Optimal Load Flow Research Articles

Containing Wind Farm Power System Probabilistic Optimal Power Flow Calculation Using the Method of Combined Cumulants and Gram-Charlier Expansion

This paper uses the optimal probabilistic load flow method for power containing wind farm analysis. Based on Computation of optimal load flow using the Interior point method ,considering the stochasticlal power output of wind generator and the random outage of synchronous generator and the stochastic of load power, calculating the probability distribution of branch power flow and node voltage. This paper uses RTS-24 as the example to analysis the method ,and comparison the results with that of the Monte-Carlo method, to analysis the change of power system after the grid connected of wind turbine.

Optimal multiplier load flow method using concavity theory

This paper utilises concavity properties in the optimal multiplier load flow method (OMLFM) to find the most suitable low voltage solution (LVS) for the systems having multiple LVS at the maximum loading point. In the previous method, the calculation of the optimal multiplier is based on only one remaining low voltage solution at the vicinity of voltage collapse point. However, this does not provide the best convergence for multi-low voltage solutions at the maximum loading point. Therefore, in this paper, concavity properties of the cost function in OMLFM are presented as the indicator to find the most suitable optimal multiplier in order to determine the most suitable low voltage solutions at the maximum loading point. The proposed method uses polar coordinate system instead of the rectangular coordinate system, which simplifies the task further and by keeping PV type buses. The polar coordinate in this method is based on the second order load flow equation in order to reduce the calculation time. The proposed method has been validated by the results obtained from the tests on the IEEE 57, 118 and 300-bus systems for well-conditioned systems and at the maximum loading point.

A hybrid method combining JFPSO and probabilistic three-phase load flow for improving unbalanced voltages in distribution systems with photovoltaic generators

This paper presents a new hybrid method that combines jumping frog and particle swarm optimization and probabilistic three-phase load flow to improve unbalanced voltages in distribution systems with photovoltaic generators. This paper applies a new three-phase probabilistic load flow based on the Monte Carlo simulation. The voltage regulation is one of the principal problems to be addressed in photovoltaic distributed generation. The proposed method defines the nodes where photovoltaic grid-connected system is connected and their mean power output minimizing the maximum value of voltage unbalances at the nodes. Numerical applications are presented using the unbalanced distribution system IEEE 13-nodes and including photovoltaic generators at several nodes. The results obtained show the decrease in the unbalance factor due to the presence of distributed generation.

Quadratic Discriminant Index for Optimal Multiplier Load Flow Method in ill conditioned system

In ill conditioned power systems, the classical Optimal Multiplier Load Flow Method (OMLFM) can only calculate Low Voltage Solutions (LVS) at the vicinity of the maximum loading point (MLP). It cannot determine the boundary zone between solvable and unsolvable cases of load flow equations solution. Considering this limitation, this paper proposed the Quadratic Discriminant Index (QDI) based on the properties of quadratic form of load flow equations to enhance OMLFM to find LVS at the MLP in polar coordinate form. These properties can describe all straight lines through two distinct state variables solution as Multiple Load Flow Solutions (MLFS) in OMLFM. The trajectory of these lines approaches MLP in term of loading factor. Furthermore, in this process, MLP in well, ill and unsolvable operation zones can also be determined. The test results of a single-machine system and IEEE 14, 57 and 118-bus test systems demonstrate the validity of the proposed method.

Voltage and Reactive Power Load Flow Optimization in the Power System Using Fuzzy Logic

The paper presents issues related to voltage control in the power system. An original method of reactive power flow optimization is considered, which leads to improved voltages in the power system and reduced active power losses. The optimization method is based on a procedure that employs fuzzy logic and is supported by a gradient search algorithm. The method has been implemented in PLANS software and verified.

Purification, antioxidant activity and protein-precipitating capacity of punicalin from pomegranate husk

Punicalin is a kind of ellagitannin, existing in pomegranate husk, and has shown remarkable biological activities. A rapid and large-scale separation method of punicalin from pomegranate husk was established, using medium pressure liquid chromatography (MPLC). The optimal mobile phase consisted of 5% methanol and 0.1% (v/v) TFA in water, and the optimal loading amount and flow rate were 1.0g and 80ml/min, respectively. Under this condition, 339mg of 95.9% punicalin could be obtained in 40min. 59.7mg of 78.0% gallic acid could be separated simultaneously. This method was practical for industrial utilisation of pomegranate husk. Afterwards, the antioxidant and protein-precipitating capacities of the purified punicalin, together with punicalagin, were evaluated. Results showed that punicalin had strong antioxidant activity, and it exhibited a low affinity for protein. This suggested that the antioxidant of punicalin would not be greatly masked by tannin–protein precipitation in application, and hence confirmed punicalin to be a promising antioxidant.

