Search

This paper presents allocation of energy losses to consumers connected to radial distribution networks in a deregulated environment. A detailed comparison of the proposed 'Exact Method' with three alternative algorithms, namely, pro rata, quadratic allocation and proportional allocation are presented. Pro rata procedure is based on the load demand of each consumer, quadratic and proportional allocations are based on identifying the real and reactive parts of current in each branch and the losses are allocated to each consumer, and the proposed 'Exact Method' is based on the actual contribution of real power loss by each consumer. A case study based on a 30-node distribution system is provided. Index Terms--Deregulation, energy loss allocation, radial distribution systems.

To get the distribution network to operate at its optimum performance in an automated distribution system reconfiguration was been proposed and researched. Considering, however, that optimum performance implies minimum loss, no overloading of transformers and cables, correct voltage profile, and absence of phase voltage and current imbalances, network reconfiguration alone is insufficient. It has to be complemented with techniques for phase rearrangement between the distribution transformer banks and the specific primary feeder with a radial structure and dynamic phase and load balancing along a feeder with a radial structure. This paper contributes such a technique at the low-voltage and medium-voltage levels of a distribution network simultaneously with reconfiguration at both levels. While the neural network is adopted for the network reconfiguration problem, this paper introduces a heuristic method for the phase balancing/loss minimization problem. A comparison of the heuristic algorithm with that of the neural network shows the former to be more robust. The approach proposed here, therefore for the combined problem, uses the neural network in conjunction with a heuristic method which enables different reconfiguration switches to be turned on/off and connected consumers to be switched between different phases to keep the phases balanced. An application example of the proposed method using real data is presented. Index Terms--Distribution automation, distribution control, heuristic algorithm, load balancing, neural network, optimal control, phase arrangement, phase current imbalance, phase voltage imbalance, power loss, reconfiguration.

This paper presents allocation of power losses to consumers connected to radial distribution networks before and after network reconfiguration in a deregulated environment. Loss allocation is made in a quadratic way and it is based on identifying the real and imaginary parts of current in each branch, and losses are allocated to consumers. The network reconfiguration algorithm is based on the fuzzy multiobjective approach and the max-min principle is adopted for the multiobjective optimization in a fuzzy framework. Multiple objectives are considered for real-power loss reduction in which nodes voltage deviation is kept within a range, and an absolute value of branch currents is not allowed to exceed their rated capacities. At the same time, a radial network structure is maintained with all loads energized. The three objectives considered are modeled with fuzzy sets to evaluate their imprecise nature and one can provide his or her anticipated value of each objective. A 69-node example is considered to demonstrate the effectiveness of the proposed method. Index Terms--Fuzzy multiobjective optimization, loss allocation, network reconfiguration.

In this conceptual paper, a framework for defining loss calculation methodologies is proposed. Nine basic elements required to define and/or classify loss calculation methodologies are presented. Three elements specifically deal with substantive policy decisions, one element is about risk management, and the remaining five elements represent process or calculations. Description of each of these elements and how they relate to various loss calculation methodologies are included. Index Terms--Actual losses, allocation of losses, average losses, loss calculation, loss factor, marginal losses, normalization of losses, power system, risk, transmission.

Energy losses in distribution systems are generally estimated rather than measured, because of inadequate metering in these systems and also due to the high cost of data collection. These estimations are generally based on some rules of thumb. This paper presents the results of a joint investigation undertaken in collaboration with a local utility to study this issue. Based on data collected from feeders specially instrumented for this purpose, true losses in some primary and secondary feeders are obtained. These losses are compared with the estimated losses obtained by the methods presently in use. In view of the large discrepancies observed between measured and estimated values, two new schemes for estimating losses in primary and secondary distribution networks have been developed. The measured values are used to highlight the reliability of the new estimation methods. Index Terms--Distribution systems, loss estimation, primary and secondary distribution networks, radial feeders.

