Power Transmission Loss Research Articles

Planning of Low-Voltage Distribution Networks Using Hierarchical Methods

Low-voltage distribution networks represent a component of the power system with the most prominent problems in terms of voltage quality and losses of electrical power which is delivering to the end customers. Overcoming of such problems is a real challenge for distribution companies, since they are obliged to deliver electricity of standard quality to the end customers, but at the same time taking care of their own interests. In this paper, a method based on hierarchical algorithms applicable in the planning of low-voltage distribution networks is presented. The planning of such networks includes determining of an optimum location of substation, radial network configuration, as well as appropriate types of power lines, all in order to achieve the prescribed voltage levels and minimize the power losses in electricity transmission.

An approach of calculation on sliding friction power losses in involute helical gears with modification

Sliding friction between the teeth is recognized as one of the main reasons of power losses in transmission as well as a potential reason of vibration and noise. A new approach is proposed to accurately calculate the sliding friction power losses in involute helical gears considered modification and geometric deviations resulting from the manufacturing processes, assembly errors, and deflections of support structures based on the simulation of gear mesh under light and significant load. Firstly, the paths of contact points on the pinion tooth surface are obtained from tooth contact analysis. Tooth surface load distributions and loaded transmission errors in one mesh period are obtained from loaded tooth contact analysis. Secondly, tooth surface load distributions are converted into the normal forces of tooth surface points of contact, loaded transmission errors are brought to the calculation formulas of sliding velocity, and the sliding friction coefficients of tooth surface points of contact are calculated by a non-Newtonian thermal elastohydrodynamic lubrication model. Substituting the sliding velocities, the normal forces, and the sliding friction coefficients into the power calculation formulas gives the sliding friction power losses of tooth surface points of contact. By the soft MATLAB, the values of the sliding friction power losses are integrated and the sliding friction power loss in helical gears from engagement to disengagement is obtained. Finally, an example of this approach is shown in the end. The results indicate that it is very necessary to consider the influence of loaded transmission errors for calculation of sliding friction power losses.

단순확장관 내부 파티션 위치에 따른 음향투과손실 계산식의 개발

This paper proposed a new formula for predicting acoustic power transmission loss of simple expansion chamber with two internal partitions. Seventeen cases of computational results were performed and the database was constructed for the TL according to the various positions of internal partitions. Using this database, firstly, the formula for the peak values of TL at certain frequencies was developed using the least square estimation. Secondly, the formula for the TL curve could be obtained automatically with the input data of the positions of two internal partitions. The formula of TL developed in this paper showed good agreement with computational results. This formula will be helpful for the positioning of internal partitions to improve TL at target frequencies.

IJIREEICE - Electrical, Electronics, Instrumentation and Control

In this country development of electrical power system particular for transmission line expansion and interconnection of neighbouring power system try to improve system security and economic operation. Due to this province in large scale power system, operation , control and expansion planning for particular system become challenging task to reduce transmission loss as minimum as possible for optimal operation. Now days, One of the major problems in opened power markets is loss division. In this paper, a different method for allocating and identify real power transmission losses to pool market participants is proposed. The proposed method is fundamentally based on decomposition of loss function and different in generators voltage concept. The method has been implemented and tested on several networks and IEEE 5-bus test system sample summarized in the paper. The results show that the method is inclusive and fair to splitting the energy losses of a deregulated power market to its participants.

Analysis and effect of multi-fuel and practical constraints on economic load dispatch in the presence of Unified Power Flow Controller using UDTPSO

Abstract This paper presents an attempt to analyze the effect of multi-fuel and practical constraints on economic load dispatch problem using a novel uniform distributed two-stage particle swarm optimization (UDTPSO) algorithm without and with unified power flow controller (UPFC) while satisfying equality, inequality, practical constraints such as ramp-rate and prohibited operating zone (POZ) limits and device operating limits. A Novel severity function is formulated based on the transmission line overloads and bus voltage violations to identify an optimal location to install UPFC. A multi-objective optimization problem is solved for multi-fuel non-convex cost and transmission power loss objectives. Obtained results for considered standard test functions and electrical systems indicate the effectiveness of the proposed algorithm and can obtain efficient solution when compared to existing methods. Hence, the proposed method is a promising method and can be easily applied to optimize the power system objectives.

