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ABSTRACT: Economic load dispatch (ELD) performs an important part in the economic operation of power system. The ELD problem is considered as a non-linear constrained optimisation problem. The problem becomes non-convex and non-smooth when the generators' prohibited zones and valve-point effect are considered. The purpose of this work is to present a solution strategy to solve ELD problem in an efficient way while considering several aspects of ELD. The strategy employs a hybrid mechanism involving a quantum mechanics inspired particle swarm optimisation (PSO). The conventional PSO is modified by integrating quantum mechanics theory that redefines the particles positions and velocities in more diverse manner and therefore explores more search space. The PSO is further upgraded from a single population-based to a multi-population one. Such feature of the method delivers a fine balance between the local and global searching abilities. The simulations are carried by considering several cases of thermal units by varying different combinations of system configurations such as with/without valve-point effect, with/without network loss and for one or several hours of load demand. The results are quite promising and effective compared with several benchmark methods.
IET Generation Transmission & Distribution 11/2011; · 1.20 Impact Factor
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ABSTRACT: This article presents a strategy to solve thermal unit commitment (UC) integrated with an equivalent solar battery system using Fuzzy based Quantum inspired Evolutionary Algorithm (FQEA). As a renewable power source, solar power is injected stochastically with the model. To handle the uncertainty and intermittency involved while integrating solar power and load forecasting, the trivial crisp problem formulations are modified by fuzzification. An evolutionary algorithm based on the concept and principle of quantum computation is applied to solve the UC problem. The conventional Quantum Evolutionary Algorithm (QEA) is advanced by using several operators such as binary differential operator, mutation and crossover along with trivial rotation operator with a re-defined rotational angle look-up table. The QEA is further modified by introducing multi-population based scheme. The fitness function is formulated by combining the objective function, penalty function and the aggregated fuzzy membership function. The proposed FQEA is applied to UC problem in different scaled power systems up to 100 units. Provided simulation results will show the effectiveness of FQEA.
Fuzzy Systems (FUZZ), 2011 IEEE International Conference on; 07/2011
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ABSTRACT: In order to solve problems of global warming and depletion of energy resource, renewable energy systems such as wind generation is getting attention. In this optimal operation method, we introduce forecasted output power data of wind turbine generator which is calculated from Grid Point Value (GPV) data of wind speed. And we are considering forecasted error in GPV data. The optimization target is smoothed the output power fluctuation of a wind farm (WF) and is aimed to obtain more benefit for electric power selling. The optimization method uses tabu search (TS).
Power Electronics and ECCE Asia (ICPE & ECCE), 2011 IEEE 8th International Conference on; 07/2011
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ABSTRACT: A photovoltaic (PV) system's output power fluctuates according to the weather conditions. Fluctuating PV power causes frequency deviations in the power utilities when the penetration is large. Usually, an energy storage system (ESS) is used to smooth the PV output power fluctuations and then the smoothed power is supplied to the utility. In this paper, a simple fuzzy-based frequency-control method is proposed for the PV generator in a PV-diesel hybrid system without the smoothing of PV output power fluctuations. By means of the proposed method, output power control of a PV generator considering the conditions of power utilities and the maximizing of energy capture are achieved. Here, fuzzy control is used to generate the PV output power command. This fuzzy control has average insolation, change of insolation, and frequency deviation as inputs. The proposed method is compared with a maximum power point tracking control-based method and with an ESS-based conventional control method. The numerical simulation results show that the proposed method is effective in providing frequency control and also delivers power near the maximum PV power level.
IEEE Transactions on Energy Conversion 07/2011; · 2.27 Impact Factor
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ABSTRACT: This paper presents an output power smoothing method by a simple coordinated control of DC-link voltage and pitch angle of a wind energy conversion system (WECS) with a permanent magnet synchronous generator (PMSG). The WECS adopts an AC-DC-AC converter system with voltage-source converters (VSC). The DC-link voltage command is determined according to output power fluctuations of the PMSG. The output power fluctuationsin low- and high-frequency domains are smoothed by the pitch angle control of the WECS, and the DC-link voltage control, respectively. By using the proposed method, the wind turbine blade stress is mitigated as the pitch action in high-frequency domain is reduced. In addition, the DC-link capacitor size is reduced without the charge/discharge action in low-frequency domain. A chopper circuit is used in the DC-link circuit for stable operation of the WECS under-line fault. Effectiveness of the proposed method is verified by the numerical simulations.
