In this paper, Brent method is proposed to solve dynamic economic dispatch (DED) problem with TRANSMISSION LOSSES. The proposed algorithm involves the selection of the values of incremental fuel costs (lambda) and then the evaluation of optimal lambda is done by Brent method. The constraint of ramp rate limits distinguishes the DED problem from traditional static economic dispatch (ED) problem. The DED problem divides the entire dispatch period into a number of small time intervals and then static economic dispatch problem is solved in each interval by incorporating the ramp rate limits. The proposed method has been tested on 6- and 15- units. The simulation results of the proposed method are compared with conventional lambda iterative method. The simulation results show that the proposed method achieves qualitative solution with less computational time than the conventional lambda iterative method.

Part of water flowing downstream in rivers, infiltrates into the bed river. Infiltrated water depends on morphologic and hydraulic characteristic of the rivers. Planners and managers want to know the amount of water infiltrates into the bed and consequently recharges ground water. In this study three rivers of Kashaf rud river basin, namely Ferizi, shandiz (Zoshk) and Golestan, were selected and their discharges were measured during period of 2009-2011 at the beginning and the end of a selected reach in each of the mentioned rivers by a current meter. Then TRANSMISSION LOSSES (TL) of the reaches were computed by subtracting the measured discharges. By surveying longitudinal profile and cross sections of the reaches and running the Hec-Ras model, wetted perimeter was determined for every discharge measurement for three selected reaches. Analysis of data showed that there is a significant exponential relationship between TL and the measured discharge at the beginning of the reach and wetted perimeter for one kilometer of the reach. The results showed that the percentage of TL decreases with increasing of the discharge in each river. As well as TL rate decreases from west to east; on the other hands in Ferizi river is the most and in Golestsn river is least. Developing an exponential model which is independent of the wetted perimeter, is one of the other results of the research.

The Optimal Power Flow is one of the fundamental problems in power system analyses. Some essential studies in power system operation and planning typically require a large number of repetitive OPF solutions. In these analyses, the convergence speed of the OPF solutions beside their accuracy are two key objects. The full ACOPF is accurate, but takes long solution time. The DCOPF is a simple approximation of OPF that is very fast but is not so accurate. This paper presents a method to improve the accuracy of DCOPF, based on evaluating some nodal shares of TRANSMISSION LOSSES. Like the previous DCOPF, the Modified DCOPF is derived from a non-iterative DC power flow, and thus its solution requires no long run time. Moreover, it can simply be realized in the form of Lagrange representation, makes it possible to be considered as some constraints in the body of any bilevel optimization problem, with its internal level including the OPF satisfaction. The efficiency of the Modified DCOPF is illustrated through implementing on three test cases (IEEE 30 & 118 Bus test systems and Iran 2006 TRANSMISSION Network) and comparing the results (generation levels, line flows, and voltage angles) with the conventional DCOPF and full ACOPF.

Flow in ephemeral streams of arid regions occurs in a short period of time and is highly variable. Floods in these dry-land rivers change their volume as they travel downstream due to infiltration from the beds and floodplains. This reduction in flow, termed TRANSMISSION LOSSES, also causes attenuation of flood wave and acts as recharge source for groundwater and qanats. In this research, a model for dynamic flood routing in ephemeral rivers has been developed. To achieve this, the Saint-Venant equations were modified by including TRANSMISSION LOSSES in them and a computer code was developed in MATLAB to solve the equations. Model was verified because the performance of the model under Lane’s hydrograph and the data of Hughes Wash River were satisfactory. To further understand the flow behavior and predict TRANSMISSION LOSSES, model was run for a reach in Zoshk River in Khorasan Razavi. Sensitivity analysis of parameters of this dynamic-routing model shows that the outputs of the model (peak flow, flood volume and seepage volume) are more sensitive to the length and hydraulic conductivity of the reach of study and peak flow of inflow hydrograph.

