Unit commitment problem in deregulated environment

► Paper presents MILP model for unit commitment problem on day-ahead market. ► Model requires a single type of binary variables used in modelling on/off decision. ► Bilateral contracts are included in this model to reduce risk of profit deviation. This paper addresses the self-scheduling problem of...

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Bibliographic Details
Published in:International journal of electrical power & energy systems Vol. 42; no. 1; pp. 150 - 157
Main Authors: Bisanovic, Smajo, Hajro, Mensur, Dlakic, Muris
Format: Journal Article
Language:English
Published: Oxford Elsevier Ltd 01.11.2012
Elsevier
Subjects:
0/1 Mixed-integer linear programming
Applied sciences
Bilateral contracts
Contracts
Costs
Day-ahead market
Deregulation
Electrical engineering. Electrical power engineering
Electrical power engineering
Exact sciences and technology
Integer programming
Linear programming
Miscellaneous
Operation. Load control. Reliability
Optimization
Power networks and lines
Thermal unit commitment
Thermoelectricity
Unit commitment
Thermal unit commitment
Day-ahead market
Bilateral contracts
0/1 Mixed-integer linear programming
Performance evaluation
Dispatching problem
Costs
Deregulation
Bilateral agreements
Power system economics
Optimization method
Power distribution planning
Modeling
Optimization
Trade
Power markets
Deterministic approach
Branch and bound method
Power system planning
Interior point method
Linear programming
Mixed integer programming
Scheduling
Forecasting management
Case study
Integer programming
Thermal power
Electrical network
Starting
Effectiveness factor
ISSN:0142-0615, 1879-3517
Online Access:Get full text
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Summary:► Paper presents MILP model for unit commitment problem on day-ahead market. ► Model requires a single type of binary variables used in modelling on/off decision. ► Bilateral contracts are included in this model to reduce risk of profit deviation. This paper addresses the self-scheduling problem of generation companies owning thermal power units considering bilateral contracts and day-ahead market. This approach allows precise modelling of variable costs, start-up costs and comprehensive system of constraints. The self-scheduling model is formulated as deterministic optimization problem in which expected profit is maximized by 0/1 mixed-integer linear programming technique. Solution is achieved using the homogeneous and self-dual interior point method for linear programming, with a branch and bound optimizer for integer programming. The effectiveness of the proposed model for optimizing the thermal generation schedule is demonstrated through the case study with detailed discussion.
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content type line 23
ISSN:0142-0615
1879-3517
DOI:10.1016/j.ijepes.2012.03.051