Comparison of Practical Unit Commitment Problem Solutions
Titel:
Comparison of Practical Unit Commitment Problem Solutions
Auteur:
Raglend, I. Jacob Padhy, Narayana Prasad
Verschenen in:
Electric power components & systems
Paginering:
Jaargang 36 (2008) nr. 8 pagina's 844-863
Jaar:
2008-08
Inhoud:
In this article, a comparative study has been done for the unit commitment problem (UCP) with operational, power flow, and environmental constraints along with contingencies to plan a secure and economical hourly generation schedule based on the solutions obtained. The UCP solutions obtained without considering power-flow constraints are not practical due to secure operation of the power network. The UCP with power-flow constraints obtains the minimum system-operating cost, satisfying both unit and network constraints using hybrid Lagrangian multiplier and Newton-Raphson power-flow algorithms. Considering various environmental aspects, there is a need to include environment constraints to get a realistic unit commitment (UC) schedule. The UC solution for the environmentally constrained problem has been formulated as a multi-objective problem by considering both economic load dispatch and economic emission dispatch simultaneously. The combined economic emission dispatch bi-objective problem is converted to a single objective function by adding a modified price penalty factor. The UC schedule must withstand, even if there are any contingencies that have occurred in any line of the network, which can be incorporated by performing contingency analysis by removing one line from the system and performing optimal power flow (OPF) until all of the lines are removed once for each possible state. The state that converges for OPF for every line removal is selected, and OPF is performed again without any contingencies. In this article, the UC solutions obtained with operational, power flow, and environmental constraints, along with contingencies in the network, are compared for the IEEE 30-bus and the Indian utility practical systems scheduled for 24 hr. The algorithm and simulation are carried through a Matlab environment, and the results obtained are quite encouraging.
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