Wind Turbine Generating Units Research Articles

Frequency Regulation of Interlinked Microgrid System Using Mayfly Algorithm-Based PID Controller

The primary goal of this article is to design and implement a secondary controller with which to control the system frequency in a networked microgrid system. The proposed power system comprises of Renewable energy sources (RESs), energy-storing units (ESUs), and synchronous generator. RESs include photovoltaic (PV) and wind turbine generator (WTG) units. The ESU is composed of a flywheel and a battery. Because renewable energy sources are not constant in nature, their values fluctuate from time to time, causing an effect on system frequency and power flow variation in the tie line. The nonlinear output from the RESs is balanced with the support of ESUs. In order to address this situation, a proportional integral derivative (PID) controller based on the Mayfly algorithm (MA) is proposed and built. Comparing the responses of controllers based on the genetic algorithm (GA), differential evolution (DE), and particle swarm optimization (PSO) technique-optimized to demonstrate the superiority of the MA-tuned controller.. The results of the validation comparisons reveal that the implemented MA-PID controller delivers and is capable of regulating system frequency under various load demand changes and renewable energy sources. A robustness analysis test was also performed in order to determine the effectiveness of the suggested optimization technique (1%, 2%, 5%, and 10%) step load perturbation (SLP) with ±25% and ±50% variation from the nominal governor and reheater time constant).

Optimal WTGUs Placement for Performance Improvement in Electrical Distribution System Using Improved TLBO

The optimal location and size for Distributed Generation (DG) to get maximum advantages and improve the performance of electrical distribution systems (EDS) is a difficult challenge to solve. With EDS performance indices, this research offers a constrained generalized multi-objective performance index (MOPI) objective function. Improved Teaching Learning Based Optimization (ITLBO) is used to solve the proposed objective function by removing the convergence issue of basic Teaching Learning Based Optimization (TLBO). By optimizing the MOPI, the Wind Turbine Generation Unit (WTGU) is examined for single and multiple DG placement and sizing in EDS performance improvement. The ideal approach reduces the burden of EDS consumer loss allocation by minimizing power losses, improving the consumer voltage profile and voltage stability, increasing the line loadability margin (LLM), and increasing the line loadability margin (LLM). The performance test was carried out on a 33-node EDS and used MATLAB software to demonstrate the efficacy of optimal solution.

Design and performance study of a rotating piezoelectric wind energy harvesting device with wind turbine structure

This paper proposes a rotating piezoelectric ambient wind energy harvesting device with wind turbine structure (R-PWEH), which mainly consists of wind turbine, support structure, excitation module, and power generation unit. This paper mainly investigates the effect of wind turbines with a different number of fan blades and units with different shapes of power generation on the performance output of R-PWEH. A series of experimental studies were conducted on the R-PWEH in the wind speed range of 0–20 m/s. In the experimental study at a wind speed of 16 m/s, the maximum voltage output of the R-PWEH was 114.24 V when the wind turbine with 11 fan blades and the rectangular cantilever beam power generation unit was installed. The optimal external load at this point is 8 kΩ and the maximum output power is 36.89 mW. The fastest charging rate for the capacitor at this parameter allows for easy powering of multiple light-emitting diodes for illumination. It has good prospects for development in practical applications, such as the ability to power micro and small sensors.

A novel Green Leaf‐hopper Flame optimization algorithm for competent frequency regulation in hybrid microgrids

AbstractA proficient frequency regulation scheme has been explored in this work for two interconnected hybrid microgrids () comprised of multiple renewable energy sources, like solar‐thermal units, wind turbine generator units, solar photovoltaic, biogas turbine, biodiesel generator, and storage units. A new optimization algorithm has been formulated to replicate the photo‐tactic swarming behavior of green leafhoppers named Green Leaf‐hopper Flame optimization algorithm (GLFOA) to tune the system controllers (proportional integral (PI)/proportional derivative (PD)/proportional integral derivative (PID) controllers). The superiority of GLFOA is confirmed by comparing the performance with several popular optimization algorithms. To assess the stability of the several rigorous tests have been conducted considering availability/nonavailability of renewable resources, gusty wind, real‐time variation of solar radiation and wind velocities along with the random load disturbances. GLFOA tuned PID controllers were found to be the best to contain the frequency deviations. The maximum peak overshoot, undershoot, and settling time obtained by GLFOA tuned PID controllers are 0.01051 Hz, −0.00764 Hz, and 14.15 s, respectively, which are within an acceptable limit. Further, there is an improvement of 0.15% in the performance index obtained by GLFOA over its counterpart obtained by grey wolf optimization, confirming the superiority of the GLFOA tuned controller.

