JOURNAL OF IRANIAN ASSOCIATION OF ELECTRICAL AND ELECTRONICS ENGINEERS
Year:2018 | Volume:15 | Issue:1 |Papers Count:11

In this paper, a new multi-objective model for the expansion planning of the renewable distributed generation (DG) in smart distribution networks based on the passive defense considerations is proposed. The proposed planning model aims to minimize the outage duration of the distribution network loads considering priority of critical, sensitive and important loads. It also aims to minimize network costs and active power losses, at the same time. The optimum solution of the proposed model consists of DG unit’s size, location, and best year for installation. Uncertainties of load and output power of renewable DG units are handled by chance-constrained programming approach. Multi-objective particle swam optimization algorithm is used as an optimization tool to solve the proposed optimization model. The effectiveness of the proposed expansion model is demonstrated through examination on a 38-bus radial distribution network.

In conventional power systems, frequency and voltage deviations are chosen as indexes for characterizing conventional power system security. While in an autonomous micro grid with Electronically Interfaced Distributed Generation (EIDG), frequency and voltage deviations against power and loads disturbances perfectly controlled by f-P and V-Q controller. Unlike conventional power systems, frequency and voltage deviations are not important issues to characterize autonomous micro grid security with Electronically Interfaced Distributed Generation (EI-DG). But in a balanced autonomous micro grid Generation and Consumption power chosen as indexes for characterizing microgrid security against power and loads disturbances. Hence, micro grid is considered insecure if Generation and Consumption power balance is not established. Therefore, load shedding and generation tuning are required as prompt preventive measures. This paper suggests a new strategy to assist the micro grid against power and loads disturbance, while using Adaptive Network Based Fuzzy Inference System (ANFIS) as a methodology for this investigation. In case of, Micro grid insecure identification, predictions prevent control strategy is suggested by another Adaptive Network Based Fuzzy Inference System (ANFIS).

In this paper, the short term optimal economic planning for a microgrid is implemented at two levels with different horizons. The purpose of 24-hour scheduling is to determine the generation of micro-turbines, the contribution of responsive loads, the status of charging and discharging energy storage resources, the exchange rate with the upstream network, the prediction of renewable resources generation, optimum cost for the system operator and the amount of pollutant emissions will be minimized. Planning in the second layer runs for 15 minutes ahead. At this stage, the goal is to reduce the forecast error and minimize the cost of first layer operation. The proposed Method is implemented and tested using MATLAB programming. The proper performance of this method is reduce operation costs and maximize responsive loads profit.

Growth of wind distributed generation (DG) in the active distribution grids can impact on the operation and planning aspects of network. Therefore, this paper presents a probabilistic load flow problem to evaluate the impacts of wind unit uncertainties on the distribution systems.Proposed method is based on the cumulants technique that is a straightforward approach. This analytical method can assess the bus voltages of system in a probabilistic manner. Using correlated cumulants, a suitable methodology is presented to consider the correlation between wind generations. Furthermore, Weibull distribution is considered for modelling wind speed. Thereby, wind power curve is obtained. The proposed method is applied to the IEEE standard 33 bus test system, and the results are discussed.

Voltage and reactive power control have been widely employed to reduce power losses and satisfy the main distribution system operational constraints.In recent years, Distributed Generators connected to the distribution network have received increasing attention. The connection of enormous DGs into existing distribution network changes the operation of distribution systems and affect the daily Volt/Var control. Intermittent renewable resources, particularly wind and solar, or random changes in load level can cause significant fluctuations in distribution feeder voltages.This article presents a two-step control approach for finding the optimization feeder control settings and maintaining the feeder voltages and THD within specified levels by P-PSO optimization method. The load-tap changer transformers, voltage regulator and capacitor banks is controlled based on load and PV (with smart inverters) output 24 hours forecasting base on, while In order to reduce voltage fluctuations very short term output of PVs and load forecasting deal with the fast changing transients by output reactive power control.Evaluation studies are performed based on the harmonic IEEE 123 node radial test feeder under varying load and generation conditions. The results demonstrate that the proposed approach is promising for voltage and VAR control of distribution feeders with intermittent resources.

