Research on Applied Technology with a Continues Method for Unit Commitment Problem

2014 ◽  
Vol 952 ◽  
pp. 319-322
Author(s):  
Lin Feng Yang ◽  
Jie Li ◽  
Zhi Hui Ge
Keyword(s):  
Interior Point ◽  
Interior Point Method ◽  
Unit Commitment ◽  
Mixed Integer ◽  
Unit Commitment Problem ◽  
Integer Quadratic Programming ◽  
Applied Technology ◽  
Commitment Problem ◽  
Mixed Integer Quadratic Programming ◽  
Integer Constraints

A continue method based on relaxation is applied to solve the unit commitment problem (UCP). At first, the primal UCP is reformulated as a simple mixed integer quadratic programming (MIQP), and then the MIQP is solved by interior point method (IPM) and commercial software CPLEX. The first continues problem, UCP without integer constraints, can be solved by IPM to get the no integer solution. The second continues problem, an equivalent continues problem of UCP, can be solved starting from the solution obtained in first problem.

scholarly journals Evaluati on of long-term start up costs impact on short-term price based operational optimization of a CCGT using MILP

2019 ◽  
Vol 137 ◽  
pp. 01012
Author(s):  
Sylwia Gotzman ◽  
Paweł Ziόłkowski ◽  
Janusz Badur
Keyword(s):  
Power Plants ◽  
Unit Commitment ◽  
Real Life ◽  
Mixed Integer ◽  
Unit Commitment Problem ◽  
Operational Optimization ◽  
Start Up ◽  
Commitment Problem ◽  
Electricity Spot Market

An increasing share of the weather-dependent RES generation in the power system leads to the growing importance of flexibility of conventional power plants. They were usually designed for base load operation and it is a challenge to determine the actual long-term cycling costs, which account for an increase in maintenance and overhaul expenditures, increased forced outage rates and shortened life expectancy of the plant and components. In this paper, the overall impact of start up costs is evaluated by formulating and solving price based unit commitment problem (PBUC). The electricity spot market is considered as a measure for remunerating flexibility. This approach is applied to a real-life case study based on the 70 MWe PGE Gorzόw CCGT power plant. Different operation modes are calculated and results are used to derive a mixed integer linear programming (MILP) model to optimize the operation of the plant. The developed mathematical model is implemented in Python within the frame of the PuLP library and solved using GUROBI. Results of the application of the method to a numerical example are presented.

scholarly journals Stochastic Unit Commitment Problem, Incorporating Wind Power and an Energy Storage System

2020 ◽  
Vol 12 (23) ◽  
pp. 10100
Author(s):  
Khalid Alqunun ◽  
Tawfik Guesmi ◽  
Abdullah F. Albaker ◽  
Mansoor T. Alturki
Keyword(s):  
Energy Storage ◽  
Wind Power ◽  
Unit Commitment ◽  
Mixed Integer ◽  
Master Problem ◽  
Thermal Unit ◽  
Unit Commitment Problem ◽  
Battery Energy Storage ◽  
Commitment Problem ◽  
Battery Energy

This paper presents a modified formulation for the wind-battery-thermal unit commitment problem that combines battery energy storage systems with thermal units to compensate for the power dispatch gap caused by the intermittency of wind power generation. The uncertainty of wind power is described by a chance constraint to escape the probabilistic infeasibility generated by classical approximations of wind power. Furthermore, a mixed-integer linear programming algorithm was applied to solve the unit commitment problem. The uncertainty of wind power was classified as a sub-problem and separately computed from the master problem of the mixed-integer linear programming. The master problem tracked and minimized the overall operation cost of the entire model. To ensure a feasible and efficient solution, the formulation of the wind-battery-thermal unit commitment problem was designed to gather all system operating constraints. The solution to the optimization problem was procured on a personal computer using a general algebraic modeling system. To assess the performance of the proposed model, a simulation study based on the ten-unit power system test was applied. The effects of battery energy storage and wind power were deeply explored and investigated throughout various case studies.

An MILP Formulation for the Thermal Unit Commitment Problem Considering Start-Up and Shut-Down Power Trajectories

2014 ◽  
Vol 672-674 ◽  
pp. 493-498 ◽  
Author(s):  
Jun Deng ◽  
Hua Wei
Keyword(s):  
Unit Commitment ◽  
Mixed Integer ◽  
Test Case ◽  
Thermal Unit ◽  
Unit Commitment Problem ◽  
Binary Variables ◽  
Computational Performance ◽  
Start Up ◽  
Commitment Problem ◽  
Mixed Integer Linear Formulation

This paper presents a mixed-integer linear formulation for the thermal unit commitment problem considering the start-up and shut-down power trajectories. A realistic and accurate modeling of the unit’s operating phase is given, which includes the phases of start-up, dispatchable and shut-down. The start-up type is decided by the unit’s prior off-line time. The start-up costs and power trajectories depend on the type of start-up. A new set of binary variables is introduced to represent the dispatchable status, which can decrease the binary variables and constraints significantly. Finally, a test case study is analyzed to verify the correctness and show the computational performance of the proposed formulation.

scholarly journals Unit commitment based reliability analysis with contingency constraint

2019 ◽  
Vol 16 (1) ◽  
pp. 74
Author(s):  
Raheema Syed ◽  
P. Srinivasa Varma ◽  
R. B. R Prakash ◽  
Ch. Rami Reddy
Keyword(s):  
Power Plants ◽  
Benders Decomposition ◽  
Unit Commitment ◽  
Reliability Assessment ◽  
Branch And Cut ◽  
Mixed Integer ◽  
Unit Commitment Problem ◽  
Commitment Problem ◽  
Model Reliability ◽  
The Cost

<span lang="EN-IN">Unit commitment state’s the strategic choice to be prepared in order to define which of the accessible power plants should be taken into account to supply power. It permits utilities to reduce generation price of power. In this paper, the unit commitment problem is elucidated by taking N-1-1 contingency as a foremost constraint. The standard N-1-1 contingency takes the loss of sequential two components in the network having intervening interval for network modifications in the middle of two losses. The crucial objective to carry out contingency constrictions is to make certain that the operations of power system are adequately strong to unexpected losses of the components of the network. The optimal scheduling/allocation of the generating units is resolved by taking into account the N-1-1 criterion of contingency. By considering the N-1-1 criterion of contingency, the problem results to give an optimised model which is a linear model of mixed integer form. The linear program of mixed integer is a technique of an operational assessment in which restriction is imposed on few variables to be integers. Primarily benders decomposition was considered but for the improvement of results, the algorithm of branch and cut is presented. IEEE 30 bus system is taken into consideration and widespread analysis is accomplished to associate performance of the system under N-1-1 criterion contingency. The computational outcomes determine the value for taking into concern the intervening interval for the adjustments of the system with respect to the cost and robustness of the system. Later to the above model reliability assessment is proposed to calculate the Loss Of Load Expected (LOLE). This model is solved using MATLAB/MATPOWER software.</span>

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