Comparative Analysis between Conventional PI, Fuzzy Logic and Artificial Neural Network Based Speed Controllers of Induction Motor with Considering Core Loss and Stray Load Loss

Most of the controllers of IM （induction motor） for industrial applications have been designed based on PI controller without consideration of CL （core loss） and SLL （stray load loss）. To get the precise performances of torque as well as rotor speed and flux, the above mentioned losses should be considered. Conventional PI controller has overshoot effect at the transient period of the speed response curve. On the other hand, fuzzy logic and ANN （artificial neural network） based controllers can minimize the overshoot effect at the transient period because they have the abilities to deal with the nonlinear systems. In this paper, a comparative analysis is done between PI, fuzzy logic and ANN based speed controllers to find the suitable control strategy for IM with consideration of CL and SLL. The simulation analysis is done by using Matlab/Simulink software. The simulation results show that the fuzzy logic based speed controller gives better responses than ANN and conventional PI based speed controllers in terms of rotor speed, electromagnetic torque and rotor flux of IM.

Research on large-scale cascading failure of power systems using synergistic effect

This paper discusses the primary causes from the point of synergistic effects to improve power system vulnerability in the power system planning and safety operation. Based on the vulnerability conception in the complex network theory the vulnerability of the power system can be evaluated by the minimum load loss rate when considering power supply ability.Consequently according to the synergistic effect theory the critical line of the power system is defined by its influence on failure set vulnerability in N-k contingencies.The cascading failure modes are proposed based on the criterion whether the acceptable load curtailment level is below a preset value.Significant conclusions are revealed by results of IEEE 39 case analysis weak points of power networks and heavy load condition are the main causes of large-scale cascading failures damaging synergistic effects can result in partial failure developed into large-scale cascading failures vulnerable lines of power systems can directly lead the partial failure to deteriorate into a large blackout while less vulnerable lines can cause a large-scale cascading failure.

On reliability optimization for power generation systems

The reliability level of a power generation system is an important problem which is concerned by both electricity producers and electricity consumers. Why？ It is known that the high reliability level may result in additional utility cost, and the low reliability level may result in additional consumer＇s cost, so the optimum reliability level should be determined such that the total cost can reach its minimum. Four optimization models for power generation system reliability are constructed, and the proven efficient solutions for these models are also given.

Analytical Modeling of Disaster-induced Load Loss for Preventive Allocation of Mobile Power Sources in Urban Power Networks

Continuous power supply of urban power networks(UPNs)is quite essential for the public security of a city because the UPN acts as the basis for other infrastructure networks.In recent years,UPN is threatened by extreme weather events.An accurate modeling of load loss risk under extreme weather is quite essential for the preventive action of UPN.Con-sidering the forecast intensity of a typhoon disaster,this paper proposes analytical modeling of disaster-induced load loss for preventive allocation of mobile power sources(MPSs)in UPNs.First,based on the topological structure and fragility model of overhead lines and substations,we establish an analytical load loss model of multi-voltage-level UPN to quantify the spatial dis-tribution of disaster-induced load loss at the substation level.Second,according to the projected load loss distribution,a preventive allocation method of MPS is proposed,which makes the best use of MPS and dispatches the limited power supply to most vulnerable areas in the UPN.Finally,the proposed meth-od is validated by the case study of a practical UPN in China.

Cumulative Capacity Credit Estimation for Renewable Energy Projects

This paper presents a novel method for accurately estimating the cumulative capacity credit(CCC)of renewable energy(RE)projects.Leveraging data from the main interconnected system(MIS)of Oman for 2028,where a substantial increase in RE generation is anticipated,the method is introduced alongside the traditional effective load carrying capability(ELCC)method.To ensure its robustness,we compare CCC results with ELCC calculations using two distinct standards of reliability criteria:loss of load hours(LOLH)at 24 hour/year and 2.4 hour/year.The method consistently gives accurate results,emphasizing its exceptional accuracy,efficiency,and simplicity.A notable feature of the method is its independence from loss of load probability(LOLP)calculations and the iterative procedures associated with analytic-based reliability methods.Instead,it relies solely on readily available data such as annual hourly load profiles and hourly generation data from integrated RE plants.This innovation is of particular significance to prospective independent power producers(IPPs)in the RE sector,offering them a valuable tool for estimating capacity credits without the need for sensitive generating unit forced outage rate data,often restricted by privacy concerns.