H. Khorramdel; B. Khorramdel; M. Tayebi Khorrami; H. Rastegar
Volume 2, Issue 1 , June 2007, , Pages 49-59
Abstract
The major problem of wind turbines is the great variability of wind power production. The dynamic change of the wind speed returns the quantity of the power injected to networks. Therefore, wind–thermal generation scheduling problem plays a key role to implement clean power producers in a competitive ...
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The major problem of wind turbines is the great variability of wind power production. The dynamic change of the wind speed returns the quantity of the power injected to networks. Therefore, wind–thermal generation scheduling problem plays a key role to implement clean power producers in a competitive environment. In deregulated power systems, the scheduling problem has various objectives than in a traditional system which should be considered in economic scheduling. In this paper, a Multi-Objective Economic Load Dispatch (MOELD) model is developed for the system consisting of both thermal generators and wind turbines. Using two optimization methods, Sequential Quadratic Programming (SQP) and Particle Swarm Optimization (PSO), the system is optimally scheduled. The objective functions are total emission and total profit of units. The probability of stochastic wind power is included in the model as a constraint. This strategy, referred to as the Here-and-Now (HN) approach, avoids the probabilistic infeasibility appearing in conventional models. Based on the utilized model, the effect of stochastic wind speed on the objective functions can be readily assessed. Also a Total Index (TI) is presented to evaluate the simulation results. Also, the results show preference of PSO method to combine with HN approach.
Design System & Algorithm
R. Effatnejad; H. Aliyari; M. Savaghebi
Abstract
The Optimal Power Flow (OPF) is one of the most important issues in the power systems. Due to the complexity and discontinuity of some parameters of power systems, the classic mathematical methods are not proper for this problem. In this paper, the objective function of OPF is formulated to minimize ...
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The Optimal Power Flow (OPF) is one of the most important issues in the power systems. Due to the complexity and discontinuity of some parameters of power systems, the classic mathematical methods are not proper for this problem. In this paper, the objective function of OPF is formulated to minimize the power losses of transmission grid and the cost of energy generation and improve the voltage stability and voltage profile, considering environmental issues. Therefore, the OPF problem is a nonlinear optimization problem consisting of continuous and discontinuous variables. To solve it, Non-dominated Sorting Genetic Algorithm-II (NSGA-II) and a new hybrid algorithm combining modified Particle Swarm Optimization (PSO) and Genetic algorithm (GA) methods are proposed. In this method, each of the algorithms is performed in its procedure and generates the primary population; then, the populations are ordered and from among them, populations with the highest propriety function are selected. The first population that guesses will enter the two algorithms’ procedures for generating the new population. Note that the inputs of the two algorithms are the same; then, generates a new population. Now, there are three groups of populations: one created by modified GA, one created by modified PSO, and the other is the first initial population, and then sorted with the described sorting method.
H. R. Imanijajarmi; A. Mohamed; H. Shareef
Volume 1, Issue 1 , June 2013, , Pages 54-62
Abstract
This paper presents an innovative active power filter design method to simultaneously compensate the current harmonics and reactive power of a nonlinear load. The power filter integrates a passive power filter which is a RL low-pass filter placed in series with the load, and an active power filter which ...
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This paper presents an innovative active power filter design method to simultaneously compensate the current harmonics and reactive power of a nonlinear load. The power filter integrates a passive power filter which is a RL low-pass filter placed in series with the load, and an active power filter which comprises an RL in series with an IGBT based voltage source converter. The filter is assumed to inject a current into the connection node of the load and grid to eliminate current harmonics and its reactive part. The voltage source converter is placed in a hysteresis feedback control loop to generate a harmonic current. The bandwidth and output amplitude of the hysteresis controller are optimized with the inductance of RL filters. Three objective functions are considered in the optimization problem, which include minimizing of current total harmonic distortion, maximizing of power factor, and minimizing of the IGBT bridge current. For solving the optimization problem, two well-known multi-objective evolutionary algorithms are applied, namely, non-dominated sorting genetic algorithm-II (NSGA-II) and Strength Pareto Evolutionary Algorithm 2 (SPEA2). Test results showed that the SPEA2 technique exhibited a better performance in comparison to NSGA-II relative to the objectives.
