2014, methodology): “Minimum-up and minimum-down time limits are also considered in this model, and are modeled as follows [21]:”
Forecasting Next-Day Electricity Prices by Time Series Models (2002, background): “If a producer has a good forecast of next-day market-clearing prices it can develop a strategy to maximize its own benefit [2] and establish a pool bidding technique to achieve its maximum benefit.”
Offering Strategy Via Robust Optimization (2011, methodology): “The following set of linear constraints are used to describe the feasible operating region [ 34 ]:”
Tight Mixed Integer Linear Programming Formulations for the Unit Commitment Problem (2012, background): “The UC problem can easily be extended to generate production schedules in a competitive market environment [3], [7], [8].”
Cycling of conventional power plants: technical limits and actual costs (2015, background): “Hereunder, the basic equations of the unit commitment model are listed [31]-[32].”
Fuzzy Adaptive Particle Swarm Optimization for Bidding Strategy in Uniform Price Spot Market (2007, background): “• Inter-temporal operating constraints [19] such as minimum up and down times have been incorporated.”
Analyzing valid inequalities of the generation unit commitment problem (2009, methodology): “(33b.1) There are other ways of modeling the minimum up and down time constraints, see [19] and [20]; these methods use big M values, i.e. they use a large multiplier.”