Improving Power Harvesting Ability of Variable Speed Wind Turbine using Intelligent Soft Computing Technique

This paper presents a study carried out on maximizing energy harvesting of wind turbines. One way of improving the output power of the wind turbines is by optimizing the power conversion coefficient. The power conversion coefficient factor is expressed as a function of the wind turbine blade tip speed ratio and the turbine blade pitch angle. Optimization of the wind turbine generator output power is done by considering the effects of variations of wind speed, blade tip speed ratio, and pitch angle. An intelligent soft computing technique known as an adaptive neuro-fuzzy inference system (ANFIS) with a fuzzy logic controller for blade pitch actuator was applied to optimize the generator output power. The simulation result showed that the power conversion coefficient of 0.513 is achieved. The study was verified by using real-time wind speed data of Adama II wind farm in Ethiopia and specifications of the Gamesa G80 horizontal axis wind turbine generator unit by MATLAB software. Accordingly, a promising and satisfying improvement in power harvesting capacity is obtained. The output power of this generator is improved by 9.47% which is by far better result as compared to the existing literature.

Simplified Modelling of Oscillation Mode for Wind Power Systems

Wind turbine generators can be operated in various types of system configurations. Once the configurations change, the system oscillation mode shapes change accordingly. The modelling of the full system is necessary for studying this issue, yet it is quite hard. In this paper, a simple approach is developed to study the mode shapes of wind power systems without the necessity of adopting the complex full-system models. The key is that the q-d axis model of electric power system is transformed into the single-axis model, so that it could integrate with the equivalent circuit model of drive train mechanism. After analyzing some of the system configurations organized by the well-known MOD-2 wind turbine generator unit, the proposed approach is found to be effective for analyzing various oscillation modes such as the local torsional oscillations, as well as the inter-unit and inter-area oscillations.

Impact of Wind Farms on Power System Voltage Stability (Dept.E)

Steady state analysis of wind turbine generating units (WTGUs) interconnected with the grid is needed as the use of WTGU are getting more popular and many new systems are being planted. In this paper, probabilistic voltage stability algorithm of WTGUs interconnected with the utility grid is developed via power Moy analysis where these units are modeled as P-Q bus(es) by detecting the collapse p oint on the Q-V curves. The developed algorithm also facilitates the computation of both the real and reactive power output of the fixed speed pitch regulated wind turbine at a specific site, wind turbine characteristics, wind speed and terminal voltage. The probabilistic nature of wind is considered by introducing the expected voltage stability margin is an index that combines both of the voltage stability and the wind distribution in one index. The proposed algorithm is implemented and applied on the IEEE 26-bus, voltage stability margin (VSM), and expected voltage stability margin (EYSM) are calculated at each wind speed. The accumulation of the EVSM over a specific period, can be considered as the system voltage stability margin which is a single value that can be compared with the voltage stability margin of the all-conventional power system.

Optimal Modeling and Allocation of Mixed Wind and Solar Generation Systems in Electric Distribution Networks

Electric power generated in a centralized station is transmitted through the transmission system and supplied to the consumer end through an electric distribution substation. Electric power losses are high in distribution network compared to the transmission system. The integration of decentralized generation (DG) units in electric distribution networks will reduce power losses. However, the integration of conventional DG is not appreciable due to various techno-economic and environmental concerns. Hence there is a need for the changeover from conventional to renewable energy sources (RES) for energy requirement. Because of vast availability, non-polluting nature, and sustainable character of RES are grasping significant attention over the years. At present most, viable RES are solar and wind energy systems in the world. It is observed that the output generation patterns of solar photovoltaic (PV) arrays and wind turbine generation units (WTGUs) are arbitrary. Hence there is a need for sophisticated method/technique for modeling these generated outputs. In the present paper, optimal modeling and allocation of RES are solved using a novel metaheuristic algorithm. The proposed algorithm is tested on 12, 15 and 85 – bus radial distribution networks (RDNs) and the simulation results obtained are outperforms other existing techniques in the literature.

Damping of low-frequency oscillation in power systems using hybrid renewable energy power plants

Global warming, increase in environmental pollution, and high cost of electrical power generation using fossil fuels are considered the most important reasons for the application of renewable energy power plants (REPPs) around the world. In recent years, a new generation of REPPs called hybrid renewable energy power plants (HREPPs) has been implemented in order to have higher efficiency and reliability than conventional REPPs such as wind power plants and photovoltaic power plants. The HREPPs include two or more renewable energy generation units such as wind turbine generation units, and PV generation units. In case of high penetration of these types of power plants, the most common tasks of synchronous generators should be supported by them. One of these tasks is the ability to reduce the low-frequency oscillation (LFO) risk through power oscillation damper such as the power system stabilizers of synchronous generators. In this paper, a novel method is proposed for LFO damping by HREPPs, which is based on the design of an optimal power oscillation damper (OPOD) implemented in the generic HREPP controller model. The structure of the proposed OPOD is a 2nd-order single-input lead-lag controller, and its performance is investigated in a modified two-area test system. The simulation results show the proper performance of the HREPP for LFO damping using the proposed OPOD in the various loading levels and different short circuit ratio values.