N. Rostami
Abstract
In this paper, a comprehensive parametric analysis for an axial-flux permanent magnet synchronous generator (AFPMSG), designed to operate in a small-scale wind-power applications, is presented, and the condition for maximum efficiency, minimum weight and minimum cost is deduced. Then a Computer-Aided ...
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In this paper, a comprehensive parametric analysis for an axial-flux permanent magnet synchronous generator (AFPMSG), designed to operate in a small-scale wind-power applications, is presented, and the condition for maximum efficiency, minimum weight and minimum cost is deduced. Then a Computer-Aided Design (CAD) procedure based on the results of parametric study is proposed. Matching between the generator side and turbine characteristics as well as the mechanical constraints is taken into account in design algorithm. A 2.5 kW AFPMSG with two parallel connected stators and surface mounted permanent magnets on its rotor disk is designed using the developed program, and then three dimensional finite-element analyses are carried out to validate the design procedure.
H. Salmani; A. Rezazadeh; M. Sedighizadeh
Abstract
Fossil-fueled vehicles are being replaced by electric vehicles (EVs) around the world due to environmental pollution and high fossil fuel price. On the one hand, the electrical grid is faced with some challenges when too many EVs are improperly integrated. On the other hand, using a massive unexploited ...
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Fossil-fueled vehicles are being replaced by electric vehicles (EVs) around the world due to environmental pollution and high fossil fuel price. On the one hand, the electrical grid is faced with some challenges when too many EVs are improperly integrated. On the other hand, using a massive unexploited capability of the batteries in too many EVs makes these challenges opportunities. This unused capacity can be employed for the grid ancillary services and trading peer-to-peer (P2P) energy. However, the preference of EV users is one of the most important factors, which has to be considered within the scheduling process of EVs. Therefore, this paper proposes a stochastic model for EV bidirectional smart charging taking into account the preferences of EV users, P2P energy trading, and providing ancillary services of the grid. Considering the likings of EV users makes the proposed scheduling model adaptive against changing operating conditions. The presented model is formulated as an optimization problem aiming at optimal managing SOC of EV battery and electrical energy placement of several facilities considering the provision of ancillary services and contributing to P2P transactions. To evaluate the proposed model, real-world data collected from Tehran city are used as input data for simulation. Numerical results demonstrate the ability of the presented model. Simulation results display that considering the preferences of EV users in the proposed model can enhance the total income provided by the EV energy-planning model such that it could balance the charging cost. Moreover, this advanced user-based smart charging model increases P2P energy transactions amongst EVs and raises the ancillary services facility to the grid. Simulation results show that the yearly cost of optimal electrical charging on normal trips, light trips, and heavy trips is reduced by 32.6%, 51.2%, and 34.8% compared to non-optimal ones, respectively.
Power System Stability
R. Ajabi-Farshbaf; M. R. Azizian; V. Yousefizad
Abstract
This paper presents a new algorithm based on Model Reference Adaptive System (MRAS) and its stability analysis for sensorless control of Doubly-Fed Induction Generators (DFIGs). The reference and adjustable models of the suggested observer are based on the active power of the machine. A hysteresis block ...
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This paper presents a new algorithm based on Model Reference Adaptive System (MRAS) and its stability analysis for sensorless control of Doubly-Fed Induction Generators (DFIGs). The reference and adjustable models of the suggested observer are based on the active power of the machine. A hysteresis block is used in the structure of the adaptation mechanism, and the stability analysis is performed based on sliding mode conditions. Simulation and practical results show appropriate operation and speed tracking of the observer with regard to obtained stability conditions.
Micro Grid
Reza Ghanizadeh; Mahmoud Ebadian; Gevork B. Gharehpetian
Volume 4, Issue 1 , June 2016, , Pages 66-82
Abstract
In this paper, a new approach is proposed for voltage and current harmonics compensation in grid-connected microgrids (MGs). If sensitive loads are connected to the point of common coupling (PCC), compensation is carried out in order to reduce PCC voltage harmonics. In absence of sensitive loads at PCC, ...
