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Item type:Publication, A co-optimization model of natural gas supply and electric power systems(2019-01-01)Nakawiro, WorawatIn Thailand, natural gas has been the primary source of fuel for power generation for the past few decades due to availability of indigenous resources. With continuous load growth and near depletion of domestic natural gas supply, renewable energy will play an increasing role in power industry in a close future. To achieve that, energy storage would become the key enabler. Therefore, this paper proposes a co-optimization steady-state model of a -coupled system of gas supply network and electric power system with integration of an energy storage device namely power-to-gas. The IEEE-14 bus power system coupled with the 20-node and 24 pipeline natural gas system is used to verify effectiveness of the proposed method through computer simulation. The results show the capability in maintaining the system variables within the statutory security limits and reducing power losses. Moreover, the proposed method has another feature that can optimally curtail loads of the two systems when experiencing stressful conditions. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, A Comparative Study on Constraint Handling for Solving Economic Dispatch by Evolutionary Algorithms(2018-07-02)Nakawiro, WorawatEvolutionary algorithm (EA) has been well accepted as a suitable tool for solving non-convex economic dispatch problems. However the major challenge is how to handle both equality and inequality constraints properly. The penalized fitness is commonly used to evaluate quality of candidate solutions. Moreover searching for feasible space is very difficult for a problem with large number of variables and number of constraints. This paper proposes a general framework which can be applied to any EA for handling constraints in ED problems. Four EAs namely differential evolution (DE), genetic algorithm (GA), particle swarm optimization (PSO) and harmony search (HS) were selected to demonstrate effectiveness in solving a non-convex ED problem of a 15 unit power system. Simulation results reveal that with the proposed constraint handling all optimization algorithms converge to the identical result based on 20 independent trials. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Voltage Stability Enhancement by Computational Intelligence Methods(2018-01-01)Nakawiro, WorawatThis chapter discusses the concepts of optimal power flow (OPF) and associated computational intelligence (CI) methods, namely artificial neural network (ANN) and ant colony optimisation (ACO). It presents an application of CI methods to solve voltage stability constrained OPF (VSCOPF) for preventive and corrective control actions. The chapter also presents two examples that apply CI techniques to determine optimal preventive and corrective control measures for enhancing voltage stability of the IEEE 30-bus test system. ACO is used to determine the optimal control action that will guarantee minimum voltage stability margin (VSM). The change in VSM due to load curtailment at effective locations is approximated by the sensitivity method in order to save computing time. Simulation results show the capability of the proposed method to improve VSM in normal operation and to restore stable operation in critical situations. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Optimal tuning of power system stabilizers by probability method(2016-09-06); Nakawiro, WorawatIt is well known that the power system stabilizer (PSS) which is designed at one operating point cannot guarantee the stabilizing effect of PSS over a wide range of operating conditions. To achieve the PSS with high stabilizing performance against various conditions, this paper focuses on the new parameters optimization of PSS by the probability method. The PSS structure is the practical 2<sup>nd</sup>-order lead-lag compensator with the local input signal. The optimal tuning of PSS parameters is carried out under random operating conditions generated by Monte Carlo method so that the probability of the occurrence of desired damping ratio for target oscillation modes are maximized. The particle swarm optimization is used to solve for optimal PSS parameters. Study results in the IEEE-39 bus New England system confirm that the proposed PSS yields better damping effect than the conventional PSS under various operating conditions and severe faults. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, A Simulation Study of Inverter Air Conditioner Controlled to Supply Reactive Power(2016-01-01) - Some of the metrics are blocked by yourconsent settings
Item type:Publication, A combined GA and IPM approach for unit commitment problem(2015-01-30)Nakawiro, WorawatUnit commitment involves determination of a large number of variables (both discrete and continuous). The well-known curse of dimensionality is very pronounced when dealing with large-scale power systems. This paper presents an approach combined between genetic algorithm (GA) and interior point method (IPM). GA is used to determine the on/off status of generators (discrete variables) whereby IPM finds the optimal power dispatch of the committed generators. Simulations were carried out for the case with 10, 30, 60 and 100 units. The results show that the proposed method helps improve quality of the final result and also reduce computing time. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Predictive voltage control for a distribution network with renewable energy sources(2014-10-15)Nakawiro, WorawatThis paper presents a predictive voltage control strategy for power distribution systems with renewable energy sources. A mixed-integer nonlinear programming problem was formulated and solved by genetic algorithm (GA). The on-load tap changer transformer and reactive power set point of wind and solar farms are determined. The day-ahead control horizon is considered and optimization is carried out at every hour. The wind and solar power are predicted by artificial neural network. The proposed methodology is implemented on a test distribution network to verify its effectiveness. It is demonstrated that the proposed method is capable of maintaining the system voltage close to the nominal as compared to the case of fixed control set-points. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Robust power oscillation damper design for DFIG-based wind turbine(2013-09-02); ; Nakawiro, WorawatA new robust power oscillation damper (POD) design for a doubly fed induction generator based- wind turbine is proposed in this paper. The POD structure is specified by the second-order lead/lag compensator with single input signal. The parameters optimization of POD is formulated based on a mixed H<inf>2</inf>/H<inf>∞</inf> control using linear matrix inequalities. The POD parameters are optimized by the firefly algorithm so that the damping performance against system disturbances and the robustness under system uncertainties are satisfied. Simulation results in a single machine infinite bus confirm the superior robustness of the proposed POD over the conventional POD. © 2013 IEEE.4 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Electrical modeling and simulation of industrial power system with Matlab/Simulink program(2013-07-12)