The second part of this paper presents a practical implementation and application of the methodology for the stochastic assessment of the annual financial losses due to interruptions and voltage sags discussed in the first part of this paper. The costs of interruptions and voltage sags are determined separately and then combined in order to estimate the total financial losses in the network. The methodology is illustrated on a generic realistic distribution network with all relevant network components modeled appropriately. Finally, different network topologies are compared taking into account total financial losses in the network. It is shown that the inclusion of the financial losses due to voltage sags that may account for up to about 20% of the interruption costs may alter the network topology ranking. Index Terms--Financial losses, interruptions, power quality (PQ), reliability, voltage sags.

This paper presents a generalized methodology for stochastic/probabilistic assessment of the annual financial losses due to interruptions and voltage sags. The costs of interruptions and voltage sags are treated separately and then combined in order to estimate the total financial losses in the network per annum. The methodology proposed is applicable to both assessment of individual customer losses and assessment of total network losses. It takes into account in a probabilistic manner all the uncertainties associated with the voltage sag calculation, sensitivity of customers' equipment to voltage sags, the interconnection of the equipment within an industrial process, and customer types and the location of the process in the network. Index Terms--Financial losses, interruptions, power quality (PQ), reliability, voltage sags.

This paper presents a study on losses in cables and transformers considering nonsinusoidal conditions in commercial facilities. A mathematical development based on classical definitions available in the literature supports the proposal of a factor that is suitable to indicate where losses are significant and must be compensated. A case study is also presented and meticulously analyzed in order to validate the theoretical assumptions. Index Terms--Harmonic distortion, losses, power system harmonics, reactive power.

Faults on the electric power distribution system are responsible for a large portion of the interruptions that a customer will experience. To maintain a high level of system reliability, vegetation maintenance is often required. Analytical prediction of the effects of vegetation maintenance on distribution system reliability requires a model of the expected failure rate of line sections that includes the effects of vegetation. Vegetation-related failures are more likely to occur as the vegetation near the overhead power lines grows, increasing the line-section failure rate. Due to difficulties in using existing growth models, this paper proposes to use a direct model for failure-rate prediction based on factors that affect vegetation growth. Four models are considered: linear regression, exponential regression, linear multivariable regression, and an artificial neural network (ANN). The models are tested with historical vegetation growth parameter data and feeder failure rates. Results are compared and the features of each model are discussed. Index Terms--Failure-rate modeling, failure-rate prediction, line clearance, neural networks, power distribution systems, regression, reliability, tree trimming, vegetation maintenance.

The problem of the harmonic loss evaluation is of growing interest among power system engineers, both for the increase of operating costs and the decrease of the useful life of the system components. The paper addresses this problem with a probabilistic approach to take into account the randomness of current and voltage harmonics; a method for evaluating the expected value of the operating costs and of the premature aging costs is presented. A numerical application to a test system is also discussed, showing the viability of the proposed approach and the significance of the results; in particular, the aging costs turn out to be unaffected by the type of probability density function describing the harmonics. Keywords - Power system harmonics, Harmonic effects, Probabilistic approach.

A new special stability control termed CAPS improves power system stability by exploiting the time-overvoltage capability of large shunt capacitor banks. During low voltage emergencies, several series groups of wye-connected capacitor banks are shorted to increase reactive power output. We describe successful commissioning tests on a 241.5-kV, 168-MVAr capacitor bank.

An adaptive loss evaluation algorithm for power transmission systems is proposed in this paper. The algorithm is based on training of artificial neural networks (ANNs) using backpropagation. Due to the capability of parallel information processing of the ANNs, the proposed method is fast and yet accurate. Active and reactive powers of generators and loads, as well as the magnitudes of voltages at voltage-controlled buses are chosen as inputs to the ANN. System losses are chosen as the outputs. Training data are obtained by load flow studies, assuming that the state variables of the power system to be studied take the values uniformly distributed in the ranges of their lower & upper limits. Load flow studies for different system topologies are carried out and the results are compiled to form the training set. Numerical results are presented in the paper to demonstrate the effectiveness of the proposed algorithm in terms of accuracy and speed. It is concluded that the trained ANN can be utilized for both off-line simulation studies and on-line calculation of demand and energy losses. High performance has been achieved through complex mappings, modeled by the ANN, between system losses and system topologies, operating conditions and load variations. Keywords: capacity loss, energy loss, artificial neural network, power transmission systems

