This paper presents the optimization of fuel cost, emission of NO_X, CO_X, and SO_X gases caused by the generators in a thermal power plant using penalty factor approach. Practical constraints such as generator limits and power balance were considered. Two contemporary metaheuristic techniques, particle swarm optimization (PSO) and genetic algorithm (GA), have were simultaneously implemented for combined economic emission dispatch (CEED) of an independent power plant (IPP) situated in Pakistan for different load demands. The results are of great significance as the real data of an IPP is used and imply that the performance of PSO is better than that of GA in case of CEED for finding the optimal solution concerning fuel cost, emission, convergence characteristics, and computational time. The novelty of this work is the parallel implementation of PSO and GA techniques in MATLAB environment employed for the same systems. They were then compared in terms of convergence characteristics using 3D plots corresponding to fuel cost and gas emissions. These results are further validated by comparing the performance of both algorithms for CEED on IEEE 30 bus test bed.

Traction applications, such as electric and hybrid vehicles, require the electrical motor to be operated at low load conditions during most of their driving cycle. Permanent magnet (PM) motors in this case may not be an optimal choice due to their poor efficiency under low load conditions despite the fact that they exhibit the best output characteristics at the rated load. However, the wound rotor synchronous motor (WRSM) demonstrates the best efficiency at low load conditions due to their controllable excitation. This paper presents an interesting comparison of WRSM and the PM motor in terms of their efficiency over the entire drive cycle of traction applications, which demonstrates that WRSMs are more suitable compared to the apparently best performance PM motor. A WRSM with similar dimensions to the 2010 Toyota Prius interior permanent synchronous motor (IPMSM) was designed and optimized in this regard. The performance comparison of the PM motor and the WRSM was presented using 2-D finite element analysis (FEA) for the WRSM and the performance analysis report of the Toyota Prius IPMSM published by the US department of energies. The FEA analysis shows that the WRSM can achieve wide torque speed characteristics. Moreover, the WRSM exhibits better efficiency under low load conditions at the higher speed or field weakening region.

This paper presents an optimal design of a recently introduced brushless wound-rotor synchronous machine (BL-WRSM). The BL-WRSM, with a special stator winding arrangement, utilizes a single three-phase inverter for generating an additional spatial subharmonic component in the stator magnetomotive force (MMF). This subharmonic component of the stator MMF is used for the brushless excitation of the rotor. The pole span and pole shoe height were the optimized parameters, with the goals of improving the quality of output power and reducing torque ripple. Moreover, the average torque of the machine was improved by optimizing the harmonic winding placed on the rotor. The optimized BL-WRSM was further analyzed for the flux weakening operation. Finite element analysis (FEA) was carried out to analyze the performance of the BL-WRSM. Finally, the performance of the optimal BL-WRSM model was verified through an experimental test, which demonstrated good agreement with the simulation results.

Energy is very important in daily life. The smart power system provides an energy management system using various techniques. Among other load types, campus microgrids are very important, and they consume large amounts of energy. Energy management systems in campus prosumer microgrids have been addressed in different works. A comprehensive study of previous works has not reviewed the architecture, tools, and energy storage systems of campus microgrids. In this paper, a survey of campus prosumer microgrids is presented considering their energy management schemes, optimization techniques, architectures, storage types, and design tools. The survey is comprised of one decade of past works for a true analysis. In the optimization techniques, deterministic and metaheuristic methods are reviewed considering their pros and cons. Smart grids are being installed in different campuses all over the world, and these are considered the best alternatives to conventional power systems. However, efficient energy management techniques and tools are required to make these grids more economical and stable.

This paper presents a novel consequent-pole hybrid brushless wound-rotor synchronous machine (CPH-BL-WRSM). The proposed machine employs permanent magnets (PMs) on the alternate poles of the salient pole rotor, which has considerably less magnet usage compared to the regular (PM) assisted synchronous machine. The proposed CPH-BL-WRSM offered the advantages of high starting torque, high torque density, and better performance under full-load conditions. The BL operation for the proposed machine is achieved by generating a composite magneto motive force (MMF) with a fundamental component and sub-harmonic component. The sub-harmonic component of the stator MMF is used for BL excitation of the rotor. The finite-element method was used to analyze the performance of the CPH-BL-WRSM in comparison with the performance of the existing BL-WRSM and regular PM-assisted BL-WRSM. Finally, a prototype of the CPH-BL-WRSM was manufactured and the experiment was conducted to demonstrate the performance of the proposed CPH-BL-WRSM.