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In this paper, a new approach is proposed for voltage and current harmonics compensation in grid-connected microgrids (MGs). If sensitive loads are connected to the point of common coupling (PCC), compensation is carried out in order to reduce PCC voltage harmonics. In absence of sensitive loads at PCC, current harmonics compensation scenario is selected in order to avoid excessive injection of harmonics by the main grid. In both scenarios, compensation is performed by the interface converters of distributed generation (DG) units. Also, to decrease the asymmetry among phase impedances of MG, a novel structure is proposed to generate virtual impedance. At fundamental frequency, the proposed structure for the virtual impedance improves the control of the fundamental component of power, and at harmonic frequencies, it acts to adaptively improve nonlinear load sharing among DG units. In the structures of the proposed harmonics compensator and the proposed virtual impedance, a self-tuning filter (STF) is used for separating the fundamental component from the harmonic components. This STF decreases the number of phase locked loops (PLLs). Simulation results in MATLAB/SIMULINK environment show the efficiency of the proposed approach in improving load sharing and decreasing voltage and current harmonics.
Application of Automatic Control in Power System
Z. Moravej; S. Bagheri
Volume 3, Issue 1 , June 2015, , Pages 71-82
Abstract
Power transformers provide a vital link between the generation and distribution of produced energy. Such static equipment is subjected to abuse during operation in generation and distribution stations and leads to catastrophic failures. This paper reviewed the techniques in the field of condition monitoring ...
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Power transformers provide a vital link between the generation and distribution of produced energy. Such static equipment is subjected to abuse during operation in generation and distribution stations and leads to catastrophic failures. This paper reviewed the techniques in the field of condition monitoring of power transformers in recent years. Transformer monitoring and diagnosis are the effective techniques for preventing the eventual failures and contributing to ensure the plan’s reliability. This paper provided a survey on the existing techniques for monitoring, diagnosis, condition evaluation, maintenance, life assessment and possibility of extending the life of the existing assets of power transformers with be appropriate classifications. Thus, this survey could help researchers through providing better techniques for condition monitoring of power transformers.
M. Zadehbagheri; M.J. Kiani; S. Khandan
Abstract
Nowadays micro-grids (MG) as one of the most important methods used for electric power generation from renewable energy to reduce dependence on fossil fuels and reducing environmental pollution have been considered. Due to the increasing number of distributed generation (DG) sources and MGs in the power ...
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Nowadays micro-grids (MG) as one of the most important methods used for electric power generation from renewable energy to reduce dependence on fossil fuels and reducing environmental pollution have been considered. Due to the increasing number of distributed generation (DG) sources and MGs in the power grids, it is of particular importance to design and implement a suitable controller in order to use all the available capacities in these systems. The uncertainty in prediction of power generation can be considered as disturbances into the electrical system, making it difficult to control, and eventually resulting in an unstable system. With the use of power electronic converters the power and voltage of MG can be controlled. In this paper, a 13-bus MG is proposed. This MG includes 3 wind farms and 2 PV farms. A robust sliding mode controller (SMC) is used to control voltage source converters of PV farms. A load shedding program is proposed to avoid complete blackout of MG in case of islanding that recover MG voltage to normal range after a voltage collapse. Simulations were performed using MATLAB/SIMULINK software on a 13-bus IEEE micro grid, and the effectiveness of the proposed control and operational method was investigated and confirmed.
F. Namdari; L. Hatamvand; N. Shojaei; H. Beiranvand
Volume 2, Issue 2 , December 2014, , Pages 129-140
Abstract
Voltage stability issues are growing challenges in many modern power systems. This paper proposes optimizing the size and location of Static VAR Compensator (SVC) devices using a Fuzzy Weighted Seeker Optimization Algorithm (FWSOA), as an effective solution to overcome such issues. Although the primary ...