This paper proposes a methodology to derive the simplified model for distribution system loss analysis. According to the typical daily load patterns and the energy consumption of customers, the hourly loading of distribution transformers can be solved. A three-phase load flow program is applied to calculate the feeder power flow so that the hourly feeder loading will be the same as that obtained by the field test. The hourly primary conductor loss, secondary conductor loss, transformer copper loss and core loss are then solved according to the mathematical modeling of system components. The sensitivity analysis of system loss with respect to the feeder loading, power factor, feeder length, transformer capacity is then performed to derive the simplified loss model of distribution feeders. A distribution feeder of Taipower system is then selected for computer simulation to demonstrate the effectiveness of the proposed method. By applying the simplified loss model derived, the daily loss pattern of distribution feeders is solved according to the actual hourly feeder loading. It is concluded that the proposed methodology provides an useful tool for distribution engineers to estimate the operation efficiency of distribution systems in a very effective manner.

No measuring method is presently available for direct and sufficiently accurate evaluation of power losses in thyristor valves used in HVDC converter stations and Static VAR controllers. This paper presents a measuring method to be used during the valve type tests with the intention to verify the guaranteed loss characteristic. The method was validated under laboratory conditions by comparison to a sophisticated calorimetric technique. An uncertainty of 1% was achieved at conditions simulating full load operation. Voltage across and current through the valve are recorded in discrete steps and digitized. The loss is then calculated as their product. Special current and voltage sensors were developed to cover a very high dynamic range of the measured quantities. A high resolution, multichannel digital recorder was used for simultaneous registration of two voltage and two current signals. The method is of a general application, since the valve is treated as a two port circuit. Therefore, it can be used to measure loss in other non-linear components and apparatus, where large dynamic changes of the measured quantities preclude application of conventional techniques.

A detailed time domain model for the eddy current losses in the windings of a transformer is presented. The basic elements for the derivation of the model are the turns which may be combined into sections. The model is expressed as an R-matrix. Its diagonal elements were fitted using a series Foster circuit while for the off-diagonal elements we used the basis functions of the Foster circuits to derive the time domain model in the form of state equations. For validation, the losses computed with the detailed model are compared with those obtained by considering full windings. The frequency response of the transformer model is compared with test results. Simulations are presented for illustration and further validation.

A novel window is presented and applied in electrical power system harmonic analysis. The goal of increasing the resolvability of low magnitude non-harmonic tones close in frequency to higher magnitude harmonics and the detectability of very low magnitude high frequency harmonics is pursued. The proposed window is derived from the Tseng window; its spectrum can be modeled in the synthesis stage and it is characterized by a narrow width main lobe and by sidelobes which are very low in correspondence to some specified frequencies. Numerical experiments demonstrate the performances and the usefulness of the new window in resolving periodic distorted waveforms in power systems.

A new method based on a heuristic technique for reactive loss reduction in distribution network is presented. This method allocates capacitors to certain nodes (sensitive nodes) which are selected by first identifying the branch which has the largest losses due to reactive power. Then, the node therein, which has the largest reactive power is selected. The capacitor rating is determined by differentiating the system losses with respect to the load connected to that node. The compensating capacitors are placed at these optimal locations with appropriate VAR ratings to achieve maximum benefits in dollar savings. The variation of the load during the year is considered. The capital and installation costs of the capacitors are also taken into account. This method is applied to a 38 feeder distribution system of 27.6 kV, 560 MVA of the city of Windsor, Ontario, resulting in annual saving of about CAN $145,000 after amortizing the capital and installation costs of applying the compensating capacitors, and using a figure for the cost of energy of 1.986 cents per kWh.

