Advanced Materials Research Vols. 433-440

Abstract: Distributed Control System (DCS) equipping the new design methodology comprises an open architecture for intelligent and agile control of distributed control systems by developing a novel international standard “IEC 61499” evolving the event driven functional modules distributed to field devices and interconnected among multiple controllers. It is investigated for predicting the short term power demand using weather and ambient conditions such as temperature, humidity, season, wind and precipitation. Forecasting algorithm simulated via Function Block Development Kit (FBDK) using Fuzzy Logic Controller (FLC). FLC is an advanced method for prediction and control of nonlinear system which is based on fuzzy logic concept comprising an algorithms formulated by linguistically expert rules. Precise mathematical model free system, robustness and flexibility in the event of parameter variations are the most advantages of FLC. In this approach three distributed weather stations are defined for estimating the power demand in a small area using IEC 61499 DCS standard and FLC as a prediction logic. IEC 61499 intensifies flexibility by capability in adaption and system reconfiguration in regard of environment changes, results on cost reduction and diminutions the industrial automation complexity. It increasingly enlarges the adaptability of proposed control system, enhances the system portability, interoperability and develops configurability. IEC 61499 facilitates world trade by swooping technical barriers to trade, eventuates the neoteric markets and economic growth and leads to a strong trend towards distributed automation systems.

Abstract: Short-term load forecasting (STLF) is an important problem in the operation of electrical power generation and transmission. In this paper, STLF algorithm was developed for electrical power systems using mathematical programming with Matlab. A fast and efficient computational algorithm has been obtained for STLF. The mean absolute percentage errors (MAPE) of daily loads forecast and weekly loads forecast for Turkey are found as 1,76%, 1,92%, respectively.

Abstract: This paper aims to solve an order allocation problem in supply chain management (SCM). In this problem, the price fluctuation over consecutive time periods is known beforehand. Based on that assumption, clients can arrange their orders in advance to minimize the costs incurred in SCM, e.g., purchasing cost or inventory holding host. However, order allocations are subject to demand volumes, time-varying costs, suppliers’ capacities, inventory levels, and inventory costs, etc. It is difficult to make a correct decision immediately. With so many factors affecting the decision-making, traditional methods (e.g., dynamic programming) is very time-consuming. Therefore, a genetic algorithm cooperated with a local search is proposed. The experimental results show that the problem can be solved efficiently and near optimally.

Abstract: Ad-hoc networks are attractive, since they can provide a high level of connectivity without the need of a fixed infrastructure. Nodes that are not within the same transmission range communicate through multi-hops, where intermediate nodes act as relays. Mutual cooperation of all the participating nodes is necessary for proper operation of MANET. However, nodes in MANET being battery-constrained, they tend to behave selfishly while forwarding packets. In this paper, we have investigated the security of MANET AODV routing protocol by identifying the impact of selfish nodes on it. It was observed that due to the presence of selfish nodes, packet loss in the network increases and the performance of MANET degrades significantly. Finally a game theoretic approach is used to mitigate the selfishness attack. All the nodes in MANET should cooperate among themselves to thwart the selfish behavior of attacker nodes.

Abstract: With the emergence of Cloud Computing in recent times, there has been a phenomenal growth in the number of Cloud Vendors (CV) providing their services. As far as the customers are concerned, with so many options available on their plates, it becomes increasingly complex and difficult to choose the right Cloud Vendor for their diverse needs. In this paper, we propose a Static Service Ranking System (SRS) with priorities defined by us in general as well as a Dynamic SRS which identifies the specific user’s priorities to rank the Cloud Vendors in order of their needs. Each factor in the priority is given a weightage accordingly and the CV rankings are calculated based on it.

Abstract: This paper presents an empirical path loss model through forest for measuring sea wave energy using 2.4 GHz wireless sensor network (WSN). The empirical path loss model was determined from measurement campaign by using 18 dBm transmitter and the receivers with a low noise amplify. The conventional path loss models for forest environments were carried out such as Weissberger, ITU-R, COST 235 and Torrico models. From the results it is found that the proposed model provides a good agreement and is used for planning WSN.