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Voltage stability issues are growing challenges in many modern power systems. This paper proposes optimizing the size and location of Static VAR Compensator (SVC) devices using a Fuzzy Weighted Seeker Optimization Algorithm (FWSOA), as an effective solution to overcome such issues. Although the primary purpose of SVC is bus voltage regulation, it can also be useful for voltage stability enhancement and even real power losses reduction in the network. To this aim, a multi-objective function is presented which includes voltage profile improvement, Voltage Stability Margin (VSM) enhancement and minimization of active power losses. Voltage stability is very close to Reactive Power Dispatch (RPD) in the network. Therefore, in addition to voltage regulation with locating SVCs, considering all of the other control variables including excitation settings of generators, tap positions of tap changing transformers and reactive power output of fixed capacitors in the network, simultaneous RPD and SVC placement will be achieved. Simulation results on IEEE 14 and 57-bus test systems, applying Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Seeker Optimization Algorithm (SOA) and FWSOA verify the efficiency of FWSOA for the above claims.
H. Taherian; I. Nazer; E. Razavi; S. R. Goldani; M. Farshad; M. R. Aghaebrahimi
Volume 1, Issue 2 , November 2013, , Pages 136-146
Abstract
Accurate and effective electricity price forecasting is critical to market participants in order to make an appropriate risk management in competitive electricity markets. Market participants rely on price forecasts to decide on their bidding strategies, allocate assets and plan facility investments. ...
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Accurate and effective electricity price forecasting is critical to market participants in order to make an appropriate risk management in competitive electricity markets. Market participants rely on price forecasts to decide on their bidding strategies, allocate assets and plan facility investments. However, due to its time variant behavior and non-linear and non-stationary nature, electricity price is a complex signal. This paper presents a model for short-term price forecasting according to similar days and historical price data. The main idea of this article is to present an intelligent model to forecast market clearing price using a multilayer perceptron neural network, based on structural and weights optimization. Compared to conventional neural networks, this hybrid model has high accuracy and is capable of converging to optimal minimum. The results of this forecasting method for Market Clearing Price (MCP) of Iranian and Nord Pool Electricity Markets, as well as Locational Marginal Price (LMP) forecasting in PJM electricity market, verify the effectiveness of the proposed approach in short-term price forecasting.
F. Jabari; M. Zeraati; M. Sheibani; H. Arasteh
Abstract
In the semi-autonomous regions and remote islands, the multiple diesel units are usually used for supplying demand and exchanging power with other adjacent zones. In the risk-aware generation companies consisting of diesel engines, photovoltaic panels (PVs), and wind turbines, the uncertain electricity ...
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In the semi-autonomous regions and remote islands, the multiple diesel units are usually used for supplying demand and exchanging power with other adjacent zones. In the risk-aware generation companies consisting of diesel engines, photovoltaic panels (PVs), and wind turbines, the uncertain electricity market prices affect the optimum operating points of these units, the total revenue gained from selling energy to neighbor microgrids, and the daily fuel cost of the diesel generators. Moreover, the output power of the diesel engines is a nonlinear function of their specific fuel consumption at discrete loading intervals. Therefore, this paper aims to present a risk-aware mixed integer nonlinear optimization problem for finding the best generation schedules of the diesel units involving the energy price fluctuations. The total fuel costs of the diesel engines minus the total revenue achieved from procuring power for nearby regions is minimized as a cost objective function satisfying the lower and upper generation bounds in each loading subinterval, the load-generation balance criterion, and the nominal capacities of generating units. The cubic spline interpolation is used for accurately fitting the fuel-power curves of the diesel generators at successive loading subintervals because of its zero norm of residual in comparison with 5${}^{th}$ degree and quadratic polynomials. A benchmark microgrid with six diesel generators, PVs and wind turbines is robustly scheduled using the budget of uncertainty with no need to probability distribution and membership functions of energy prices. It is revealed that this strategy is practical for each price-taker generation company, which desires the risk-aversion production patterns of the diesel power production units against the energy market price uncertainty in a specific operating horizon.