The problem of modifying the harmonic power flow analysis to permit the inclusion of nonlinear anisotropic transformers and computation of their iron-core (and copper losses, so far neglected in power flow studies, constitutes the objective of this paper. The nonlinear model used for transformers is capable of simulating saturation of iron-cores, anisotropy of laminations, and the iron-core and copper losses associated with anisotropic transformers, but simple enough to be included in the harmonic power flow algorithm without deteriorating its convergence properties. The dependency of iron-core losses on the maximum value of the total (fundamental and harmonic) flux density and the fact that iron-core losses are a function of the waveform of the induced voltage - that is its harmonic phase shifts with respect to the fundamental phase angle - are included. The induced voltage is transformed from frequency domain to time domain: the instantanenous induced voltage and the computed [lambda]-i characteristics are employed to compute the instantaneous magnetizing and core-loss currents. Thereafter, a transformation is made from time domain back to frequency domain to compute the fundamental and harmonic components of the above-mentioned currents. Therefore, transformer harmonic couplings are properly modeled and included in the analysis. The modified harmonic load flow formulation is applied to a balanced three-phase feeder consisting of a grounded-wye, grounded-wye nonlinear anisotropic transformer and linear and nonlinear loads. The main contribution of this paper is the computation of iron-core (and copper) losses of transformers used in balanced three-phase and single-phase systems at (non)sinusoidal operation.

Neural networks include the capability to map the perplexed and extremely non-linear relationship between the load levels of zone and the system topologies, which is required for the feeder reconfiguration in distribution systems. This study is intended to propose the strategies to reconfigure the feeder, by using artificial neural networks with the mapping ability. Artificial neural networks determine the appropriate system topology that reduces the power loss according to the variation of load pattern. The control strategy can be easily obtained on the basis of the system topology which is provided by artificial neural networks. Artificial neural networks are designed to two groups. The first group is to estimate the proper load level from the load data of each zone, and the second is to determine the appropriate system topology from the input load level. In addition, several programs with the training set builder are developed for the design, the training and the accuracy test of artificial neural networks. Finally, we also evaluate the performance of neural networks designed here, on the test distribution system. Neural networks are implemented in FORTRAN language, and trained on the personal computer COMPAQ 386.

This paper presents a systematic method to derive an optimal switching plan to achieve energy loss minimization for short term and long term operation of distribution systems. The short term optimal switching criterion is developed by binary integer programming with branch and bound technique. A overall optimization problem is formulated for the optimal switching operation. It is further divided into several subproblems to find the largest energy loss reduction among all possible switching operation between two feeders. A quick method is applied to estimate the largest loss reduction for each feeder-pairs in the distribution system during short term switching operation. In this paper, the composite load profile of each feeder is derived by the field test over one year time period. According to the typical load patterns of each customer type, the hourly loading of each service section can be simulated more accurately. After determining the hourly optimal network configuration by taking into account the typical daily load patterns for all the distribution feeders, the long term optimal switching criterion for each season is derived and the corresponding critical switches, which should be operated for energy loss reduction as season changed from summer to winter and vice versa, are also determined. During the computer simulation, the installation and operation cost of sectionalizing switches are included in the objective function as actual cost so that the results obtained will be more practical. A practical Taipower distribution system is selected for computer simulation to demonstrate the efficiency and practicality of the proposed method to reduce the energy loss by operating the critical switches derived.

An electrical distribution system reconfiguration algorithm to reduce system losses is presented. The algorithm calculates switching patterns as a function of time. Either seasonal or daily time studies may be performed. Both manual and automatic switches are used to reconfigure the system for seasonal studies, whereas only automatic switches are considered for daily studies. A load estimation algorithm provides load information for each time point to be analyzed. The load estimation algorithm can incorporate any or all of the following: spot loads, circuit measurements, and customer time-varying diversified load characteristics. Voltage dependency of loads is considered at the circuit level. It is shown that switching at the system peak can reduce losses but may cause a marginal increase in system peak. Data structures used to model loads and to store switch configurations as a function of time are described. Example problems are provided to illustrate results.

This paper reports a power flow based heuristic algorithm for determining the minimum loss configuration of radial distribution networks. The algorithm is based on the concept of optimum flow pattern which is determined by solving the KVL and KCL (Kirchhoff's voltage and current laws) equations of the network. The optimum flow pattern of a single loop formed by closing a normally open switch is found out and the flow pattern is established in the radial network by opening a closed switch. This process is repeated till the minimum loss configuration is obtained. A simple, fast and approximate power flow method has also been developed to assist the reconfiguration algorithm. The proposed reconfiguration algorithm has been found to give better network configuration than those obtained by some other recent methods reported in literature.