Special Protection Schemes (SPSs), are corrective action schemes that are designed to protect power
systems against severe contingency conditions. In planning of SPSs, protecting transmission network from
overloading issue due to critical situations has become a serious challenge which needs to be taken into
account. In this paper, a Special Protection and Control Scheme (SPCS) based on Differential Evolution
(DE) algorithm for optimal generation rescheduling has been applied to mitigate the transmission line
overloading in system contingency conditions. The N-1 contingency has been performed for different
single line outages under base and increased load in which generation rescheduling strategy has been
undertaken to overcome the overloading problem. Simulation results are presented for both pre-and
post system emergency situations. The IEEE 30-bus test system was utilised in order to validate the
effectiveness of the proposed method.
An electric power system generate electricity to meet demands. Distributed Generation (DG) allows
electricity to be generated in a small capacity where the customer is located. In this paper, multi-objective
functions based on the indices of system performance are formulated and used to determine the best
location. The Differential Evolution technique (DE) has been employed to calculate optimal sizing for
each location. Unity power factor DG model have been studied in this work and the problems solved
with one DG unit. IEEE 14 bus has been used as a test system.
Phasor Measurement Units (PMUs) are an important component in Wide Area Protection (WAP)- based
operations in power systems. It is needed that a certain placement scheme of PMUs is suggested if
power system scale gets larger. The optimal placement of PMU in power systems has been considered
and formulated in order to reduce the number of installed PMUs while accomplishing a desired level of
reliability of observation. Optimal PMU Placement (OPP) problem as the combinatorial optimization
problem has been formulated to determine the minimum PMU location in the power system. In this paper,
Disparity Evolution-type Genetic Algorithm (DEGA) based on disparity theory of evolution is applied.
Genetic Algorithm (GA) is employed for the purpose of comparison with DEGA. The optimization
model is solved for IEEE 118 standard bus system. DEGA can find better placement suggestion compared
with GA because of the nature of evolution that models the double spiral structure of DNA to hold the
diversity of population.