جستجوی مقالات مرتبط با کلیدواژه « نیروگاه بادی » در نشریات گروه « برق »

With penetration of renewable energy sources and increasing congestion in transmission networks, the issue of unit commitment (UC) problem has increased in importance, and power system operators demand effective approaches to find a suitable solution to this problem. In this paper, by considering a dynamic line rating (DLR) in the presence of wind power units, a model has been offeredfor the UC problem  to use the existing capacity of lines more effectively through adding smart-grid technologies to the power system. To adapt the proposed approach with real conditions, uncertainties of the problem parameters including wind speed, network load, and ambient temperature were modeled by a scenario-based method in form of a stochastic programming. A Monte-Carlo simulation was used to generate those scenarios, and K-means clustering algorithm was employed so as to reduce  scenarios . All problem limitations were taken into account, and transmission network constraints were considered by AC load flow relations. Numerical results on the IEEE RTS-24-bus system demonstrated the efficiency of the presented model in reducing transmission congestion, operating costs, wind power curtailment; and finally the enhancement of  the network’s technical criteria along with the reliable and stable planning for the power system. Rgarding simulation results, the presence of DLR increased the conductor temperature up to 7 oC by satisfying the maximum allowable temperature. This resulted in 34% higher loading of line compared to a static rating. In this way, the DLR brought  about a 15.33% reduction in total operating cost. In addition, the load shedding and wind power curtailment showed reductions of  88.9% percent  and 89.7% in the presence of DLR.

In areas where the motor load is the predominant load, when the short circuit occurs, the speed of the motors decreases and their power reactive consumption increases, which causes some delays in voltage recovery after fault clearance. This delay can cause operation of protection systems and load shedding. Fault-Induced Delayed Voltage Recovery is a phenomenon in which the voltage level does not reach the pre-fault value immediately after the fault is cleared. If the Voltage recovery delay is significant, the wind power plant will be disconnected from the power system, which causes other problems in the power system. The purpose of this paper is to evaluate the effect of different wind power plant controls on voltage recovery delay. Wind power plant modeling is based on IEC61400-27-1 standard. Also in this paper the effect of location of wind power plant and the ability to Low Voltage Rid Through of wind power plant is considered. All the simulations are performed in DIgSILENT PowerFactory 2021 software.

In Iran, due to the high rate of economic growth and development activities, the annual demand for various energies, including electrical energy, has increased, as a result of which the construction of new power plants has become an undeniable necessity. Considering the evolution of energy in the current century and the need for renewable energies, the use of wind energy and the establishment of wind power plants are increasingly developing. One of the most important issues in the use of wind energy is determining the location of its use, which has a great impact on the efficiency of wind power generation equipment and devices. Determining the right place for the construction of wind power plants requires attention to various criteria and factors. The purpose of this research is to determine the role of climate, geography, economic-social, environmental and geological factors in determining the suitable location for the construction of wind power plants in Khuzestan province. Based on the different roles and effects of these factors, a limitation map and a map of effective factors were prepared. The weights of criteria, sub-criteria and options were determined by Analytical Hierarchy Process (AHP) in EC2000 software environment and GIS software environment was used for spatial modeling and analysis and information integration. The results show that the southern and southwestern regions of Khuzestan province are the best places to build wind power plants.

The expansion of big cities, the ever-increasing demand for electricity consumption, the use of renewable energy sources, the creation of an electricity market, the high cost of creating new electrical networks and many other issues have caused the use of distributed generation in the power system to increase; Therefore, with the increase in the share of distributed generation in the supply of electrical energy, planning the use of these units is considered one of the important issues in planning the development of production and distribution networks. Wind and solar power plants are among the most important renewable sources that are used to produce electricity today, but these sources are somewhat unpredictable and their injected power to the grid fluctuates. In these systems, energy storage systems are usually used to compensate in case of power loss, or in case of power increase, to store energy in itself to inject it into the power grid when needed. The simultaneous use of several distributed generation sources of production should be such that the cost of production and the amount of losses are minimal. The lifespan of the batteries used in these cases is completely dependent on the number of charges and discharges and the frequency of the current passing through them. So, the life of the used battery can also be one of the influential parameters in how to plan this system for production. In this research, a network with three wind turbine units, three solar power generation units and three battery units is considered. This system is programmed using the optimization method of gravity search based on fuzzy logic in such a way that the cost of production and the amount of losses are minimized and the life of the battery is also increased.

The use of high voltage direct current (HVDC) technology to connect wind turbines seems to be very convenient, as it provides a cost-effective solution for long-distance energy transfer as well as for offshore wind farms. In this paper, a new method for connecting wind turbine chains with the help of DC link connection is presented. In this method, electronic power converters are used to create HVDC converters distributed between turbines. In the proposed method, in addition to reducing the number of equipment, converters and electronic components of power, it reduces costs and increases efficiency and better voltage stability in wind fluctuations. The simulation results show that the change in wind speed and related fluctuations due to changes in air climate have no effect on the output voltage of the system connected to the transmission network. The results show that the designed controller works well and keeps the voltage constant at 100 kV by controlling the current. It should be noted that all simulations were performed in PSCAD / EMTDC software environment.