The load unbalance is one of inherent features of distribution systems which draws a negative sequence current from islanded synchronous generators.This leads to overheating of the stator and, in particular, the rotor core. In such a case, it is not possible to operate the generator at its associated rated power. Thus, implementing an inverter-based resource in parallel with the synchronous generator is the main strategy proposed in this paper to tackle such a problem. To do so, the negative sequence of the reactive power is measured, and the output voltage of the inverter is regulated using a resonance controller in the abg reference frame such that its injected negative sequence current makes the generator voltage balance, as much as possible. Investigations performed in this paper show that based on the proposed method, the inverter can rapidly and effectively compensate the load unbalance in the distribution system. Accordingly, the generator current is also balanced, and thus, there is no need to limit the synchronous generator output power. Moreover, it is not necessary to overdesign the synchronous generator for unbalanced load conditions. As a result, the islanded mode synchronous generator can also be operated in a distribution system with unbalance loads without considerable derating.

The solar photovoltaic (PV) farm delivers its harvested DC energy to the AC grid via power electronic interfaces. With insolation as well as ambient temperature variations, these power electronic converters should regulate operating point at optimal point to extracting maximum power from PV cells. In this paper, a direct nonlinear control method is developed for cascaded H-bridge multilevel inverter with a LCL output filter. Multilevel inverters produce less harmonic voltages, so the size of output filter can be reduced. Moreover, operating in higher voltage levels gives the opportunity of omitting the step-up transformer in the grid with medium voltage. In the proposed control method, DC terminals of cascaded multilevel inverter can be controlled, independently. So, solar farm can be divided into distinct zones and maximum power can be harvested due to independent control of these zones. Using the proposed nonlinear controller, the DC-DC converters, usually used for maximum power point tracking, can be omitted. Moreover, exchanging the reactive power with the grid can be controlled at PCC.

Parallel, standby and series configurations are different types of power switch configuration that can be considered in semiconductor switches to improve the reliability of power electronic converters and theirs lifetime, especially in specific application such as high power industrial applications, satellites, power electronic interface for renewable energies and etc. In this paper, the reliability models of series traditional configuration and the new type are developed based on the Markov process. The mean time to failure (MTTF) of series and new configuration are derived. The reliability and MTTF of triple and new configuration are compared together. In some cases, some redundancy configurations have the same MTTF in a boundary condition. The analytical result illustrated that the new configuration is a suitable alternative instead of the standby configuration. The result showed the series and parallel configuration are suitable for high voltage and high current applications.

In this paper, an optimized double-fed induction generator in wind power plants has been studied. The equations of optimal design is extracted and for evaluation of generator performance, a model has been presented and based on this model, the generator is optimized using finite element analysis (FEA). The aims of the optimizations are improvement of voltage and current waveform to could reach a better output power. Also, in mechanical point of view, dimension of machine including axial length, number of slots per phase per pole, etc is optimized and minimum weight of machine obtained. The results show that, with a proper optimization, Total costs of the generators like materials costs are significantly reduced. Finally, the FEA results compared with analytical methods and it is observed that the FEA is a powerful tool to optimize the induction generators. The study also shows that optimization of the generator performance can help to improve the performance of the wind farm.

Permanent magnet synchronous motors (PMSMs) are used in many applications including the control systems due to their high efficiency, high power density, good dynamic behavior, high precision and excellent controllability. One of the PMSM problems is the cogging torque which is made by interaction between PMs and stator teeth. This leads to some noise and vibration of the motor that in control applications leads to fluctuation of the motor from its trajectory when tracking the target point. Hence, the motor should be designed in such a way to have very low cogging torque. In this research to reach this purpose, at first a suitable combination of slot/pole has been selected for the motor. Then, the optimum shape of the magnet has been obtained by using 2D finite element method. For the magnet shape, two important parameters of the magnet are optimized simultaneously. The designed motor has been fabricated and tested. The experimental results validate the simulation results and show that by the presented design the motor has very low cogging torque.

In this paper, the optimal design of a non-slotted AF (Axial Flux) motor is presented using sizing equations, IPSO (Improve Particle Swarm Optimization) algorithm and Finite Element software. IPSO optimization method reduces the evaluation time of the motor design, because of parallel evaluation. This reduction of time is relevant to number of the CPUs. The optimization objective is to achieve an almost sinusoidal Back EMF (Electromotive force), minimizing magnet weight and maximizing efficiency. In order to precise calculation of the magnet thickness, a new equation is presented. In the first step the design optimization parameters such as number of pole, the air gap, and electrical loading is specified by IPSO to satisfy design objectives. The motor designed by sizing equations and IPSO, is evaluated with the help of Finite Element method to verify the accuracy of the obtained results.