IEEE Transactions on Energy Conversion 07/2011; · 2.27 Impact Factor
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ABSTRACT: Stand-alone ac power supply system such as isolated islands is subject to large frequency and voltage fluctuations caused by power deviations of wind turbine generator and load demand. The autonomous decentralised frequency control system of parallel operated decentralised generators based on droop characteristic is presented in this study. The conventional droop control methods proposed in past researches show slow and oscillating dynamic responses. Moreover, the conventional droop control is affected by measurement noise when the fast controllability of the system is emphasised. This study proposes the improved droop control system for load sharing of multi-operated decentralised generators by applying H<sub>∞</sub> control theory, improving transient response of droop control and robustness against measurement noise and parameter variations. Simulation results validate the effectiveness of the proposed control system.
IET Renewable Power Generation 04/2011; · 1.74 Impact Factor
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ABSTRACT: The control of wind-energy conversion systems (WECSs) is still a challenging task for design engineers. Despite being ubiquitous in the wind industry, the performance of classical proportional-integral-derivative controllers is not ideal, and they require additional notch filters to handle turbine nonlinearity. This has triggered interest toward advanced control concepts that are multiobjective and multivariable. With optimality, feedback, and robustness being prerequisites in developing control policies that guarantee high-integrity and fault-tolerant control systems, H <sub>∞</sub> control theory has become a standard design method of choice over the past two decades and is gaining prominence in industrial (and WECS) control applications. Based on the linear matrix inequality approach, this paper presents a comprehensive and systematic way of applying the H <sub>∞</sub> control design algorithm for automatically gain-scheduling the linear-parameter-varying turbine plant along parameter trajectories. Control seeks to regulate both power and voltage via a synthesis of two controllers, namely, pitch and generator torque, respectively, for a megawatt-class WECS. Digital simulations executed in a MATLAB/Simulink environment ascertain that the control paradigm meets the objectives of optimizing power conversion throughout the operating envelope, as well as eliminating power oscillations through system damping.
IEEE Transactions on Industrial Electronics 02/2011; · 5.16 Impact Factor
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ABSTRACT: Simulation has become the most important technique used today for evaluation of engineering solutions, and modeling plays a crucial part in the design of intelligent control paradigms for complex dynamic structures. For the analysis of a megawatt-class wind-energy conversion system (WECS), this research adopts the H <sub>∞</sub> control theory in designing an advanced control paradigm that accomplishes the dual purpose of energy capture optimization, as well as power train cyclic load alleviation by mitigating against wind-speed fluctuations. This work is presented in two parts: The first details the modeling of the subsystems of WECS and introduces the multiobjective H <sub>∞</sub> control concept, and the second deals with the implementation of the control paradigm. Presented herein is a modeling approach of individual subsystems as a basis for devising the unified control strategy for a 2-MW grid-connected pitch-regulated variable-speed WECS that incorporates a doubly fed induction generator. The credibility of the archetype, to establish the argument that the models produce sound insights and comparable results to data from the real system, is ascertained via validation.
IEEE Transactions on Industrial Electronics 02/2011; · 5.16 Impact Factor
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ABSTRACT: Recently, renewable energy such as wind turbine generators and photovoltaic systems are introduced as distributed generators (DGs). Connection of a large amount of DG causes voltage deviation beyond the statutory range in distribution systems. Reactive power control of inverters interfaced with DGs is one of the solutions against this problem. Additionally, reactive power control has a possibility to contribute to the reduction of distribution loss. In this study, the authors propose a voltage control method in distribution systems by reactive power control of inverters interfaced with DGs. The proposed method has been developed in order to reduce distribution loss and voltage regulation into statutory range without any telecommunication. In the proposed method, each interfaced inverter controls reactive power based on voltage control reference, which is calculated from self-information. The calculation rule of control reference has been developed using optimal data which consist of relations between randomly given inputs and corresponding optimal outputs, which are calculated by an optimisation technique. Simulations are conducted to show the effectiveness of the proposed method.
IET Generation Transmission & Distribution 12/2010; · 1.20 Impact Factor
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ABSTRACT: From the perspective of global warming suppression and depletion of energy resources, renewable energy such as wind generation (WG) and photovoltaic generation (PV) are getting attention in distribution systems. Additionally, all electrification apartment house or residence such as DC smart-house have increase in recent years. However, due to fluctuating power from renewable energy sources and loads, supply-demand balancing fluctuation of power system become problematic. Therefore, smart-grid has become very popular in worldwide. This paper presents a methodology for optimal operation of a smart grid to minimize interconnection point power flow fluctuation. To achieve the proposed optimal operation, we use distributed controllable loads such as battery and heat pump. By minimizing the interconnection point power flow fluctuation, it is possible to reduce the maximum electric power consumption and the electric cost. This system consists of photovoltaics generator, heat pump, battery, solar corrector, and load. In order to verify the effectiveness of the proposed system, MATLAB<sup>®</sup> is used in simulations.
