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**1 - 8**of**8**### The Estimation of Electric Power Losses in Electrical Networks by Fuzzy Regression Model Using Genetic Algorithm

"... This paper presents the comparative study for fuzzy regression model using linear programming, fuzzy regression model using genetic algorithms and standard regression model. The fuzzy and standard models were developed for estimation of electric power losses in electrical networks. Simulation was ca ..."

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This paper presents the comparative study for fuzzy regression model using linear programming, fuzzy regression model using genetic algorithms and standard regression model. The fuzzy and standard models were developed for estimation of electric power losses in electrical networks. Simulation was carried out with a tool developed in MATLAB.

### Fast Power Loss Computation and Shunt Capacitor Insertion Using Fuzzy Logic Technique 1

"... Abstract: Fast power loss computation was implemented using supervisory control and data acquisition system (SCADA) with personal computer. Logic Control Array (LCA) and EPROM circuits were used to implement SCADA system to facilitate the required measurements to obtain the daily load profile for re ..."

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Abstract: Fast power loss computation was implemented using supervisory control and data acquisition system (SCADA) with personal computer. Logic Control Array (LCA) and EPROM circuits were used to implement SCADA system to facilitate the required measurements to obtain the daily load profile for residential and commercial customers. LCA, EPROM and PC were used to simplify the electronic circuits, reduce the cost and speed up the computation time. An illustrative example had been considered to measure, store and show the active power, reactive power, load voltage, load current, power factor and the shunt capacitors current. It as observed that when 2.7 MVAR bank capacitor inserted in the network the load current decreased from 740.8A to 688.4A and the power factor was improved from 0.80 to 0.93, which reduced the apparent power, hence allowing to add more loads to the network and release the feeder capacitor. A rule-based fuzzy decision maker had been designed and tested with the real data collected from Jordan electricity board using SCADA system. The calculated output was almost similar to that obtained from the first approach presented in this study. The advantage of using fuzzy decision maker was its simplicity that can be implemented on a programmable logic device. Key words: Power factor improvement, power loss computation, fuzzy-based decision maker, capacitor insertion, programmable logic device

### 9 Electric Load Modeling for Long-Term Forecasting

"... Long-term electric peak-load forecasting is an important issue in effective and efficient planning. Over- or underestimation can greatly affect the revenue of the elec-tric utility industry. Overestimation of the future load may lead to spending more money in building new power stations to supply th ..."

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Long-term electric peak-load forecasting is an important issue in effective and efficient planning. Over- or underestimation can greatly affect the revenue of the elec-tric utility industry. Overestimation of the future load may lead to spending more money in building new power stations to supply this load. Moreover, underestimation

### A combined 2-dimensional fuzzy regression model to study effect of climate change on the electrical peak load

"... Abstract—This paper studies the impact of climate change on the electricity consumption by means of a fuzzy regression approach. The climate factors which have been considered in this paper are humidity and temperature, whereas the simultaneous effect of these two climate factors is considered. The ..."

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Abstract—This paper studies the impact of climate change on the electricity consumption by means of a fuzzy regression approach. The climate factors which have been considered in this paper are humidity and temperature, whereas the simultaneous effect of these two climate factors is considered. The impacts of other climate variables, like the wind, with a minor effect on energy consumption are ignored. The innovation which applies in this paper is the division of the year into two parts by using the temperature-day graph in the year. To index the humidity, data of the minimum humidity per day are used. For temperature, the maximum temperature of the first part of the year (warm days) and the minimum of the second part (cold days) are used. The indicator for the consumption is the daily peak load. The model results show high sensitivity to the temperature but low sensitivity to the humidity. Moreover, it is concluded that the model structure cannot be the same and for the cold par additional variables such as gas consumption should be considered. Keywords- fuzzy regression, electricity consumption, climate change I.

### Data clustering Intelligent methods Oceanic observing network

"... ty d d re S). D ssin nd p on the greedy clustering algorithm, and a data processing method based on the maximum entropy for the nce to acet o ather a ur abi applications when working offshore. The oceanic data is sparser than terrestrial-based information [5]. This is because data collec-tion is mor ..."

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ty d d re S). D ssin nd p on the greedy clustering algorithm, and a data processing method based on the maximum entropy for the nce to acet o ather a ur abi applications when working offshore. The oceanic data is sparser than terrestrial-based information [5]. This is because data collec-tion is more difficult. Integrated ocean observation network has certainly arrived as a well-established application domain. The ini-tial impetus for developing an integrated ocean observation sys-tem is the need to automate the production of nautical charts ment of wireless communication and computer network, real-time data transfer from offshore has become an important factor in ocean observing. One of the goals is to make this system fully auto-mated in collecting, processing and presenting real-time informa-tion to the end users [9]. The data processing of the OWS attempts to automate the process of oceanic data processing, but the data environments are dynamic in many respects: data adding and removing, real-time data updating, users preferences and goals change, and data applications is a dynamic process [10]. Data domains are often high-dimensional and spare. One of data processing ways in the

### Reactive Power Compensation Using Fuzzy Controller

"... The nature of load whether industrial or residential is more or less inductive rather than resistive. Therefore always the power factor remains to be as low as cos 900 = 0. Such a condition of p.f. is highly disadvantageous to the supplier and due to this reason the supplier fixes the tariff, at cer ..."

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The nature of load whether industrial or residential is more or less inductive rather than resistive. Therefore always the power factor remains to be as low as cos 900 = 0. Such a condition of p.f. is highly disadvantageous to the supplier and due to this reason the supplier fixes the tariff, at certain fixed value of power factor which may be 0.8 and above. The concept of power factor improvement is same as reactive power compensation. The consumer has therefore to maintain a bank of capacitors with in his premises. These capacitors are to be put across the load to preserve the power factor at some threshold value. Also beyond certain level the approach of P.F. improvement or reactive power compensation proves to be uneconomical because the cost of capacitor outweighs the profits of savings caused by the addition of extra capacitance at the load end. The efforts have been made in the present work to develop a fuzzy controller to enable the capacitance of right size to be added across the load so that the cost of operation is minimum or the saving is maximum. Based on the out come of fuzzy controller the actual feed back control system would enable the right size of capacitance to be placed across load. The automation in p.f. Control would always ensure that the size of capacitance to be placed across the load is responsive to the desired improvement in p.f. or reactive power compensation.