Coordinated control of series‐connected offshore wind park based on matrix converters

ABSTRACTOptimization and reliability are two important aspects in design and operation of wind parks either for offshore as for onland emplacements. However, offshore locations demand conscientious effort in optimizing the size and the weight of each component in the energy conversion system because of the high investment and maintenance costs related with the supporting structures and transportation respectively. Achieving these two objectives requires the combination of different optimization stages, which consider a suitable design of the entire conversion system with innovative and more efficient power electronic devices, optimized topology of the offshore grid and customized control strategies for optimizing the operation of the park.This paper presents an energy conversion concept for wind turbines on the basis of a reduced matrix converter (RMC) that will enable series direct current architecture in offshore wind parks thus preventing the need for offshore platforms. The RMC is built with bidirectional semiconductors that give reduced losses because of both superior topology and more efficient semiconductors. The proposed conversion topology is tested in stationary state and transient operation. In addition to operational features of the concept, control and operation of a wind park with several turbines are presented.Dynamic operation of the turbine as well as the high‐voltage direct current transmission line effects are considered. Three types of models are therefore developed. First, an accurate and detailed model for analyzing one single turbine with the converter operated at high‐frequency switching is presented. This model considers a new modulation for the RMC. A second and simplified model is used for small signal analysis. This model permits to simulate several series‐connected cluster during transient. Finally, an optimal direct current load flow model is used for evaluating stationary state operation.Results show the technical feasibility of the proposed concept and their advantages over conventional topologies. The paper also discusses the technological challenges that this type of offshore grid architecture will bring. Copyright © 2011 John Wiley & Sons, Ltd.

Binary Particle Swarm Optimization for Optimization of Photovoltaic Generators in Radial Distribution Systems Using Probabilistic Load Flow

This article shows that technical constraints must be considered in radial distribution networks, where voltage regulation is one of the primary problems in distributed generation photovoltaic systems. Loads and distributed generation production are modeled as random variables. Results prove that the proposed method can be applied for keeping voltages within desired limits at all load buses of a photovoltaic grid-connected system. To evaluate the performance of a photovoltaic system, this article has developed a probabilistic model that takes into account the random nature of solar irradiance and load. This work introduces a new method utilizing discrete particle swarm optimization and probabilistic radial load flow. Computer simulation reduction demonstrates better performance of the new probabilistic load flow in comparison to the Monte Carlo simulation. Acceptable solutions are reached in a smaller number of iterations. Therefore, convergence is rapidly attained, and computational cost is low enough for that required for Monte Carlo simulation.

Wind power optimal capacity allocation to remote areas taking into account transmission connection requirements

Wind power is site dependent and is by nature partially dispatchable. Furthermore, good wind sites are far from grid. Owing to these problems, and along with the existing limitations in the transmission networks, a comprehensive analysis over an extended time is needed to properly explore all potential wind sites for wind capacity allocation. This problem is computationally expensive and decomposition methods are required to break down this problem. Here Benders decomposition approach is used, which is a popular technique for solving large-scale problems, to decompose the original problem into a master and a subproblem. The master problem is a linear problem, which allocates wind capacity to each site and determines the transmission line capacity for connection to the grid. The subproblem is a mixed-integer problem and performs a year-long unit commitment accompanied with DC optimal load flow. The subproblem uses the solution of the master problem to form the appropriate cut, representing operation cost, for the next iteration of the master problem. This procedure is iterated until the optimal solution is found. The IEEE 24-bus test system is used to demonstrate the proposed method. Simulation results show that the maximum profit is gained when there is a trade-off between transmission cost and wind curtailment. It is shown that by using a proper wind capacity allocation, wind penetration into the system will be maximised.