Active and reactive power transmission loss allocation to bilateral contracts through game theory techniques

Transmission loss has a considerable effect in overall power generation. For fairly distributing the charge of losses to generators and consumers in a deregulated power system, the allocation of this loss is very important. Game-theoretic methods seem fairer for share determination of each participant of a coalition with no discrimination. In this paper, the active and reactive power transmission losses are allocated to bilateral transactions simultaneously through load flow calculations and cooperative game theory solutions. The loss allocation problem and each bilateral transaction are treated as a game and a player of the game, correspondingly. Two game theory-based approaches, the Shapley value and the $\tau $-value, are surveyed. The former is the most relevant game theory allocation method, while the latter is a novel approach. The influences of all loss allocation game players and bilateral bargains on transmission loss are considered. These two proposed methods are applied to a simple 6-bus network and the modified IEEE 57-bus test system. In the 6-bus network positive MVA loss allocations and in the IEEE 57-bus system negative MVA loss allocations are studied. Finally, the results of allocation procedures are compared to each other.

Enhanced GSA-Based Optimization for Minimization of Power Losses in Power System

Gravitational Search Algorithm (GSA) is a heuristic method based on Newton’s law of gravitational attraction and law of motion. In this paper, to further improve the optimization performance of GSA, the memory characteristic of Particle Swarm Optimization (PSO) is employed in GSAPSO for searching a better solution. Besides, to testify the prominent strength of GSAPSO, GSA, PSO, and GSAPSO are applied for the solution of optimal reactive power dispatch (ORPD) of power system. Conventionally, ORPD is defined as a problem of minimizing the total active power transmission losses by setting control variables while satisfying numerous constraints. Therefore ORPD is a complicated mixed integer nonlinear optimization problem including many constraints. IEEE14-bus, IEEE30-bus, and IEEE57-bus test power systems are used to implement this study, respectively. The obtained results of simulation experiments using GSAPSO method, especially the power loss reduction rates, are compared to those yielded by the other modern artificial intelligence-based techniques including the conventional GSA and PSO methods. The results presented in this paper reveal the potential and effectiveness of the proposed method for solving ORPD problem of power system.

Solving optimal reactive power dispatch problem using a novel teaching–learning-based optimization algorithm

The paper presents a novel teaching–learning-based optimization (TLBO) algorithm, the Gaussian bare-bones TLBO (GBTLBO) algorithm, with its modified version (MGBTLBO) for the optimal reactive power dispatch (ORPD) problem with discrete and continuous control variables in the standard IEEE power systems for reduction in power transmission loss. The feasibility and performance of the GBTLBO and MGBTLBO algorithms are demonstrated for standard IEEE 14-bus and standard IEEE 30-bus systems. A comparison of simulation results reveals optimization efficacy of the GBTLBO and MGBTLBO algorithms over other well established other algorithms like bare-bones differential evolution (BBDE) and bare-bones particle swarm optimization (BBPSO) algorithm. Results for ORPD problem demonstrate superiority in terms of solution quality of the GBTLBO and MGBTLBO algorithms over original TLBO algorithm and other algorithm.

