Abstract
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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.