IPEC, 2010 Conference Proceedings; 11/2010
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ABSTRACT: System security in the generation market is one of the important aspects in power system operation under deregulated environment. It becomes more crucial when thermal power system is integrated with wind system. This paper presents an approach to determine the security constrained unit commitment (SCUC) for thermal units integrated with wind power system. A Lagrangian relaxation based algorithm with Particle Swarm Optimization (PSO) has been applied to solve this model. The method initially decomposes the load demand hours into several groups based on their homogeneity. Then instead of solving hourly SCUC, this method solves SCUC for each group. Lagrangian formulations are applied to relax the constraints with objective function using multipliers. PSO is then applied to solve UC. Since security constraints including transmission flow and voltage limits are considered, an iterative sub problem is introduced to minimize the security constraint violation using a simplified heuristic method. The Lagraingian multipliers are updated using gradient method. The process will continue until the difference between the primal and dual problem comes to a tolerable limit. To compromise the uncertainty of wind power, it is injected with the provided supply using a Gaussian distribution stochastic function. The simulation provides some analysis of the proposed method with two test systems (IEEE 6-bus and and 31-bus).
IPEC, 2010 Conference Proceedings; 11/2010
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ABSTRACT: Recently, operational cost for diesel generator such as fossil cost, transport cost, and storage cost are expensive in isolated island. Consequently, renewable energy generation is advanced in the world. Furthermore, all-electric house and electric vehicle carrying a storage battery is increasing. Controllable load in the grid can be installed using all-electric house and electric vehicle carrying a storage battery. In this paper, we propose an optimization approach to determine operational planning of wind generator, photovoltaic facility, diesel generator, and battery energy storage-system. In this optimization method, forecasted output power data of wind generator, photovoltaic facility, and controllable load are assumed to be available for all day which is utilized in operational planning of wind generator, photovoltaic facility, diesel generator, and battery energy storage-system. As the optimization method, genetic algorithm and tabu search are used in this paper.
Electrical Machines and Systems (ICEMS), 2010 International Conference on; 11/2010
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ABSTRACT: Effective utilization of renewable energies such as wind energy is expected in place of the fossil fuel. The speed of wind is not remained constant and windmill output power is proportional to the cube of wind speed. In order to wind speed deviation, the output power of wind turbine generators (WTGs) is fluctuated. To reduce the fluctuation, different methods are already proposed such as energy storage devices, electric double layer capacitors, flywheels, and so on. These methods are effective but they require a significant extra cost to the system. This paper represents a method to generate smooth output power of a large WTG by using the inertia of WTG system. The inertia behaves like an inductor in an electrical circuit. It stores energy during acceleration and releases energy during deceleration. It can be utilized to generate smooth output power of a WTG. The additional energy storage system is not required. Additionally, the proposed method can be changed into the Maximum Power Point Tracking (MPPT) control method by adjusting an average time. The effectiveness of the proposed output power smoothing control is compared with MPPT control method and verified by using the MATLAB SEVIULINK environment.
Electrical Machines and Systems (ICEMS), 2010 International Conference on; 11/2010
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ABSTRACT: Recently, smart grids are attracting attention. Already, a smart grid based on an AC grid is proposed. However, no study on research is presented or published on a smart grid based on a dc grid. This paper presents an ac/dc hybrid smart power system. The proposed system has advantages of both dc and ac grids. The proposed power system consists of a wind generator and several controllable loads. The controllable loads have different capacities. Therefore, by applying power consumption control with the droop characteristic, the dc bus voltage is maintained within the acceptable range. As controllable loads, electric water heater and electric vehicle are assumed. Effectiveness of the proposed method is verified by numerical simulation results.
IEEE Transactions on Smart Grid 10/2010;
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ABSTRACT: Electricity price forecasting is becoming increasingly relevant to power producers and consumers in the new competitive electric power markets, when planning bidding strategies in order to maximize their benefits and utilities, respectively. This paper proposed a method to predict hourly electricity prices for next-day electricity markets by combination methodology of ARIMA and ANN models. The proposed method is examined on the Australian National Electricity Market (NEM), New South Wales regional in year 2006. Comparison of forecasting performance with the proposed ARIMA, ANN and combination (ARIMA-ANN) models are presented. Empirical results indicate that an ARIMA-ANN model can improve the price forecasting accuracy.