Optimal reactive power dispatch (ORPD), is one of the most challenging problems of power system operation. This problem deals with both system security and the economy. The problem’s objective functions are usually decreasing the voltage profile deviation of the system, improving the voltage stability margin, and decreasing system loss. ORPD is modeled as an optimization problem with nonlinear functions and constraint and mixed continuous/discrete decision variables. The decision variables are the reactive power of the generators and compensators and the tap number of the transformers. To consider the security of the system, the effect of unscheduled events must be modeled and investigated in the ORPD problem. This type of ORPD is called security constraint ORPD (SC-ORPD). However, the uncertain nature of power systems makes it inevitable to consider them in planning issues. These uncertainties are the source of risk in power grids and must be addressed in planning issues, including ORPD. Risk is the possibility of something bad happening. In other words, risk involves uncertainty about the effects of an activity. Therefore, risk functions include a combination of the probability of an event and its impact. Considering deterministic objective functions (not risk-based ones) in ORPD problems may decrease system economy because most of the events are rare in power system operation. In addition, due to low event probability, the calculated risk may not reflect the true risk that operators and networks are facing. These uncertainties are classified into two categories: technical and economic. Technical uncertainties, which affect the system security, include network topology and operation (like demand and generation) whereas economic uncertainties include micro and macro economies. This paper presents, security-constrained optimal reactive power dispatch by considering the technical uncertainties of power systems. Maximizing the voltage stability margin based on the new voltage instability risk index and minimizing losses are the technical and economic objective functions, respectively. The proposed index is more compatible with practical criteria than existing indicators because it excludes the effect of the low events outage probability of power system components on the risk index. The SPEA-II optimization algorithm is then used to find non-dominant solutions, and finally, the fuzzy decision-maker is used to select the dominant solution. The proposed method is applied to standard 30 IEEE-bus system. The results show, that the proposed algorithm is superior to existing methods and increases the voltage stability margin for postulated contingencies and at the same time reduces operating costs.

The presence of uncertain parameters in the power system has created many challenges for designers andoperators of the system including the problem of capacitors in the presence of wind power plants. The answer depends on the amount of load and output power of the wind power plant that has uncertain values. In this paper, the information gap based decision theory method is used model the uncertainty in load and output power of the wind power plant. The objective function includes the cost of capacitive banks and energy losses, used to of load Flow based on unscented transformation for calculate energy losses. A genetic algorithm is used to optimize the above problem. Finally, the efficiency of the proposed method has been investigated by carrying out numerical studies on the IEEE 33-bus network.

With the high penetration of renewable energy, especially wind power generation with probabilistic nature, the power system is faced with multiple challenges from planning and operation point of view. The need for highly flexible emerging sources like energy storage systems for the integration of renewable energy is essential. Furthermore, the natural gas network as a clean and low-cost energy carrier has an impressive role in the long-term energy perspective. The emergence of new technologies like Power-to-Gas (P2G) and compressed air energy storage (CAES) technologies cause the interdependency between electricity and natural gas networks. An optimal bidding strategy of the hybrid wind farms, CAES and P2G facilities to participate in the day-ahead market is investigated in this paper. The hybrid robust-stochastic approach is implemented to handle the system uncertainties including wind power generation, as well as power market prices to maximize profit. The power generated by the wind farm is modeled by a scenario-based stochastic approach, while day-ahead power price uncertainty to find bidding/ offering curves is modeled by a robust optimization approach. Numerical results indicate an increase in profit, as well as maximum utilization of wind power capacity in the presence of P2G and CAES, simultaneously.

Security-Constrained Unit commitment, one of the most critical tasks in electric power system operations, faces new challenges as the supply and demand uncertainty increases dramatically due to the integration of variable generation resources such as wind power generation. To cope with these concerns, we propose a two-stage adaptive robust unit commitment model for the security constrained unit commitment problem in the presence of load and wind uncertainty.   In addition to being robust model to deal with the uncertainty of wind power production, energy storage devices has been considered for further handling of this issue. Compared to the conventional stochastic programming approach, the robust optimization model is more practical because only requires a deterministic uncertainty set , while in stochastic programming to obtain a probability distribution function of parameter uncertainty is very difficult. To resolve the SCUC problem using robust optimization that is very complex and difficult, Benders decomposition algorithm is used to make smaller problems, which makes reduced complexity of the problem, which results in to solve it easier.