Distribution Systems
A. Najafi; R. Aboli; H. Falaghi; M. Ramezani
Volume 4, Issue 2 , December 2016, , Pages 153-164
Abstract
Utilizing capacitor banks is very conventional in distribution network in order for local compensation of reactive power. This will be more important considering uncertainties including wind generation and loads uncertainty. Harmonics and non-linear loads are other challenges in power system which complicates ...
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Utilizing capacitor banks is very conventional in distribution network in order for local compensation of reactive power. This will be more important considering uncertainties including wind generation and loads uncertainty. Harmonics and non-linear loads are other challenges in power system which complicates the capacitor placement problem. Thus, uncertainty and network harmonics have been considered in this paper, simultaneously. Capacitor placement has been proposed as a probabilistic harmonic problem with different objectives and technical constraints in the capacitor placement problem. Minimizing power and energy loss and capacitor prices are considered as objectives. Particle Swarm Optimization (PSO) and Differential Evolution (DE) algorithms have been used to solve the optimization problem. Loads are subjected to uncertainty with normal probabilistic distribution function (PDF). Auto Regressive and Moving Average (ARMA) time series and two point estimate method have also been utilized to simulate the wind speed and to perform the probabilistic load flow, respectively. Finally, the proposed method has been implemented on standard distorted test cases in different scenarios. Monte Carlo Simulation (MCS) has also been used to verify the probabilistic harmonic power flow. Simulation results demonstrate the efficiency of the proposed method.
Power Electronic
elias shokati asl; Mohammad Shadnam Zarbil; Mehran Sabahi
Volume 3, Issue 2 , December 2015, , Pages 158-166
Abstract
The Cúk converter, which has voltage buck and boost ability, offers high flexibility as an interface device for solar panels. In addition, current ripple can be more reduced because of two input and output inductors at both sides. This paper presents a new application of current-variable inductors ...
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The Cúk converter, which has voltage buck and boost ability, offers high flexibility as an interface device for solar panels. In addition, current ripple can be more reduced because of two input and output inductors at both sides. This paper presents a new application of current-variable inductors in a Cúk converter that reduces the size and capacity of storage elements. Because of two inductors in structure, implementation of these variable inductors is important; therefore, the proposed design leads to cost and size savings, increases the performance interval of tracker to gain solar energy at lower sunlight levels, and simplifies control strategy. To validate the effectiveness of this structure, the analytical analysis, simulation results using PSCAD/EMTDC software and experimental results are presented.
Energy Management
B. Mohammadi ivatloo; M. Nazari-Heris; F. Kalavani
Abstract
Thermal energy storage (TES) system has been introduced as a practical facility for shifting load from peak hours to off-peak hours. Because of different energy consumption during day and night, peak and off peak period is created on load curve. Ice storage technology which is a kind of TES system, is ...
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Thermal energy storage (TES) system has been introduced as a practical facility for shifting load from peak hours to off-peak hours. Because of different energy consumption during day and night, peak and off peak period is created on load curve. Ice storage technology which is a kind of TES system, is implemented in different points of the world with the purpose of solving load shifting problem. The basic process of this technology is storing energy in the ice during off-peak hours, utilizing an air conditioning unit in which the stored energy will be utilized during day. Utilization of ice storage system is a good solution for optimizing consumption of gas and electrical energy, which will be effective in urban pollution reduction. This paper aims to introduce load shifting problem and the implemented procedures to overcome this problem from the past, analyzing ice storage system as a solution to this problem. Moreover, feasibility of the ice storage technology on a case study in Iran is discussed to show the performance and efficiency of the technology. The obtained results for the case study show that by utilizing ice storage system the consumption and the paid cost will be reduced with respect to conventional system.
Renewable Energy
R. Aghaie; M. Farshad
Abstract
The performance of photovoltaic (PV) systems is highly dependent on environmental conditions. Due to probable changes in environmental conditions, the real-time control of PV systems is essential for exploiting their maximum possible power. This paper proposes a new method to track the maximum power ...
