One of the concerns in power system preventive control and security assessment is to find the point where the voltage and frequency collapse and when the system forces a severe disturbance. Identifying the weakest bus in a power system is an essential aspect of planning, optimising and post-event analysing procedures. This paper proposes an approach to identify the weakest bus from the frequency security viewpoint. The transient frequency deviation index for the individual buses is used as the weakest bus identification as well as a frequency security indicator. This approach will help to determine the bus with the worst deviation, which helps to analyse the system disturbance, takes proper control action to prevent frequency failure, and most importantly, observes consumer frequency. The approach is applied to the WSCC 9 bus test system to show the feasibility of the method.
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.