International Journal of Smart Electrical Engineering
Volume:7 Issue: 3, Summer 2018

This paper addresses the design procedure of a fuzzy logic-based adaptive approach for DFIGs to enhance automatic generation control (AGC) capabilities and provide better dynamic responses in multi-area power systems. In doing so, a proportional-integral (PI) controller is employed in DFIG structure to control the governor speed of wind turbine. At the first stage, the adjustable parameters of the PI controller are optimized in an offline manner via the genetic algorithm (GA). In the second stage, the outlined fuzzy logic-based adaptive approach is intended for valid adjustment the gains values of PI controller through suitable membership functions in an online manner. To verify the high performance of the designed fuzzy PI controller, a hybrid interconnected two-area power system is considered, taking into account the physical limitations of generation rate constraint non-linearity and governor dead-band effect. Eventually, two scenarios including step and random load changes are selected to establish the success of the proposed fuzzy PI controller in damping of the area frequency and tie-line power oscillations. Simulation results are presented and compared with GA-based PI controller.

During extremely hot summer days, air conditioning systems are known as major electricity consumers in residential, commercial and industrial sectors. Moreover, high energy requirement of multiple-chiller plants may cause an interconnected power grid be faced with annual on-peak electrical demand, load-generation mismatch, voltage collapse and catastrophic wide area blackout. Therefore, this paper presents a day-ahead economic dispatch model for water cooled multiple chiller systems aiming to minimize total power consumption of cooling towers, pumps and chillers. In addition, refrigeration capacity limit of each chiller and cooling load-generation balance criterion are considered as optimization constraints. On/off status and partial load ratio of each chiller, power consumption of pump/cooling tower/chiller, temperature of chiller outlet water, temperature of cooling tower outlet water, mass flow rate of cooled water, mass flow rate of water flowing in and out of cooling tower are considered as decision variables. Simulations are conducted on a benchmark system with two 550 refrigeration ton (RT) units, four 1000 RT chillers and different cooling load levels over a 24-hour time horizon using generalized algebraic mathematical modeling system (GAMS) software.

Partial Discharge (PD) is the most important source of insulation degradation in power transformers. In order to prevent catastrophic failures in transformers, PDs need to be located as soon as possible so that maintenance measures can be taken in time. Due to the structural complexity of windings, locating the PD source inside a transformer winding is not a simple task. In this paper, the efficacy of the proposed Frequency Response Assurance Criterion (FRAC) correlation technique for finding the location of a PD source in a transformer winding is evaluated and compared with two well-known correlation techniques in this regard, that are Time domain correlation and Kullback- Leibler divergence. The responses of the winding to PD pulses, generated by Heidler function, of known pulse duration applied in parallel along the whole sections of the winding are considered as the reference data. In addition, the captured responses of the winding generated by injecting the PD pulses of arbitrary shapes and magnitude along the various sections of the winding are taken as the test data. Subsequently, the location of the PD source is determined by finding the maximum FRAC value between the reference signals and the test signal. First, a simulation case-study is carried out to show how the proposed method can be applied to locate a PD source. Subsequently, the results of the proposed method are compared with the time-domain and Kullback–Leibler divergence correlation techniques. Finally, the proposed method is validated with the experimental results. The simulation and experimental results demonstrate that the proposed method is more effective in precisely determining the location of a PD source even in a very noisy condition.

Subscriber service is not feasible in the construction of large-scale traditional networks with the aim of providing more services. The high distance between production and consumption requires the definition of a transmission network as a challenging intermediary. The cost of transmission network and the risk associated with it cannot be ignored at all. The idea of a microgrid, which began with the local feeding of loads, can improve the reliability of the previous power system and, in addition, deliver the power to customers with more quality. Microgrids are the key to achieve low carbon networks by collecting distributed generation (DG) resources. Power management in the form of a microgrid causes other sensitivities. The need for storage systems besides the power intermittency of DGs, unintended islanding, and the protection of microgrids, especially in the island state, are the main issues discussed in this paper in a coherent format. This research work is a detailed reference for microgrids mainly in protection issues related to the islanded ones.

Smart grid enhances optimization in generation, distribution and consumption of the electricity by integrating information and communication technologies into the grid. Today, utilities are moving towards smart grid applications, most common one being deployment of smart meters in advanced metering infrastructure, and the first technical challenge they face is the huge volume of data generated from variety of smart devices including the meters. This data is beneficial for both customers and utilities, but only if the capability of using it and extracting knowledge and hidden patterns from data is exploited. In this article, a brief overview of data sources along with applications of big data analytics in power distribution networks and related analytical data models are presented. At the end, big data management tools and techniques applicable in power distribution networks are introduced.

Reactive power as a utility of ancillary service in restructured environment is supplied by Independent System Operator (ISO). Due to the particular importance of optimal pricing strategy in the power market, the study aims to investigate this problem more closely. To this end, first the problems of restructuring, reactive power generation and its associated costs thereof were reviewed and different types of transmission rights identified. Next, an algorithm was proposed as the selected method for reactive power pricing in terms of Fina g simultaneous Opportunity Cost (OC) at power plants. The pricing method was based on the respective marginal costs as ncial Transmission Rights (FTR) of transmission lines in the presence of the hybrid market model (spot and bilateral) usin well as the optimal power flow and implemented the succession planning method via MATLAB for IEEE 57-buses test system. Comparison of the results obtained from the proposed method (where in capacitors and Static VAR Compensator (SVC) were considered as reactive power generation sources) with those of the current pricing method used in the Iran power grid showed increased earnings due to reactive power investment.