Unit commitment with transmission security and voltage constraints

Abstract

In this paper, optimal power flow (with transmission security and voltage constraints) is incorporated in the unit commitment formulation. Using Benders decomposition, the formulation is decomposed into a master problem and a subproblem. The master problem solves unit commitment with prevailing constraints, except transmission security and voltage constraints, by augmented Lagrangian relaxation. The subproblem minimizes violations of transmission security and voltage constraints for a commitment schedule given in the master problem. Since transmission constraints are decoupled from voltage constraints in the subproblem, the subproblem could hrther be decomposed into two smaller subproblems. The resulting transmission subproblem minimizes transmission flow violations for the worst contingency case by adjusting unit generation and phase shifter controls. The corresponding reactive subproblem minimizes voltage constraints by reactive power generation and tap changing controls. In the case of transmission flow or voltage infeasibility, Benders cuts are produced for unit commitment rescheduling. The iterative process between the master problem and the subproblems provides a minimum production cost solution for generation scheduling while satis&ing the constraints. A comprehensive unit commitment software package is developed using Visual C*. A 36-unit system in the IEEE-118 bus network is used to demonstrate the efficiency of the method.

A spatially and temporally resolved model of the electricity grid – Economic vs environmental dispatch

“…The master problem is the traditional unit commitment problem without the transmission and voltage constraints, and the sub-problems include securitychecking routines using the results from the master problem and Benders cuts [20,21]. This method has been used to solve the UC problem with transmission constraints and voltage constraints [22], and with stochastic unit commitment to include higher penetration of wind energy resources [23].…”

Robust unit commitment problem with demand response and wind energy

“…A set of I = 36 thermal units from an IEEE 118 system (Ma and Shahidehpour (1999)) are used in all experiments and some parameters are adjusted for our models: (i) the fuel cost is linear in stead of quadratic form, and (ii) the ramping up/down parameters are adjusted according to the rule in Frangioni and Gentile (2006). The fixed price before response is 15 and the same L = 10 levels price and demand increase/decrease are pre-defined at each time (the discrete increase/decrease levels are sampled from experiment results in Faruqui and Sergici (2009)).…”

Security Constrained Unit Commitment in a Power System based on Benders Decomposition and Mixed Integer Non-linear Programming

“…Intellectual benefit on the influential UC problem by [21], mainly approaches on MINLP with non-convex representation of thermal unit operator with undefined network constraints [22][23][24][25]; As UC problem have been comprehensive classically to incorporate a DC representation both with or without (e.g., [26][27]) real power losses are considered. Although, with DC power flow constraints relatively than AC problemmightguide to inaccuracy, as a DC model ignore reactive power and voltage.…”