Industrial Electronics and Applications (ICIEA), 2010 the 5th IEEE Conference on; 07/2010
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ABSTRACT: In this study, a simple coordinated control method based on minimal-order observer is proposed for multiple photovoltaic (PV) systems. Here, output power command is generated in two steps: central and local. In the central step, a minimal-order observer estimates load power. Then, load variation index is calculated by subtracting the average of estimated load power from the instantaneous estimated load power. From the available maximum PV power, base PV power is produced by using a low-pass filter and is added with the load variation index to generate the central PV output power command. In the local step, a simple coordination is maintained between the central power command and the local power commands. The proposed method is compared with the method where maximum power point tracking control is used for each of the PV systems. Simulation results show that the proposed method is capable of reducing the frequency deviations of the power utility and also delivers power near maximum PV power.
IET Renewable Power Generation 04/2010; · 1.74 Impact Factor
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ABSTRACT: In the framework of competitive electricity markets, power producers and consumers need accurate price forecasting tools. Price forecasts embody crucial information for producers and consumers when planning bidding strategies in order to maximize their benefits and utilities, respectively. The choice of the forecasting model becomes the important influence factor on how to improve price forecasting accuracy. This paper provides a hybrid methodology that combines both autoregressive integrated moving average (ARIMA) and artificial neural network (ANN) models for predicting short-term electricity prices. This method is examined by using the data of Australian national electricity market, New South Wales, in the year 2006. Comparison of forecasting performance with the proposed ARIMA, ANN, and hybrid models are presented. Empirical results indicate that a hybrid ARIMA-ANN model can improve the price forecasting accuracy.
IEEE Transactions on Power Systems 03/2010; · 2.68 Impact Factor
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ABSTRACT: Wind turbines have become the most cost-effective renewable energy systems available today and are now completely competitive with essentially all conventional generation systems. However, wind stochasticity results in fluctuations in output power as well as undesirable dynamic loading of the drive train during high turbulence. A model-based predictive control strategy for the field-oriented control of a doubly fed induction generator is presented. The control region is defined over two wind profiles: average wind speeds below and above equipment rating, subject to assigned constraints of the maximum allowable system frequency fluctuations and the power limit of the wind generating system. To meet the control objectives of maximising energy capture and alleviation of drive train fatigue loads, each of the WGS component blocks is modelled separately so as to explore the associated trade-offs. Simulations, carried out under a Matlab<sup>®</sup> environment, serve to verify that the proposed paradigm performs better than the classical linear proportional-integral controller in achieving the regulation of torsional dynamics while maintaining optimal operation.
IET Renewable Power Generation 02/2010; · 1.74 Impact Factor
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ABSTRACT: With the increasing trend of connecting high penetrations of wind energy conversion systems (WECSs) to the transmission networks comes the challenge of updating the grid code for the connection of megawatt-class wind turbines. Starting with each WECS entity in the wind farm, the specifications would require the ability to complement some of the power system control services-voltage and frequency control-currently carried out by conventional synchronous generation. This paper investigates output power stability of a WECS in a highly fluctuating wind environment. Based on a performability model, a control strategy is devised for maximizing energy conversion in low to medium winds, and maintaining rated output in above rated winds while keeping torsional torque fluctuations to a minimum. Control is exercised via collective blade pitch control as well as generator torque control. The fundamental philosophy behind the proposed control strategy for the wind turbine coupled to an asynchronous doubly fed induction generator is general and can be easily extended to other WECS configurations.
IEEE Transactions on Energy Conversion 01/2010; · 2.27 Impact Factor
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ABSTRACT: This paper presents a fuzzy methodology for solving thermal unit commitment problem integrated with wind power system using differential evolution approach. Wind power facility is coupled with an equivalent battery to compensate with frequency and voltage fluctuations. Wind energy system is integrated with the system due to lower electric cost and positive effect on the environment. But due to the uncertainty of wind speed and hence wind power generation and load forecasting, a crisp optimization method may fail short providing the effective solution. Therefore, to solve the problem effectively, this model handles such imprecision by fuzzyflcation. Then the unit commitment problem is solved by using a modified differential evolution approach. Trivial differential evolution method is modified to work with thermal scheduling problem which is a mixed-integer problem requiring discrete optimization. Several simulations are presented in order to demonstrate the effectiveness of the proposed method.
Intelligent System Applications to Power Systems, 2009. ISAP '09. 15th International Conference on; 12/2009