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The performance of photovoltaic (PV) systems is highly dependent on environmental conditions. Due to probable changes in environmental conditions, the real-time control of PV systems is essential for exploiting their maximum possible power. This paper proposes a new method to track the maximum power point of PV systems using the moth-flame optimization algorithm. In this method, the PV DC-DC converter’s duty cycle is considered as the optimization parameter, and the delivered power of the PV system is maximized in real time. In the proposed approach, some schemes are also employed for detecting condition changes and ignoring small fluctuations of the duty cycle. The results of performance evaluation confirm that the proposed method is very fast, robust, and accurate in different conditions such as standard irradiance and temperature, irradiance and temperature variations, and partial shading conditions. The obtained steady-state efficiency and response time for the introduced method under the standard conditions of the test PV system are 99.68% and 0.021 s, respectively. Indeed, in addition to a relatively good efficiency, the faster response of the introduced tracker is also evident in comparison with other methods.
Electric Mechinces & Drive
D. Habibinia; M. Feyzi; N. Rostami
Abstract
Accurate computing of the saturated inductances of Permanent Magnet Synchronous Machine (PMSM) is very important during the design process. In this paper, a new method is presented based on the B-H characteristic of the stator material and unsaturated inductances formulations. This method is used to ...
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Accurate computing of the saturated inductances of Permanent Magnet Synchronous Machine (PMSM) is very important during the design process. In this paper, a new method is presented based on the B-H characteristic of the stator material and unsaturated inductances formulations. This method is used to calculate the saturated inductances of the axial flux PMSM. The synchronous inductance and all of the leakage inductances can be calculated using this method. Two motors with different slot/pole combinations are selected as the case studies. The effectiveness and accuracy of the method is confirmed by 3D Finite Element Analysis (FEA). This method can be extended to other types of electric machines comprising multi-phase winding in their armature such as induction motors and other types of synchronous motors.
S. Cheshme-Khavar; A. Abdolahi; F.S. Gazijahani; N.T. Kalantari; J.M. Guerrero
Abstract
With the exponential penetration of renewable energy sources (RES), the need for compatible scheduling of these has increased from economic and environmental points of view. Due to the high-efficiency and fast-response features of combined heat and power (CHP) generation units, these units can immunize ...
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With the exponential penetration of renewable energy sources (RES), the need for compatible scheduling of these has increased from economic and environmental points of view. Due to the high-efficiency and fast-response features of combined heat and power (CHP) generation units, these units can immunize the system against RES fluctuations. To address the operational challenges associated with RES, this paper aims to schedule the arbitrage of cryogenic energy storage (CES) not only to maximize its owner but also to minimize RES variability. On the other hand, plug-in electric vehicles (PEV) are applied in the proposed model as responsible loads to smooth the system's load profile by changing the consumers' consumption patterns. The proposed problem is modeled as second-order cone programming and solved by the dominated group search optimization algorithm. To verify the applicability and effectiveness of the proposed approach, four different case studies have been executed.
Renewable Energy
S.M. Hashemzadeh; M. Hejri
Abstract
This paper presents a model-based approach for the global maximum power point (GMPP) tracking of solar strings under partial shading conditions. In the proposed method, the GMPP voltage is estimated without any need to solve numerically the implicit and nonlinear equations of the photovoltaic (PV) string ...
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This paper presents a model-based approach for the global maximum power point (GMPP) tracking of solar strings under partial shading conditions. In the proposed method, the GMPP voltage is estimated without any need to solve numerically the implicit and nonlinear equations of the photovoltaic (PV) string model. In contrast to the existing methods in which first the locations of all the local peaks on the P-V curve are estimated and next the place of the GMPP is selected among them, the suggested method estimates directly the GMPP without any need for the evaluation of the other local peaks. The obtained GMPP voltage is then given as a reference value to the input voltage controller of a DC-DC boost converter to regulate the output voltage of the solar string at the GMPP voltage in various irradiation conditions. Furthermore, the values of the temperature and irradiation level of each PV module within the PV string are estimated, and therefore, the proposed method does not need to thermometers and pyranometers. This makes it as a reliable and low-cost GMPP tracking method. The theoretical aspects on which the proposed GMPP algorithm is established are also discussed. The comparison of the numerical results of the suggested GMPP tracking scheme with the existing methods at different environmental conditions shows the satisfactory operation of the proposed technique from the speed and accuracy point of views.
