MIP-based stochastic security-constrained daily hydrothermal generation scheduling

This paper presents the application of a mixedinteger

programming (MIP) approach for solving stochastic

security-constrained daily hydrothermal generation scheduling

(SCDHGS). Power system uncertainties including generating units

and branch contingencies and load uncertainty are explicitly considered

in the stochastic programming of SCDHGS. The roulette

wheel mechanism and lattice Monte Carlo simulation (LMCS)

are first employed for random scenario generation wherein the

stochastic SCDHGS procedure is converted into its respective

deterministic equivalents (scenarios). Then, the generating units

are scheduled through MIP over the set of deterministic scenarios

for the purpose of minimizing the cost of supplying energy and

ancillary services over the optimization horizon (24 h) while satisfying

all the operating and network security constraints. To amore

realistic modeling of the DHGS problem, in the proposed MIP

formulation, the nonlinear valve loading effect, cost, and emission

function are modeled in linear form, and prohibited operating

zones (POZs) of thermal units are considered. Furthermore, a dynamic

ramp rate of thermal units is used, and for the hydro plants,

the multiperformance curve with spillage and time delay between

reservoirs is considered. To assess the efficiency and powerful

performance of the aforementioned method, a typical case study

based on the standard IEEE-118 bus system is investigated, and

the results are compared to each other in different test systems.