Abstract: In distributing systems, load forecasting is one of the major management problems to carry on energy flowing; protect the systems, and economic management. In order to manage the system, next step of the load characteristics must be inform from historical data sets. For the forecasting, not only historical parameters are used but also external parameters such as weather conditions, seasons and populations and etc. have much importance to forecast the next behavior of the load characteristic. Holidays and week days have different affects on energy consumption in any country. In this study, target is to forecast the peak energy level the next an hour and to compare affects of week days and holidays on peak energy needs. Energy consumption data sets have nonlinear characteristics and it is not easy to fit any curve due to its nonlinearity and lots of parameters. In order to forecast peak energy level, Adaptive neural fuzzy inference system is used for hourly affects of holidays and week days on peak energy level is argued. The obtained values from output of the artificial intelligence are evaluated two fold cross validation and mean absolute percentage error. The obtained two fold cross validation error as mean absolute percentage error is 3.51 and included holidays data set has more accuracy than the data set without holiday. Total success increased 2.4%.

Abstract: This paper presents a method to determine parameters of BTB (back-to-back) converters in terms of the enhancement of interface flow margins. Interface flow margin is by definition a measure of how much active power can be transferred from the external areas to the study area with the fixed load demand, and it is mainly constrained by system voltage stability. BTB converters are controllable equipments with the active power flow through them, and its DC link in fact can divide the AC systems at the location and hence can reduce the fault current level. This paper first calculates margin enhancement sensitivities at the nose point of F-V curves and formulates an optimization problem to update the BTB parameters to improve the margins. This procedure is repeated performed until the required margin enhancement is achieved.

Abstract: This approach is carry out for developing the Adaptive Neuro-Fuzzy Inference System (ANFIS) for controlling the forthcoming Intelligent Universal Transformer (IUT) in regard of voltages and current control in both input and output stages which is optimized by particle swarm optimization. Current or voltages errors and their time derivative have been considered as the inputs of Nero Fuzzy controller for elaborating the firing angles of converters in IUT basic construction. ANFIS constructed from a fuzzy inference system (FIS) in which the membership function parameters are tuned according to the back propagation algorithm or in conjunction to the least squares method. A neural network maps inputs through input membership functions and associated parameters, and output membership functions and associated parameters to outputs which interprets the input-output map. The associated parameters of membership functions change through the learning algorithm by a gradient vector modeling the input output data in case of given parameters. Optimization method will be investigated to adjust the parameters according to error reduction computed by sum of the squared variation from actual outputs to the desired ones. Advanced Distribution Automation (ADA) is the state of art introducing for tomorrows distribution automation with the new invention in management and control. ADA is equipping by the Intelligent Equipment Devices (IED) in which IUT is a key point introducing as an intelligent transformer subjecting for tomorrows distribution automation in the near future. The proposed ANFIS is a control scheme develop for controlling the IUT by bringing the major advantages like harmonic Filtering, voltage regulation, automatic sag correction, energy storage, 48V DC option, three phase outputs in term of one phase input, reliable divers power as 240V 400HZ for communication utilization and two other 240V 60 HZ outputs, dynamic system monitoring and robustness in major disturbances occurred in terms of input and load variation.

Abstract: This paper proposes a practical mitigation solution to the voltage sag problem by resonant grounding for a 22-kV distribution system of Provincial Electricity Authority (PEA). The simulation is carried out to investigate the voltage sag impact at the low voltage side of the delta/wye distribution transformer connected at the fault location in the existing solidly grounded system and proposed resonant grounded system by ATP-EMTP simulation. The results indicate that the proposed resonant grounding can help all customers connected at the same bus survive from voltage sag problems and also keep the customers on the faulty feeder connected to the system being continuously supplied. In addition, the distribution system with resonant ground lengthens the useful lifetime of the upstream circuit breaker of the feeder as its number of operations is significantly reduced.