G. Vikram Raju; N. Venkata Srikanth
Abstract
The enhanced power transfer capability is possible with the six-phase transmission system but it did not gain popularity due to the lack of a proper protection scheme to secure the line from 120 types of different possible short circuit faults. This work presents a protection scheme with discrete wavelet ...
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The enhanced power transfer capability is possible with the six-phase transmission system but it did not gain popularity due to the lack of a proper protection scheme to secure the line from 120 types of different possible short circuit faults. This work presents a protection scheme with discrete wavelet transform (db4 mother wavelet) and an artificial neural network (ANN). The Levenberg-Marquardt algorithm is used for training the ANNs. This protection scheme requires only the pre-processed current information of the sending end bus. For fault detection and classification of all 120 fault types, a single ANN module is implemented with six inputs and six outputs. For fault location estimation in each phase, 11 ANN modules with six outputs are implemented, one for each of the 11 types of combination of faults. The MATLAB/ SIMULINK simulation results of the proposed protection technique implemented on the six-phase Allegheny power transmission system show that it is effective and efficient in detecting and classifying all the faults with varying fault parameters with an accuracy of 99.76%. It is found that the performance of the fault location estimation modules is better with the training data and moderate with the testing data.
M. Darabian; A. Jalilvand; R. Noroozian
Volume 2, Issue 1 , June 2007, , Pages 60-73
Abstract
In the past few decades, increasing growth of wind power plants causes different problems for the power quality in the grid. Normal and transient impacts of these units on the power grid clearly indicate the need to improve the quality of the electricity generated by them in the design of such systems. ...
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In the past few decades, increasing growth of wind power plants causes different problems for the power quality in the grid. Normal and transient impacts of these units on the power grid clearly indicate the need to improve the quality of the electricity generated by them in the design of such systems. Improving the efficiency of the large-scale wind system is dependent on the control parameters. The main contribution of this study is to propose a sensitivity analysis approach integrated with a novel hybrid approach combining wavelet transform, particle swarm optimization and an Adaptive-Network-based Fuzzy Inference System (ANFIS) known as Wavelet-ANFIS-PSO to acquire the optimal control of Doubly-Fed Induction Generators (DFIG) based wind generation. In order to mitigate the optimization complexity, sensitivity analysis is offered to identify the Unified Dominate Control Parameters (UDCP) rather than optimization of all parameters. The robustness of the proposed approach in finding optimal parameters, and consequently achieve a high dynamic performance is confirmed on two area power system under different operating conditions.
Power System Stability
H. Shayeghi; A. Younesi
Abstract
In this paper a fuzzy logic (FL) based load frequency controller (LFC) called discrete FuzzyP+FuzzyI+FuzzyD (FP+FI+FD) is proposed to ensure the stability of a multi-source power system in restructured environment. The whale optimization algorithm (WOA) is used for optimum designing the proposed control ...
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In this paper a fuzzy logic (FL) based load frequency controller (LFC) called discrete FuzzyP+FuzzyI+FuzzyD (FP+FI+FD) is proposed to ensure the stability of a multi-source power system in restructured environment. The whale optimization algorithm (WOA) is used for optimum designing the proposed control strategy to reduce fuzzy system effort and achieve the best performance of LFC task. Further, to improve the system performance, an interline power flow controller (IPFC) and superconducting magnetic energy system (SMES) is included in the system. Governor dead band, generation rate constraint, and time delay are considered as important physical constraints to get an accurate understanding of LFC task. The performance of the optimized FP+FI+FD controller is evaluated on a two area six-unit hydro-thermal power system under different operating conditions which take place in a deregulated power market and varying system parameters in comparison with the classical fuzzy PID controller. Simulation results shows that WOA based tuned FP+FI+FD based LFC controller are relatively robust and achieve good performance for a wide change in system parameters considering system physical constraints.