A 2020 GB transmission network study using dispersed wind farm power output

A large amount of wind power generation capacity is expected to be installed in Great Britain by 2020. A considerable amount of this capacity will be located in Scotland. This will require reinforcement of power transmission capacity between Scotland and England. Analysis of the impact of a large amount of wind generation capacity on the electricity network requires modelling of wind power output. Due to the lack of available wind power output data a method for artificially generating wind power output from real wind speed data was developed. The technique is based on monthly wind speed averages used to generate Weibull distributions. Hourly wind power output time series over one year are generated for 18 onshore and offshore locations in Great Britain. Capacity factors, maxima, minima and hourly output variations, their means and standard deviations are calculated. A comparison of statistical parameters of the generated data with those of real wind power output shows that both have similar statistical properties. The geographically distributed wind power output data is used in conjunction with an optimal load flow model for analysing three network case studies. One case study uses a hypothesised 2020 Great Britain transmission network the other two cases enhance the network with an Eastern and Western HVDC line linking Scotland and England. The simulation results illustrate the effectiveness of both HVDC lines in reducing wind generation curtailments and operational costs.

HEURISTIC METHODE FOR OPTIMIZING POWER LOAD FLOW ANALYSIS IN ELECTRICAL POWER SYSTEM

The primary goal of a generic optimal power load flow problem Is minimizing total fuel costs of generating units in an electrical power system while maintaining the security of the system. This paper presents an algorithm for optimizing power load flow analysis through the application of Newton ’s method and attends to interchange power between the different power systems. Specifically, it will explore the implementation of data structure such as the binary tree in searching OPF variables (controls, states, constraints) in large power system. So the OPF solution is quickly converging. The primary goal of a generic OFF has been tested by simulation method for 6- bus system in Power World environment. The optimal power flow results is shown that total generation fuel cost in the interchange power case is less expensive than in no interchange power case as well as total transmission losses in the power system are smaller.

Locational Capacity Credit Evaluation

Boosted by U.K. governmental targets of securing 10% of electricity generation from renewable resources by 2010 and 20% by 2020 and widespread public support for renewable energy, distributed generators (DGs) are rapidly increasing in electrical power systems. Among the renewable DGs, wind energy is emerging as the popular choice due to its mature technology and low operation and maintenance costs. This paper utilizes the reliability aspects of electrical power systems to provide a probabilistic approach to determine the capacity credit (CC) of distributed generators. Monte Carlo simulations are employed to cater for the stochastic nature of the simulations and each trial is validated using the Newton-Raphson optimal load flow solution. Bernoulli trials are used to simulate the availability of network components. An algorithm to evaluate the capacity credit due to distributed generation (DG) connected in the network is shown. Hence, the amount of conventional generation which can be backed off from the bulk supply point (BSP) of the distribution network can be quantified. Wind energy production is known to depend on the wind regime experienced by the wind turbines, as well as the geographical landscape and the presence of wind obstacles, which in turn determines capacity credit. Having verified that adding a specific DG at each node does not violate any operating constraints, it was assumed that thermal constraints would not affect CC in this particular system. In a more in-depth study, it is shown in this paper that capacity credit also varies with the different voltage levels at which the wind turbine generators are connected and the loading level of the distribution network. Moreover, it is shown that CC does not vary with the base case reliability, but rather with wind penetration levels.

Improving the steady-state loading margin to voltage collapse in the North-West Control Area of the Mexican Power System

This paper reports the application of a static approach for assessing the steady-state loading margin to voltage collapse of the North-West Control Area (NWCA) of the Mexican Power System. The approach uses both optimal load flow (OLF) and conventional load flow (LF) solutions, and singular value decomposition of the load flow Jacobian matrix ( J). Additionally, the approach allows to determine suitable locations for corrective actions such as, the addition of new equipment or load shedding. The results shows that the combination of OLF and LF resulted in a steady-state loading margin to voltage collapse of the NWCA 7.2% higher than the case when only conventional load flow solutions were considered.

Multiobjective optimal load flow based on ideal distance minimization in 3D space

In this paper, three objectives of Multiobjective Optimal Load Flow (MOLF) problem — cost of generation, system transmission loss and pollution — are considered. The MOLF problem is formulated as a multiobjective optimization problem using weighting method and a number of noninferior solutions are generated in 3D space. The optimal power system operation is attained by Ideal Distance Minimization method. This method employs the concept of an ‘Ideal Point’ (IP) to scalarize the problems having multiple objectives and it minimizes the Euclidean distance between IP and the set of noninferior solutions. This method has been applied to three IEEE standard systems.

