A method for determining the unit commitment schedule for hydro-thermal systems using extensions and modifications of the Branch and Bound method for Inteler Programming has been developed. Significant features of the method include its computational practicability for realistic systems and proper representation of reserves associated with different risk levels. Contracts relating to power interchange have also been adequately modelled for such an approach.

Integer Programming Approach to the Problem of Optimal Unit Commitment with Probabilistic Reserve Determination

This paper is concerned with the solution of large-scale unit commitment problems. An optimization model has been developed for these problems that incorporates minimum up and down time constraints, demand and reserve constraints, cooling-time dependent startup-costs, and time varying shutdown costs, as well as other practical considerations. A solution methodology has been developed for the optimization model that has two unique features. First, computational requirements grow only linearly with the number of units. Second, performance of the algorithm can be shown (rigorously) to actually improve as the number of units increases. With a preliminary computer implementation of the algorithm, we have been able to reliably solve problems with 250 units over 12 (2-hour) time periods, and we expect to be able to easily double these numbers.

Solution of Large-Scale Optimal Unit Commitment Problems

The thermal power plant generator maintenance scheduling problem is addressed. The problem is formulated as a mixed-integer programming problem, and it is solved by using an optimization method known as simulated annealing. Since the simulated annealing method assumes an analogy between a physical multiparticle system and a combinatorial optimization problem, a global minimum can be found with high probability through a careful annealing process. Numerical results on a real-scale test system are given, and the effectiveness of the proposed method is demonstrated. >

Maintenance scheduling by using simulated annealing method (for power plants)

This paper addresses generation maintenance scheduling in a competitive electric energy environment. In a centralized setting, the system operator derives a maintenance scheduling plan that attains the desired reliability while minimizing cost and imposes it to all producers. In a competitive environment, this is not possible because the operator is still in charge of maintaining an adequate level of reliability, but the target of each producer is to maximize its own profits, which conflicts in general with the reliability objective of the operator. This paper proposes a technically sound coordinating mechanism based on incentives/disincentives among producers and the operator, which allows producers to maximize their respective profits while the operator ensures an appropriate level of reliability.

Generation maintenance scheduling in restructured power systems

Most unit maintenance scheduling packages consider preventive maintenance schedule of generating units over a one or two year operational planning period in order to minimize the total operating cost while satisfying system energy requirements and maintenance constraints. In a global maintenance scheduling problem, the authors propose to consider transmission line maintenance scheduling and line capacity limits along with generation and line outages. The inclusion of transmission and network constraints in generating unit maintenance will increase the complexity of the problem, so they propose to decompose the global generator/transmission scheduling problem into a master problem and sub-problems using Benders decomposition. In the first stage, a master problem is solved to determine a solution for maintenance schedule decision variables. In the second stage, sub-problems are solved to minimize operating costs while satisfying the network constraints. Benders cuts based on the solution of the sub-problem are introduced to the master problem for improving the existing solution. The iterative procedure continues until an optimal or near optimal solution is found.

Integrated generation and transmission maintenance scheduling with network constraints

An experimental method of scheduling the necessary maintenance activities on generator units in a power system is developed. The problem is identified as an integer programming problem, and a method based on the branch-and-bound technique is developed. The maintenance scheduling problem is characterized by a large number of complex constraints. The method presented is capable of taking into account all these constraints and hence, results in a practically implementable solution, if a feasible solution exists. Other features of the method are employment of a number of different objective functions and discovery of a feasible solution if one exists. Furthermore, unlike most present methods, it actually finds the optimal solution. The operation of the method is exemplified by application to a realistic system.

Karol Morsztyn

Papers

An Experimental Method of Determination of Optimal Maintenance Schedules in Power Systems Using the Branch-and-Bound Technique