The future of development and design is impossible without study of POWER FLOW(PF), exigency the system outcomes load growth, necessity add generators, transformers and POWER lines in POWER system. The urgency for OPTIMAL POWER FLOW ((OPF)) studies, in addition to the items listed for the PF and in order to achieve the objective functions. In this paper has been used cost of generator fuel, active POWER losses network and system loadability index, so artificial neural network used to compare two propagation algorithms of this type of network and define the model (OPF) analysis is carried out. The performances of the two algorithms are analyzed and compared using the model assessment index and MGN tests. Statistical method of Bootstrap has been used on achieve the best performance to improve (OPF) estimates. In order to reduce steps with less than 1%, for evaluate and improve the (OPF) estimation with single-objective optimization functions of the Bayesian and Perceptron neural networks have been studied in IEEE 30 bus test system. The results show the effective role of bootstrapped Bayesian neural network in terms of performance, using MATLAB software.

In this paper, a novel risk-based, two-objective (technical and economical) OPTIMAL reactive POWER dispatch method in a wind-integrated POWER system is proposed which is more consistent with operational criteria.  The technical objective includes the minimization of the new voltage instability risk index. The economical objective includes cost minimization of reactive POWER generation and active POWER loss. The proposed voltage instability risk employs a hybrid possibilistic (Delphi-Fuzzy)-probabilistic approach that takes into consideration the operator’s experience, the wind speed and demand forecast uncertainties when quantifying the risk index. The decision variables are the reactive POWER resources of the system. To solve the problem, the modified multi-objective particle swarm optimization algorithm with sine and cosine acceleration coefficients is utilized. The method is implemented on the modified IEEE 30-bus system. The proposed method is compared with those in the previously published literature, and the results confirm that the proposed risk index is better at estimating the voltage instability risk of the system, especially in cases with severe impact and low probability. In addition, according to the simulation results compared to typical security-based planning, the proposed risk-based planning may increase the security and economy of the system due to better utilization of system resources.

This paper addresses a new concept for optimizing the POWER FLOW in a multilateral open access POWER system. Using a full AC POWER FLOW in this optimization permits the system operator to determine the optimum feasible system operating point based on predefined transactions and contracts Introduction of fuzzy constraints to contracts for difference will increase the system flexibility to face with changes in operating conditions. The proposed approach is tested on IEEE RTS 24-bus network with satisfactory results.

The problem of OPTIMAL economic operation of hydrothermal electric POWER systems is solved using POWERful continuation method. While in conventional approach, fixed generation voltages are used to avoid convergence problems, in the proposed algorithm, they are treated as variables so that better solutions can be obtained. The algorithm is tested for a typical 5-bus and 17-bus New Zealand networks. Its capabilities and promising results are assessed.

In this paper two POWER elements for POWER controller in transmission line are presented: Variable Frequency Transformer (VFT) and Rotary POWER FLOW Controller (RPFC). In addition, here a new OPTIMAL POWER FLOW ((OPF)) with these elements is presented. In this paper, it has been made use of the Impedance and Admittance nonsymmetrical matrix and the matrix of loss or coefficient B are calculated in a new method. It has also been indicated that the system is not optimized if OPTIMAL POWER FLOW is not considered in locating and POWER of FLOW controller in line. The proposed method was applied to a 26-bus and 6-generator system and the results were satisfactory.

In this paper, two new computationally efficient improved stochastic algorithms for solving multi-area DC OPTIMAL POWER FLOW (DC-(OPF)) in interconnected POWER systems have been presented. These algorithms are based on the combined application of Fuzzy Logic strategy incorporated in both Evolutionary Programming (EP) and Tabu Search (TS) algorithms, hence termed as Fuzzy Mutated Evolutionary Programming (FMEP) and Fuzzy Guided Tabu Search (FGTS). Multi-area DC-(OPF) calculations determine optimum generation schedule, OPTIMAL control variables and system quantities of each area with due consideration of generation and transmission system limitations for efficient POWER system operation. The popularity of EP and TS algorithms are due to their significant property of dealing with the optimization problems without any restrictions on the structure or type of the function to be optimized and due to the ease of computation. The proposed methods are tested on single area, two area and four area IEEE 30-bus interconnected systems. The OPTIMAL solutions obtained using SLP (Successive Linear Programming), EP, TS, FMEP and FGTS are compared and analyzed. The analysis reveals that the proposed algorithms are relatively simple, efficient, reliable and suitable for real-time applications. And these algorithms can provide accurate solution with fast convergence and have the potential to be applied to other POWER engineering problems.

The recent state of electrical system comprises the conventional generating units along with the sources of renewable energy. The suggested article recommends a method for the solution of single and multi-objective OPTIMAL POWER FLOW, incorporating wind energy with traditional coal-based generating stations. In this article, the two thermal POWER plants are replaced with the wind POWER plants. The techno-economic analysis are done with this state of electrical system. In proposed work, Weibull probability distribution functions is used for calculating wind POWER output. A non-dominated sorting based multi-objective moth flame optimization technique is used for the optimization issue. The fuzzy decision-making approach is applied for extracting the best compromise solution. The results are authenticated though modified IEEE-30 bus test system, which is combined with wind and thermal generating plants.

In restructured POWER systems, Independent System Operator (ISO) uses a lot of tools to minimize the costs while delivering the POWER to consumers in a reliable and stable state. To minimize the costs, ISO uses security-constrained unit commitment (SCUC), and schedules unit reserves for reliability point of view. For stability point of view, ISO implements OPTIMAL POWER FLOW ((OPF)) to secure the bus voltage margins, and to reduce the losses. In this paper, an algorithm is proposed to include this OPTIMAL generation scheduling with transmission lines parameters, and a case study is implemented to verify the proposed algorithm.

Transmission expansion planning (TEP) is one of the most important parts of expansion planning in POWER systems. Competition in these systems has resulted in essential changes in TEP models and criteria. While methods introduced so far are essentially based on dc load FLOW, the proposed method utilizes the ac OPTIMAL POWER FLOW ((OPF)) in order to model the real world condition and obtaining OPTIMAL plans. Furthermore, in order to model the operation and investment costs, transmission tariffs are used. Investigation on 8-bus system confirms the advantages of the proposed method as compared with previously presented approaches.