Fuzzy multi-objective decisions in the problem of optimal distribution load flow

Abstract This paper presents an iterative method for the calculation of load flows and decisions making in multi-objective procedure for optimal solution in distribution systems in the presence of uncertain and/or low precision input data. Uncertainty of node active and reactive loads and source–node voltage are given through the linguistic description transformed to trapezoidal membership functions fuzzy variables. System topology and element parameters, as well as, locations and capacities of switched-on capacitors are assumed to be certain (crisp) variables. The same assumption is applied for tap-change positions of transformers. Calculations of load flows are performed by using rules of interval arithmetic. For the determination of optimal defuzzified solution based on minimum active power losses, the minimum operator procedure is applied. Constraints of voltage profile are ‘soft’ and specified through corresponding linguistic descriptions, translated to the form of the membership functions. The methodology for the multi-objective decisions is developed, by using the calculation of the satisfactory degree with achieved solutions with or without weighting factors (thresholds), set to particular criteria. Finally, for verification of fuzzy optimal distribution load flow model, a real-life three-voltage level distribution system, is used.

Optimal load flow using sequential unconstrained minimization technique (SUMT) method under power transmission losses minimization

Abstract The paper presents a new approach for solving the optimal power flow problem. The problem is solved by a sequential unconstrained minimization technique (SUMT) algorithm which was developed by Fiacco and McCormick. Firstly, we compute real power transmission losses and maintain a constant optimal power flow calculation procedure. Secondly, we propose a new approach for total real power transmission losses, as a linear function of generated real power; its effect and influence on the minimum cost of fuel and the result of real power transmission losses. In the second case, the real power transmission losses are 28% lower then the first case. The proposed approach has been applied for the first time to the 14 bus test system and the results are judged satisfactory.

New sequential AC‐DC load‐flow approach utilizing optimization techniques

AbstractThis paper presents a novel method for solving the sequential load‐flow problem of a general multiterminal DC network in an integrated AC‐DC system. The proposed method utilizes optimization technique both to prevent the violation of variables constraints and to minimize the real power losses and hourly fuel cost of AC‐DC systems. This paper is also the first study in literature using steepest descent algorithm (SDA) for AC‐DC optimal load flow. Instead of SDA, any optimization technique can be used with the proposed AC‐DC load‐flow algorithm.

Optimal weight assessment based on a range of objectives in a multiobjective optimal load flow study

In a multiobjective optimal load flow study (MOLF) two objectives (cost of generation and transmission losses) have been considered for minimisation. A weighting method has been used to formulate the problem. An attempt is made to obtain the relation between the range of each objective, i.e. cost of generation and transmission losses, and the weight associated with each of them. If the range of an objective function is large, a small weight has to be associated with it. If the decision makers follow this relation, then appropriate weights will be elicited. The ‘optimal weight’ is derived on the basis of the maximum range of each objective function. If the ‘optimal weight’ is attached to the multiobjective function consisting of cost of generation and transmission losses, the target point is achieved in a single step, thereby saving much computational effort.

Dynamic hydro-thermal economic dispatch with water availability constraints and variable water head

Operation of a system having both hydro and thermal plants is quite complex as hydro plants have negligible operating cost, but are required to operate under constraints of water available for hydro generation in a given period of time. The problem thus belongs to the realm of dynamic optimization. The earliest work on optimal load flow for hydro-thermal systems was probably due to Ramamoorthy [1]. Head variation was neglected and nonlinear programming techniques were employed. In this paper, the problem of minimizing the operating cost of a hydro-thermal system can be viewed as one of minimizing the fuel cost of thermal plants under the constraint of water availability (storage and inflow) and variable water head for hydro generation over a given period of operation. Optimization will be carried out with thermal power generation and water discharge rate as control variables, with transmission losses accounted for by the exact network model, namely the load flow equations. The problem is solved here using nonlinear programming technique in conjunction with successive approximation method. The method of solution has been accelerated to reduce the computational time burden using the first order gradient method. Because of the large-scale nature of the problem, special attention is paid to finding convergence characteristics and realistic initial guess estimates for the algorithm.

Multicriterial Load Flow Optimization and Conirol Action's Selection in High Voltage Grid Systems

Both technically and economically favorable operating states of voltage and reactive power are of interest from the point of view of efficient and reliable operation of high voltage grid systems. A special multicriterial optimization method is being offered which compromises various target functions. It facilitates a situation-dependent and weighted combination of the target functions and evaluates the influence of potential control variables on optimization targets basing on sensitivity coefficients. Furthermore the sensitivities are appropriate to preselect the effective actuating variables of the optimization run in advance. This enables in combination with a post filtering of small changes of actuating variables an essential reduction of the. control actions over the day without a substantial loss of performance.