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.

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.

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.

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.

This paper objective presents static synchronous series compensation FACTS device with biogeography based optimization (BBO) to deal for obtaining worthwhile POWER FLOW control. The biogeography based optimization method is utilized to find the OPTIMAL fitted child sets by surviving parents with the help of migration and mutation Jaipur process. The present BBO technique from the evolutionary strategy with static synchronous series compensator provides improved outcomes in comparison to other optimization methods. The simulation outcomes illustrate that the proposed BBO algorithm is efficacious, secure and correct to search the optimized values with SSSC based FACTS devices. The proposed method is considering the solution quality an optimistic substitute method for extricating the OPF problems. The simplification and effectiveness of this method are validated on the IEEE 57 bus and 75 bus Systems. In this paper, from the outcome results, it is clearly shown that the proposed technique execution can be properly and effectively applied to the OPTIMAL position of multiple OPF problems. i.e. BBO based algorithm with SSSC FACTS device is found better results when compared to without SSSC device in all aspects.

This paper presents a fuzzy interactive approach to find the OPTIMAL location of OPTIMAL Unified POWER FLOW Controller (OUPFC) device as a multi-objective optimization problem. The problem formulation is based on OPTIMAL POWER FLOW (OPF) problem while the metric function and weighting method are added to ensure the collaboration among objective functions. The objective functions are the total fuel cost, POWER losses, and system loadability with and without the minimum cost of OUPFC installation. The proposed algorithm is implemented on IEEE 14- and 118-bus systems. The solution procedure uses nonlinear programming with discontinuous derivatives (DNLP) to solve the OPTIMAL location and settings of OUPFC device to enable POWER system dispatcher to improve the POWER system operation. The optimization problem is modeled in General Algebraic Modelling System (GAMS) software using CONOPT solver. Furthermore, the results obtained by OUPFC are compared with those of the Unified POWER FLOW Controller (UPFC) device. The OUPFC is outperformed by UPFC in the POWER system operation from the economic and technical point of view.

The measure of Reactive POWER optimization of main POWER network mainly considers on-load tap changer, the OPTIMAL capacity of the capacitor, the voltage of generator under the steady load. In This paper, a multi-objective optimization methodology to the OPTIMAL Reactive POWER FLOW (ORPF) problem is proposed in which the e-constrained approach is implemented for the Multi-objective Mathematical Programming (MMP) formulation. The objectives functions of the proposed model include optimize the total fuel cost, the active POWER losses, and the system load ability. Since the control variables include discrete variables (var sources and transformer tap ratios), the ORPF is inherently a mixed-integer nonlinear programming (MINLP) problem. The optimum tap settings of transformers are directly determined in terms of the admittance matrix of the network since the admittance matrix is constructed in the optimization framework as additional equality constraints. To show the effectiveness of proposed method the results are compared with single-objective, two-objectives and three-objectives. Finally, the method has been implemented in GAMS and solved using DICOPT solver to obtain OPTIMAL solutions. In this research, for selection of the best compromising answer among the Pareto OPTIMAL solutions has been designed a fuzzy decision-maker tool. The algorithm is tested on standard IEEE 14- bus test system. Simulation results show that the proposed algorithm is able to control reactive POWER FLOW effectively and optimize the selected objective functions.

Parallel Hybrid Electric Vehicle POWERtrain (PHEV), combining an electric motor with an auxiliary POWER unit, improves vehicle performance and fuel economy, reducing the effects of private cars on air quality in cities. These advantages can be enhanced by using a dedicated control strategy to identify the OPTIMAL POWER FLOW distribution at each instant of time in the main POWERdrive sources as a function of the state of the POWERdrive components and the actual driving conditions. In this connection the literature analysis has evidenced as the research efforts in the field of PHEV OPTIMAL POWER FLOW management should be oriented not only to develop precise and robust control strategies that can improve the vehicle performances, but also to lower the required computational resources making the solution strategy suitable with the vehicle dynamics and allowing, moreover, a cost effective hardware implementation. To develop this complex activity, fuzzy logic (FL) was used. As demonstrated by the simulation studies developed, FL enables the OPTIMAL POWER FLOW management problem to be solved by handling its intrinsic non-linearity using rules, membership functions, and the inference process. This results in improved performance, simpler implementation, and reduced design costs compared with rigorous mathematics based approaches.

This paper proposes an OPTIMAL POWER FLOW (OPF) algorithm by Direct Load Control (DLC) programs to optimize the operational cost of smart grids considering various scenarios based on different constraints. The cost function includes active POWER production cost of available POWER sources and a novel flexible load curtailment cost associated with DLC programs. The load curtailment cost is based on a virtual generator for each load (which participates in DLC program). To implement the load curtailment in the objective function, we consider incentive payments for participants and a load shedding priority list in some events. The proposed OPF methodology is applied to IEEE 14, 30-bus, and 13-node industrial POWER systems as three examples of the smart grids, respectively. The numerical results of the proposed algorithm are compared with the results obtained by applying MATPOWER to the nominal case by using the DLC programs. It is shown that the suggested approach converges to a better quality solution in an acceptable computation time.