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With increasing demand in energy, efficiency, reliability, and resiliency in the power systems, integration of distributed generation (DG) or renewable energy sources in the local distribution system is trending nowadays. The power system optimization in distribution networks plays a prominent role in planning reliable supply to the users. This paper presents a meta-heuristic approach to improve the system performance by considering: a) voltage profile improvement, b) minimize the active power loss, and c) overall operation cost as the objective functions of the distribution system reconfiguration (DSR). Modified Newton Raphson (MNR) is used for a load flow analysis of the 33 bus balanced test system and 25 bus unbalanced distribution system. To study the performance of the system objective functions, three different scenarios are considered: i) with DG integrated, ii) with DSR performed, and iii) DG placed along with DSR. These scenarios are compared with the base system configuration parameters along with convergence comparison of harmony search algorithm (HAS) and particle swarm optimization (PSO) with firefly algorithm (FFA) of the distribution systems. [ABSTRACT FROM AUTHOR]

In this paper, the performance and reliability of the hybrid microgrid system is analyzed with the two different configurations where multiple distributed energy sources supplied the power to the loads through centralized inverter and parallel inverter. The power quality, power sharing, power exchange and voltage and frequency drop parameters are evaluated by applying 1.1 kVA load on the centralized and parallel inverter hybrid systems with LL and LLG faults. The hysteresis current controller in the centralized inverter hybrid system is assuring the accurate power exchange between the grid and hybrid system during abnormal conditions. The droop controller in parallel inverter hybrid system is effectively sharing the load among the inverters during normal and abnormal conditions. The comparative analysis of these energy systems is made based on control aspects, power quality, reliability and economics. [ABSTRACT FROM AUTHOR]

Research on Self –excited induction generator (SEIG) brings a lot of attentions in the last three decades as a promising solution in distributed generation systems with low cost investment. There are two important fixations to attend in the operation of SEIG based systems, a) excitation and b) voltage regulation. Many procedures are reported regarding selection of excitation capacitance in the literature, based on state-state analysis, dynamic modeling, empirical formulas and machine parameters which involve various levels of complexity in findings. Moreover, the voltage regulation is the main challenge in implementation of SEIG based isolated systems. To address this problem, many power electronic-based schemes are proposed in the literature and but these solutions have few demerits importantly that additional cost of equipment and troubles due to failure of protection schemes. In particular, the installation of SEIG takes place at small scale in kW range in remote/rural communities which should not face such shortcomings. Further in case of off-grid systems, the maximum loading is fixed based on connected rating of the generator. This paper presents the various methods to find excitation capacitance and illustrates an experimental investigation on different possible reactive power compensation methods of delta connected SEIG and aimed to identify a simple method for terminal voltage control without power electronics. In this experimental work, the prime-mover of the generator is a constant speed turbine, which is the emulation of a micro/pico hydro turbine. From the results, it is found that a simple delta connected excitation and delta configured reactive power compensation limits voltage regulation within ±6% while maintaining the frequency of ±1%, which make feasible of the operation successfully in remote electrification systems. [ABSTRACT FROM AUTHOR]

This paper presents stability enhancement of a test system that is connected with a Wind Farm (WF) by using Power System Stabilizer (PSS) for Synchronous Generator (SG) and Power Oscillation Damper (POD) for Static Var Compensator (SVC). This paper also proposes a coordination mechanism for the controller to effectively damp out the oscillations and make the power system more stable by considering the uncertainties. The uncertainty is considered as wind speed variation and wind power penetration and different locations. The Particle Swarm Optimization (PSO) is used to overcome the controller parameter tuning drawbacks and controller coordination. The SG rotor speed deviation is selected as an objective function with various constraints for PSO. The transient stability analysis is carried out by considering large disturbance that is a three-phase fault. The nonlinear dynamic simulation results are obtained by integrating WF and SG replacement with the same rating WF. Evaluation and analysis are performed for various cases and different combination of without and with controllers. From the simulation results, it is noticed that oscillations in the system are minimized, and stability is enhanced at the maximum level. It also observed that the capability of SG and DFIG under three-phase fault is intensified by using PSO for optimized coordinated controller parameters. The robustness and effectiveness of the proposed approaches are evaluated on the IEEE-11 bus test system. [ABSTRACT FROM AUTHOR]

This paper proposes a security-constrained single and multi-objective optimization (MOO) based realistic security constrained-reactive power market clearing (SC-RPMC) mechanism in a hybrid power system by integrating the wind energy generators (WEGs) along with traditional thermal generating stations. Pre-contingency and post-contingency reactive power price clearing plans are developed. Different objective functions considered are the reactive power cost (RPC) minimization, voltage stability enhancement index (VSEI) minimization, system loss minimization (SLM), and the amount of load served maximization (LSM). These objectives of the SC-RPMC problem are solved in a single objective as well as multi-objective manner. The choice of objective functions for the MOO model depends on the load model and the operating condition of the system. For example, the SLM is an important objective function for the constant power load model, whereas the LSM is for the voltage-dependent/variable load model. The VSEI objective should be used only in near-critical loading conditions. The SLM/LSM objective is for all other operating conditions. The reason for using multiple objectives instead of a single objective and the rationale for the choice of the appropriate objectives for a given situation is explained. In this work, the teaching learning-based optimization (TLBO) algorithm is used for solving the proposed single objective-based SC-RPMC problem, and a non-dominated sorting-based TLBO technique is used for solving the multi-objective-based SC-RPMC problem. The fuzzy decision-making approach is applied for extracting the best-compromised solution. The validity and efficiency of the proposed market-clearing approach have been tested on IEEE 30 bus network. [ABSTRACT FROM AUTHOR]