Flow in streams of arid and semi-arid regions is not perennial and usually floods occur after seasonal precipitations. Therefore, the bed material is dry and underneath soil is in unsaturated condition prior to occurrence of floods. As a result, volume of flood hydrographs decreases due to infiltration as they travel downstream. This reduction in hydrograph volume is usually termed as TRANSMISSION LOSSES. Because of the existence of ephemeral rivers in most parts of Iran, study on TRANSMISSION LOSSES in these areas is necessary.In this paper, regression equations are developed for estimating TRANSMISSION LOSSES in ephemeral rivers of Ghara-Ghoom catchment in Khorasan Razavi province. To achieve this, gauging stations' data and physical characteristics of Kashafrud, Kardeh and Zoshk rivers were collected and analyzed. TRANSMISSION LOSSES in the first kilometer was considered as dependent variable in regression analysis and its dependency was tested against upstream flow volume, flow duration, antecedent moisture content, hydraulic conductivity, slope and width of the river as independent variables. Upstream flow volume was found to be the most important variable in explaining TRANSMISSION LOSSES. Three regression equations (linear and nonlinear) were developed for relating TRANSMISSION LOSSES to the most significant involved variables for Ghara-Ghoom catchment. Estimates of TRANSMISSION LOSSES can be made for any unit length (km) by calculating the flow volume at the beginning of the unit length as flow volume minus the TRANSMISSION loss in the previous unit length. Such equations can be used by water resources managers and hydraulic structure designers.

One of the significant factors in acoustic signal analysis is the TRANSMISSION Loss (TL). This factor is vastly dependent on the frequency of the signal, the traveling distance and the propagating medium condition. The propagating medium condition is usually specified in accordance to the kind of channel in which the sound wave travels in. An important type is the shallow water channel. This type of channel is especially useful for passive Sonar analysis in shallow water applications such as the Persian golf and the Red sea. In this paper a feed forward multilayer neural network is introduced for modeling and prediction of acoustic TRANSMISSION LOSSES. The inputs to the network are the traveling distance, the sound frequency, and the sea state. The process is in line with the way of natural learning and is suitable for online pattern to pattern training as the actual data from the sonar becomes available.  

Reactive power dispatch for voltage profile modification has been of interest to power utilities. Usually local bus voltages can be altered by changing generator voltages, reactive shunts, ULTC transformers and SVCs. Determination of optimum values for control parameters, however, is not simple for modern power system networks. Heuristic and rather intelligent algorithms have to be sought. In this paper a new algorithm is proposed that is based on a variant of a genetic algorithm combined with simulated annealing updates. In this algorithm a fuzzy multi-objective approach is used for the fitness function of the genetic algorithm. This fuzzy multi-objective function can efficiently modify the voltage profile in order to minimize TRANSMISSION lines LOSSES, thus reducing the operating costs. The reason for such a combination is to utilize the best characteristics of each method and overcome their deficiencies. The proposed algorithm is much faster than the classical genetic algorithm and can be easily integrated into existing power utilities software. The proposed algorithm is tested on an actual system model of 1284 buses, 799 lines, 1175 fixed and ULTC transformers, 86 generators, 181 controllable shunts and 425 loads.

In this research, the factors affecting on electricity gap were examined in the electricity industry in Iran using the system dynamics approach compared to the econometric method. In the framework of the electricity gap prediction model, simulation of energy demand were investigated as well as its supply and effective factors. Analysis of the problems with these systems was very complicated because it is a simulated model based on many variables, relationships, and delays between these variables. In this study, the electricity gap was analyzed in light of the supply and demand of energy and considering the market equilibrium price, and the gap value was investigated using a dynamic system model. Also, using a regression analysis and using econometric methods (ARMA and ARIMA modeling), the gap was estimated. The data were used for the years since 1383 to 1393, which was adapted from Iran Energy Balance Sheet. Simulation for a 25-year period for dynamic systems and a 35-year period for a structural model was considered. In these study, the result was that the RMSE criterio for the structural model was 0. 015 and for the dynamic model 0. 057, and showed that estimating the structural model is more accurate than simulation by dynamic systems. Regarding the results, dynamic modeling was with more error for data estimation and was more suitable for showing the relationship between variables (causal and causal relationships) as well as the effect of each variable on another. Therefore, in order to more accurately estimation the data, structural modeling is more appropriate with regard to the information obtained.