Short-term hydrothermal generation scheduling by a modified dynamic neighborhood learning based particle swarm optimization

Abstract The main objective of the short-term hydrothermal generation scheduling (SHGS) problem is to determine the optimal strategy for hydro and thermal generation in order to minimize the fuel cost of thermal plants while satisfying various operational and physical constraints. Usually, SHGS is assumed for a 1 day or a 1 week planing time horizon. It is viewed as a complex non-linear, non-convex and non-smooth optimization problem considering valve point loading (VPL) effect related to the thermal power plants, transmission loss and other constraints. In this paper, a modified dynamic neighborhood learning based particle swarm optimization (MDNLPSO) is proposed to solve the SHGS problem. In the proposed approach, the particles in swarm are grouped in a number of neighborhoods and every particle learns from any particle which exists in current neighborhood. The neighborhood memberships are changed with a refreshing operation which occurs at refreshing periods. It causes the information exchange to be made with all particles in the swarm. It is found that mentioned improvement increases both of the exploration and exploitation abilities in comparison with the conventional PSO. The presented approach is applied to three different multi-reservoir cascaded hydrothermal test systems. The results are compared with other recently proposed methods. Simulation results clearly show that the MDNLPSO method is capable of obtaining a better solution.

Hybrid optimisation method for optimal power flow using flexible AC transmission system devices

This study proposes a hybrid optimisation method for optimal power flow using a flexible AC transmission system (FACTS). The FACTS plays an important role in the dynamic stability and steady-state control of power systems. This study achieves steady-state control by determining the types and the optimal locations of the FACTS devices and their associated values in the transmission lines. To determine the optimal solutions to the FACTS allocation problem, a hybrid optimisation method that combines a harmony search algorithm and an ant system is proposed. The objective functions of power flow considered are the active power transmission loss, the performance index of the active power flow in the transmission lines and the performance index of the voltage difference between buses. The proposed method was verified on the IEEE 30-bus and Taiwan Power Company 345 kV simplified systems. The results demonstrate that the proposed method improves the total transfer capability and provides better steady-state control of power systems than existing methods do.

English

In recent years in Albanian due to liberalisation of energy market, the built of small hydropower plants (SHP)’s placed at the focus of private investitors. In this paper we will study the impact of Arras small hydropower plant which is built at Diber regional in Albanian power system such as energy efficiency and improvement of voltage level. This study is focused at a part of power system namely Diber area. From the analysis in the case of small hydropower plant connections with power system results in an improvement of voltage level, increasing the efficiency of power system and reduces significantly power transmission losses. We have achieved a model of a part of power system and we have calculated the power flow, level of voltage in different nodes and the transmission power losses of the system with NEPLAN software.

A Recursive Solution for Power-Transmission Loss in DC-Powered Networks

This article presents a recursive solution to the power-transmission loss in DC-powered networks. In such a network, the load cannot be modeled as a fixed equivalent resistance value, since the switching regulator may draw more or less current based on the actual supply voltage to meet the power demand. Although the power-transmission loss itself is simply I2 RL, I, in turn, depends on the load’s supply voltage, which, in turn, depends on I, making it impossible to derive a closed-form solution by classical resistive network analysis in general. The proposed approach is to first derive a closed-form solution to I in the one-node topology using the quadratic formula. Next, we extend our solution to a locally daisy-chained (LDC) network, where the network is readily decomposable into stages, such that the solution combines the closed-form formula for the current stage with the recursive solution for the subsequent stages. We then generalize the LDC topology to trees. In practice, the solution converges quickly after a small number of iterations. It has been validated on real-life networks, such as power over controller area network (PoCAN).

Application of Artificial Intelligence Technique to Economic Load Dispatch of Thermal Power Generation Unit

Economic Dispatch(ED) is one of the main problem of power system operation and control which determines the optimal real power settings of generating units with an objective of minimizing the total fuel cost, subjected to limits on generator real power output & transmission losses. In all practical cases, the fuel cost of generator can be represented as a quadratic function of real power generation. This paper describe and Introduce a new nature Inspired Artificial Intelligence method called Firefly Algorithm(FA). The Firefly Algorithm is a stochastic Meta heuristic approach based on the idealized behavior of the flashing characteristics of fireflies. The aim is to minimize the generating unit’s combined fuel cost having quadratic cost characteristics subjected to limits on generator real power output & transmission losses. This paper presents an application of the FA to ED with valve point loading for different Test Case system. The obtained solution quality and computation efficiency is compared to another artificial intelligence technique, called Genetic algorithm (GA) . The simulation results show that the proposed algorithm outperforms previous artificial intelligence method.