O. Abedinia; N. Amjady; A. Ghasemi; H. Shayeghi
Volume 1, Issue 1 , June 2013, , Pages 63-73
Abstract
A new Multi-Stage Fuzzy (MSF) controller based on Multi-objective Harmony Search Algorithm (MOHSA) is proposed in this paper to solve the Load Frequency Control (LFC) problem of power systems in deregulated environment. LFC problem are caused by load perturbations, which continuously disturb the normal ...
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A new Multi-Stage Fuzzy (MSF) controller based on Multi-objective Harmony Search Algorithm (MOHSA) is proposed in this paper to solve the Load Frequency Control (LFC) problem of power systems in deregulated environment. LFC problem are caused by load perturbations, which continuously disturb the normal operation of power system. The objectives of LFC are to mini small size the transient deviations in these variables (area frequency and tie-line power interchange) and to ensure their steady state errors to be zero. In the proposed controller, the signal is tuned online using the knowledge base and fuzzy inference. Also, to reduce the design effort and optimize the fuzzy control system, membership functions are designed automatically by the proposed MOHSA method. Obtained results from the proposed controller are compared with the results of several other LFC controllers. These comparisons demonstrate the superiority and robustness of the proposed strategy.
Micro Grid
F. Shavakhi Zavareh; E. Rokrok; J. Soltani; M. R. Shahkarami
Abstract
This paper proposes a new adaptive controller for the robust control of a grid-connected multi-DG microgrid (MG) with the main aim of output active power and reactive power regulation as well as busbar voltage regulation of DGs. In addition, this paper proposes a simple systematic method for the dynamic ...
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This paper proposes a new adaptive controller for the robust control of a grid-connected multi-DG microgrid (MG) with the main aim of output active power and reactive power regulation as well as busbar voltage regulation of DGs. In addition, this paper proposes a simple systematic method for the dynamic analysis including the shunt and series faults that are assumed to occur in the MG. The presented approach is based on the application of the slowly time-variant or quasi-steady-state sequence networks of the MG. At each time step, the connections among the MG and DGs are shown by injecting positive and negative current sources obtained by controlling the DGs upon the sliding mode control in the normal and abnormal operating conditions of the MG. Performance of the proposed adaptive sliding mode controller (ASMC) is compared to that of a proportional-integral (PI)-based power controller and SMC current controller. The validation and effectiveness of the presented method are supported by simulation results in MATLAB-Simulink.
Power System Operation
S. Halilčević; I. Softić
Abstract
This paper presents an algorithm based on inter-solutions of having scheduled electricity generation resources and the fuzzy logic as a sublimation tool of outcomes obtained from the schedule inter-solutions. The goal of the algorithm is to bridge the conflicts between minimal cost and other aspects ...
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This paper presents an algorithm based on inter-solutions of having scheduled electricity generation resources and the fuzzy logic as a sublimation tool of outcomes obtained from the schedule inter-solutions. The goal of the algorithm is to bridge the conflicts between minimal cost and other aspects of generation. In the past, the optimal scheduling of electricity generation resources has been based on the optimal activation levels of power plants over time to meet demand for the lowest cost over several time periods. At the same time, the result of that type of optimization is single-dimensional and constrained by numerous limitations. To avoid an apparently optimal solution, a new concept of optimality is presented in this paper. This concept and the associated algorithm enable one to calculate the measure of a system’s state with respect to its optimal state. The optimal system state here means that the fuzzy membership functions of the considered attributes (the characteristics of the system) have the value of one. That particular measure is called the “degree of optimality” (DOsystem). The DOsystem can be based on any of the system's attributes (economy, security, environment, etc.) that take into consideration the current and/or future state of the system. The calculation platform for the chosen electric power test system is based on one of the unit commitment solvers (in this paper, it is the genetic algorithm) and fuzzy logic as a cohesion tool of the outcomes obtained by means of the unit commitment solver. The DO-based algorithm offers the best solutions in which the attributes should not to distort each other, as is the case in a strictly deterministic nature of the Pareto optimal solution.
