International Journal of Smart Electrical Engineering
Volume:2 Issue: 4, Autumn 2013

As renewable energy increasingly penetrates into power grid systems, new challenges arise for system operators to keep the systems reliable under uncertain circumstances, while ensuring high utilization of renewable energy. This paper presents unit commitment (UC) which takes into account the volatility of wind power generation. The UC problem is solved with the forecasted intermittent wind power generation and possible scenarios are simulated for representing the wind power volatility. The iterative process between the commitment problem and the economic dispatch(ED) problem will continue until we find the optimum mode of committing the units. Furthermore we have considered a hydro pump storage (HPS) unit to be a part of operating system in order to mitigating wind power forecasting errors and peak shaving. Numerical simulations indicate the effectiveness of the proposed UC for managing the security of power system operation by taking into account the intermittency and volatility of wind power generation

Nowadays the position of the renewable energy is so important because of the environment pollution and the limitation of fossil fuels in the world. Energy can be generated more and more by the renewable sources, but the fossil fuels are non-renewable. One of the most important renewable sources is the wind energy. The wind energy is an appropriate alternative source of fossil fuel. The replacement rate of renewable energy to fossil fuels is rising, although the production cost is higher than fossil fuels. To further reduce cost of wind production, many methods have been proposed. One of the suitable approaches is the maximum power point tracking strategy. In this paper, a new intelligent maximum power point tracker called Fuzzy- Cuckoo strategy for small- scale wind energy conversion systems is proposed. The maximum power point tracker proposed uses measured wind speed to detect the maximum output power and its respective optimal rotational speed. The main contribution of the proposed approach is to exactly track the maximum power point, so the output power fluctuations captured by wind turbine are less than conventional approaches. The simulations are performed in MATAL/SIMULINK software. The superiority of the proposed approach is validated in two situations, low and rapid changes in wind speed. The maximum power point of wind energy conversion systems can be tracked by the proposed approach in any situation. The higher accuracy of the Fuzzy- cuckoo strategy than the conventional trackers is another advantage of the proposed approach.

Nowadays, economic load dispatch between generation units with least cost involved is one of the most important issues in utilizing power systems. In this paper, a new method i.e. Water Cycle Algorithm (WCA) which is similar to other intelligent algorithm and is based on swarm, is employed in order to solve the economic load dispatch problem between power plants. In order to investigate the effectiveness of the proposed method in solving non-linear cost functions which is composed of the constraint for input steam valve and units with different fuels, a system with 10 units is studied for more accordance with literatures in two modes: one without considering the effect of steam valve and load of 2400, 2500, 2600 and 2700 MW and the other one with considering the effect of steam valve and load of 2700 MW. The results of the paper comparing to the results of the other valid papers show that the proposed algorithm can be used to solve in any kind of economic dispatch problems with proper results.

In recent years, based on the growing importance of clean energy in comparison with conventional energy production from fossil fuels, DG systems are gradually becoming more popular all over the world. These resources solve many problem of system. However, these resources create some other problems too. One of the most problem of DGs is unwanted islanding. This paper addresses reliable passive islanding detection algorithm based on the change of positive sequence (ROCOPS) of voltage signal analysis method. At first, all possible linear and nonlinear load switching, motor starting and capacitor bank switching is simulated. The ROCOPS signal of these conditions is measured for all conditions. From of these data, the reliable value of ROCOPS based on thresholding is calculated. The studies reported in this paper are based on time-domain simulations using MATLAB, and the feasibility of the proposed method is evaluated with an experimental system. The experimental system is a test system that impalement for islanding condition detection. The results show that the proposed islanding detection method succeeds in detecting islanding both in the experimental and simulated systems with negligible Non Detection Zone (NDZ).

In this article different types of artificial neural networks (ANN) were used for CNTFET (carbon nanotube transistors) simulation. CNTFET is one of the most likely alternatives to silicon transistors due to its excellent electronic properties. In determining the accurate output drain current of CNTFET, time lapsed and accuracy of different simulation methods were compared. The training data for ANNs were obtained by numerical ballistic FETToy model which is not directly applicable in circuit simulators like HSPICE. The ANN models were simulated in MATLAB R2010a software. In order to achieve more effective and consistent features, the UTA method was used and the overall performance of the models was tested in MATLAB. Finally the fast and accurate structure was introduced as a sub circuit for implementation in HSPICE simulator and then the implemented model was used to simulate a current source and an inverter circuit. Results indicate that the proposed ANN model is suitable for nanoscale circuits to be used in simulators like HSPICE.

A Wireless Sensor Network (WSN) is a wireless decentralized structure network consists of many nodes. Nodes can be fixed or mobile. WSN applications typically observe some physical phenomenon through sampling of the environment so determine the location of events is an important issue in WSN. Wireless Localization used to determine the position of nodes. The precise localization in WSNs is a complex issue that requires consideration of many prominent aspects such as energy consumption at the nodes as well as the algorithm execution time. In this article, we optimize a system called Spotlight. The spotlight is a localization system that delivers high-location estimation accuracy at low cost. We propose several methods to reduce execution time compared with previous methods in Spotlight. We proposed ILS, LAS and PAS methods that improve execution time about 25%, 50% and 75%. Execution time of the proposed scheme is restricted by the size of deployment area. Furthermore, in these methods, there is no need to equip the nodes with any special hardware.

With the development of restructured power systems and increase of prices in some hours of day and increase fuel price, demand response programs were noticed more by customers. demand response consists of a series of activities that governments or utilities design to change the amount or time of electric energy consumption, to achieve better social welfare or some times for maximizing the benefits of utilities or consumers. In this paper the effect of emergency demand response program on composite system reliability of a deregulated power system is evaluated using an economic load model, AC power-flow-based load curtailment cost function and reliability evaluation techniques. In this paper for calculation the reliability indexes, the Emergency Demand Response Program (EDRP) cost is considered and in each contingency state, the EDRP cost with the customer load curtailment cost is compared and the load appropriate value is selected for load shedding or participating in EDRP. In the next stage, the system and nodal reliability indexes are calculated. To investigate the impact of EDRP activity on composite reliability of restructured power systems the IEEE 6 bus Roy Billinton Test System is utilized. According to obtained results, EDRP using lead to increasing nodal and system reliability. It can be said that solving problems such as congestion in transmission lines, power system reliability decrease at load network peak hours, is impossible without customer interfering in power market. In other hand Consumer participation, makes the power markets more competition and enhance its performance.

In recent year's renewable energy sources have become a useful alternative for the power generation. The power of photovoltaic is nonlinear function of its voltage and current. It is necessary to maintain the operation point of photovoltaic in order to get the maximum power point (MPP) in various solar intensity. Fuzzy logic controller has advantage in handling non-linear system. Maximum power point trackers are so important in photovoltaic systems to increase their efficiency. Many methods have been proposed to achieve the maximum power that the PV modules. This paper proposed an intelligent method for MPPT based on fuzzy logic controller. The system consists of a photovoltaic solar module connected to a DC-DC Boost converter and the fuzzy logic controller for controlling on/off time of MOSFET switch of a boost converter. The proposed MPPT controller for grid-connected photovoltaic system is tested using model designed by Matlab/Simulink program. Comparison of different performance parameters such as: tracking efficiency and response time of the system shows that the proposed method gives higher efficiency and better performance than the conventional perturbation and observation method.