IJIREEICE - Electrical, Electronics, Instrumentation and Control

The operation of generating units to generate energy at reduced cost to reliably serve consumers, recognizing any operational restrictions of generation and transmission facilities is called as Economic Dispatch(ED).In the present paper, an evolutionary modified Deterministic Particle Swarm Optimization (DPSO) is applied for Environmental and Economic Power Dispatch (EED) problem to find fast and efficient solutions for IEEE 14 and 30 bus systems. In such a way, proposed algorithms reduce the total expenditure task of the generating units and improve the computational efficiency. The feasibility of the proposed DPSO based algorithm is demonstrated for two power system test cases consisting of IEEE 14 bus 3-generator system and 30 bus 6-generator system. The results obtained are compared to previous PSO, GA. In practical, power systems which are able to supply a bounded range of electrical load demand, optimizing the operation expenses of the generation units is very significant from an economic point of view. It can be done by proper scheduling of each generating units which is commonly called as Economic dispatch. The conservative technique includes lambda iteration method, base point and participation factor method, gradient method, etc. However, these conventional dispatch algorithms necessitate the incremental cost curves to be monotonically rising or piece-wise linear and are highly sensitive in selecting the initial point and frequently converge to local optimal solution or diverge altogether. Hence, Economic Dispatch (ED) techniques are used to determine a condition with the lowest generation costs. The load demand, transmission power losses and generation cost coefficients are the factors must be taken into account for any ED technique. Newton based algorithms have a problem in handling a large number of inequality constraints. Linear programming methods are fast and trustworthy, but the main drawback is linked with the piecewise linear cost approximation. Non linear encoding technique has a problem of convergence and algorithm complexity.

Windage Power Losses of Ordinary Gears: Different CFD Approaches Aimed to the Reduction of the Computational Effort

Efficiency improvement is one of the main challenges in all fields of design. The reduction of power losses is becoming a great concern also in the design of power transmissions. For this reason it is important to have specific models available in order to quantify the power losses during the design stage. The power losses of a gear transmission can be subdivided into bearing losses, seal losses, meshing losses and hydraulic losses. Although literature provides models for the prediction of losses related to bearings or to gear meshing, for the calculations of the losses generated by the interaction with the lubricant, only few and simplified models are available. For this reason the authors recognize that a general purpose method is required in order to overcome this lack of fit and to improve the capability to predict the efficiency of gearboxes. Being able to compare different design solutions means being able to improve the efficiency, reduce the operating temperature and, consequently, improve the reliability of the system. In this paper, the windage losses generated by a single rotating gear have been studied exploiting different numerical approaches. The results obtained have been compared with measurements showing good agreement.

Fuzzy-TOPSIS for Appropriate Site Selection for Establishing a Thermal Power Plant

Thermal Power Plant (TPP) is one of those discoveries that have changed the daily life of everybody and playing vital role in the present real world. The selection of site for thermal power plant, affects the amount of energy generated, power generation cost, economical development, environment and transmission (loss of power). In present work, fuzzy multi-criteria decision making (FMCDM) approach is proposed for site selection of TPP under partial or incomplete information. The proposed approach initially identified the criteria for site selection of TPP. Then the experts are provided linguistic ratings as well as weights to the potential alternatives against the selected criteria. Fuzzy-TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) is applied to generate aggregate scores selection of best alternative. Finally a case empirical research is adapted to fruitful the proposed approach.