In this paper, an optimized double-fed induction generator in wind power plants has been studied. The equations of optimal design is extracted and for evaluation of generator performance, a model has been presented and based on this model, the generator is optimized using finite element analysis (FEA). The aims of the optimizations are improvement of voltage and current waveform to could reach a better output power. Also, in mechanical point of view, dimension of machine including axial length, number of slots per phase per pole, etc is optimized and minimum weight of machine obtained. The results show that, with a proper optimization, Total costs of the generators like materials costs are significantly reduced. Finally, the FEA results compared with analytical methods and it is observed that the FEA is a powerful tool to optimize the induction generators. The study also shows that optimization of the generator performance can help to improve the performance of the wind farm.

This paper represents two main contributions. Firstly, a new state space model is represented for doubly fed induction generators (DFIG) by adding the uncertainty in the state equation. Secondly, a direct active and reactive power control (DPC) is designed for wind power systems with DFIG. The proposed DPC strategy employs a nonlinear sliding mode control scheme to directly calculate the required rotor and grid control voltages so as to eliminate the instantaneous errors of active and reactive powers. Constant converter switching is achieved by using space vector modulation, which eases the design power converter and the ac harmonic filter. As a result, no extra current control loops are required, and hence the design is simplified and the transient performance is improved. Finally, the proposed controller is applied to control a 2-MW grid-connected DFIG system, and the simulation results effectiveness of proposed control system.

In this study, we will investigate the possibility of using renewable energy resources in area where electrical energy is not supported. We will consider it as a micro-grid and we will try to supply its electrical energy by decreasing cost and having reliability in system. Generally, the main reason of designing and developing of distribution grid is responsible to growth of electrical consumption with maximum economic efficiency which the restriction of system is not made violation. Existing more elements in the distribution and sub-transmission networks have faced the designing and developing with problem where there are many decision variables. Advert of the distributed generation in distribution systems furthermore the changing operation of these systems provide this possibility to companies that can design systems with low cost. In this study, we aim to minimize the cost of the hybrid system of hydroelectric, wind, solar and battery and we will calculate LPSP index by GSO algorithm. It is designed and implemented for long-term network over 20-year.

The aim of the generation expansion planning (GEP) is finding suitable technology, time and installation location of new plants in a specified time period such that the installed capacity will satisfy the load demand growth with acceptable level of reliability. In this paper, we investigate one of the important approaches known as robust optimization (RO) to consider uncertainties such as forecasted electricity load demand, wind power generation, as well as investment and operation costs. The optimal generation expansion plan obtained from the proposed RO approach is immunized against worst-case planning uncertainties considering the adopted degree of conservatism for each uncertainty set. A decomposition algorithm technique has been implemented to solve the robust counterpart of the original GEP problem in terms of cutting planes. To reduce the utility cost, the wind power plant has been utiled in robust generation expansion planning. Accordingly, the uncertaint parameters (including wind power genaration uncertainty and investment cost) have been modeled based the metod of Bertsymas and Sim.

One of the major challenges for power system operators and administrators who are involved with the electricity market, reduce the uncertainty of wind power in a competitive market. In this study an integrated partnership model wind and pumped storage power plants in the energy and reserve market clearing Different aspects of the operating costs compared. Also, the role of pumped storage plants as storage for the increased penetration of wind power in the power network has been compiled. In addition, reduced operating costs, reducing the need to store the rotating and nonrotating joint exploitation of wind and storage are discussed. To simplicity of the problem, Three-bus system, the presence of a pumped storage unit and an wind unit during the simulation period of 4 hours is considered.

One common problem in power systems is contingencies. Since the system is likely to enter an emergency condition, the various possible failures likely to occur in a system should be evaluated and ranked beforehand and the necessary measures should be accordingly taken so as to cope with such upcoming conditions by the system operator. According to the today’s increase in the use of renewable energies in power systems, a solution that can play a considerable part in reducing the adverse effects of such failures is the purposive use of such production entities for improving the power system security. Thus, the present study deals with the investigation of the methods of maximizing wind farms and their optimal location effects on the improvement of the post-contingency conditions of the system. Meanwhile taking the wind farms’ production power into consideration, the current research tries to find the best location for wind farms in such a manner that they could exert the largest effect on improving the system security. To do so, Particle Swarm Optimization (PSO) algorithm and Monte Carlo Simulation (MCS) using MATLAB are applied and the proposed method has been tested on IEEE-RTS and the numerical results have been analyzed.

This paper proposes an analytical dynamic model for series connected induction generator (SCIG) and investigates the experimental performance of SCIG and compares it with an ordinary induction generator (IG) at standalone operating mode. After introducing the structure of series connected induction generator and its different modes of performance, a suitable dynamic model is proposed for this machine. The results of experimental investigations indicate that series connected induction generator and ordinary induction generator have some similar behaviors. But, SCIG has higher speed range without any need to gearbox and capability of operating at higher voltage level. So it may be proposed as a new suitable candidate for wind power generation at regions with high-speed wind.