Interactive gravitational search algorithm and pattern search algorithms for practical dynamic economic dispatch

SUMMARY Dynamic economic dispatch strategy consists in determining the output of generation of each unit with respect to predicted load demand over a period of time satisfying the practical unit constraints. In dynamic operation of units, ramp rates (ramp down limit and ramp up limit) are the important constraints that affect considerably the life of the rotor of the generating unit. Recently, a new category of metaheuristic optimization methods has been introduced and attracted many researchers and expert engineers due to their capacity and efficiency to find the near global optimal solution. In this work, a new optimization technique known as gravitational search algorithm (GSA) is proposed and adapted in coordination with pattern search algorithm (PS) to solving the dynamic economic dispatch considering valve point loading effects, ramp rates of generating units and power losses. The proposed hybrid method named communicated GSA–PS allows balancing between exploitation and exploration capability, which makes agents to react more by changing experiences with local search mechanism. The proposed approach has been examined and applied to three practical power systems, 40 generating units to solving the static economic dispatch, 5 generating units, and 10 generating units considering ramp rates limits, valve point effect, and transmission power losses. From the different case studies, it is observed that the results compared with the other recent techniques demonstrate the particularity of the proposed approach and show clearly its effectiveness to solve practical dynamic ED problem. Copyright © 2014 John Wiley & Sons, Ltd.

Novel Multiagent-Based Scheme for Voltage Control Coordination in Smart Grids

AbstractIn this paper, a new multiagent-based voltage control scheme is proposed. The algorithm dynamically adapts the settings of control devices, such as the automatic voltage regulator of generators, transformer with under-load tap changer, and flexible alternating current transmission systems (FACTS), to optimize operational objectives. The objectives are controlling the generator excitation current, reducing transmission power loss, maintaining voltage stability, and improving voltage profile. The constraint is to keep the technical capability limits of system equipment and the transmission line power-flow limits. Furthermore, the effect of load model on voltage control dynamics is addressed. Peer-to-peer device communication is developed to facilitate information exchange among agents. The proposed scheme coordinates the operation of installed voltage control devices on both low voltage and high voltage levels. A simulation test model is implemented using a parallel computing arrangement for a 30-bu...

Solution of multi-objective optimal reactive power dispatch using pareto optimality particle swarm optimization method

For Multi-Objective Optimal Reactive Power Dispatch (MORPD), a new approach is proposed as a simultaneous minimization of the active power transmission loss, the bus voltage deviation and the voltage stability index of a power system are obtained. Optimal settings of continuous and discrete control variables (e.g., generator voltages, tap positions of tap changing transformers and the number of shunt reactive compensation devices to be switched) are determined. MORPD is solved using Particle Swarm Optimization (PSO). Also, Pareto Optimality PSO (POPSO) is proposed to improve the performance of the multi-objective optimization task defined with competing and non-commensurable objectives. The decision maker requires to manage a representative Pareto-optimal set provided by imposition of a hierarchical clustering algorithm. The proposed approach was tested using IEEE 30-bus and IEEE 118-bus test systems. When simulation results are compared with several commonly used algorithms, they indicate better performance and good potential for their efficient applications in solving MORPD problems.

A Lexicographic Optimization and Augmented ϵ-constraint Technique for Short-term Environmental/Economic Combined Heat and Power Scheduling

—In recent years, combined heat and power units have become significant elements in conventional power stations due their numerous merits, including operational cost savings and reduced emissions. In this regard, this article proposes a short-term multi-objective framework for the combined heat and power economic/emission dispatch problem. In addition, to more precisely model the problem, the non-linear forms of fuel cost functions and valve-point loading along with power transmission loss are considered. The objectives of the problem are total cost minimization as well as minimization of pollutant emissions; lexicographic optimization and the augmented epsilon-constraint technique are employed to solve the multi-objective problem. Also, a fuzzy decision making technique has been used to select the most preferred solution among the Pareto solutions. Afterward, a comprehensive comparison is performed between the results obtained from the proposed method and those derived from the non-dominated sorting genetic algorithm II, strength Pareto evolutionary algorithm 2, and multi-objective line-up competition algorithm, verifying the superiority of the presented approach for lower execution time, total cost, and emission. Furthermore, the proposed model is implemented on a large-scale test system while the execution time is rational.