Reduction of Fluctuation of Wind Turbines’ Output Power by Modeling and Control

This paper presents the development of a simplified model for wind turbine-generator unit by empirical and physical principles and enhancing its output power and frequency fluctuations. The model has been implemented by MATLAB® / SIMULINK and has reflected the main variation trends of the real wind turbine which is located in Al-Fujeij, southern Jordan. The simulation results for different sets of data have shown the validity of the proposed model and its suitability for power system studies. Furthermore, the study suggests two algorithms of the smoothing of the output power using a control system for the wind turbine generator with Energy Storage System (ESS). The idea is based on developing a computerized programmed manager for the battery, in the regulatory level, in order to perform a repeated charge / discharge process to in order discharge or inject the power to aid the real power output when it is below the external reference power and continue in the charging phase when there is much available wind energy that may exceed the reference load command sent by the energy control center. Encouraging results that may lead to feasible implementation in practice and increasing the penetration of wind energy without negatively affecting the power system frequency have been obtained.

Health condition assessment of wind turbine generators based on supervisory control and data acquisition data

As the running time of a wind turbine generator unit (WTGU) increases, the ageing and wear of its components will be aggravated gradually, which leads to deterioration of its operation condition. In order to ensure the safe and stable operation of WTGU and prolong its service life, it is of great significance to know the health condition of the WTGU and reasonably arrange maintenance. Based on the structure of the WTGU and the operation principle of the wind turbine generator (WTG), the condition assessment indexes of WTG were built, and the factors influencing the assessment index were determined. The relationship function between the assessment indexes and their influencing factors was established by using the least square support vector machine, which was used to determine the dynamic limitation of condition assessment index of WTG. The dynamic weight of each assessment index was used to characterise the influence of deterioration degree of different components on WTG conditions. Then the health conditions of WTG were evaluated using a similar cloud and fuzzy comprehensive assessment method separately. Finally, the proposed methods were verified by two examples including a direct-drive permanent magnet wind generator and a doubly-fed wind generator.

Investigation of subsynchronous control interaction in DFIG-based wind farms connected to a series compensated transmission line

The aim of this paper is to investigate the risk for subsynchronous control interaction (SSCI) in doubly-fed induction generator (DFIG) based wind farms connected to series-compensated transmission lines. For this purpose, a detailed analytical model of the frequency-dependent input admittance of the DFIG is derived. The developed admittance model is then used to get insights on the frequency characteristic of the DFIG wind turbine generator unit. In particular, the power-dissipation properties of the DFIG are used to identify those control parameters and operating condition that mainly impact the behaviour of the wind turbine in the subsynchronous frequency range. The admittance model of the wind farm together with the impedance model of the series-compensated transmission line are used to identify the risk for SSCI. Through the use of the Generalized Nyquist Criterion, it is shown that the closed-loop bandwidth of the current controller that regulates the rotor current has a major detrimental impact on the stability of the system. Furthermore, results show that the active power set-point and the level of series compensation also play an important role on the overall system’s stability. Time-domain simulations are conducted to validate the theoretical findings.

Performance of Wind Energy Conversion System with Parallel Wind Turbines Topology

Worldwide, a significant growth has been noticed in wind turbine installed capacity which encourages the exploration of new Wind Turbine topologies and developed it. In this paper, a parallel connected Wind Turbine generation units based on variable speed directly coupled Permanent Magnet Sync

Optimal stochastic scheduling of cryogenic energy storage with wind power in the presence of a demand response program

Abstract This paper provides a stochastic method to conduct the optimal scheduling of the combination of wind power and new-type large-scale energy storage with considering the demand response program in the electricity market. The integration of ASU and CES make the opportunity to store energy in the form of liquid in the off-peak periods and recovering the electricity in the peak periods. The uncertainty of electricity price, load demand and wind speed considered as the stochastic model uncertain parameters. The optimal operation of wind turbine, CES, and conventional generation units, considering the stochastic models for price, demand, and wind speed, was formulated as a mixed-integer non-linear programming (MINLP) problem. The constraints of CES operation, liquid and gas product demands, and ASU production were considered in ASU-CES modeling. The startup cost, minimum on/off time constraints, ramp rate, and capacity limits were considered in the formulation of conventional power generation. The demand response (DR) program was adopted to increase the total expected profit and decrease the total operational cost. The results revealed that the application of CES to attest system containing ASU increases the total profit of power generation units and decreases the total cost of generating power to serve load demands.

Retracted: Reliability assessment of composite generation expansion planning considering wind turbine

The expansion planning of wind turbine generating (WTG) requires the information of its forced outage rate (FOR) determined by using the continuous-time Markov Chain. In contrast with the conventional power plant, for the case study of WTG, the determination of FOR is utterly unique since it depends on the information of uncertain weather condition. Hence, the loss of load expectation (LOLE) and expected unserved energy (EUE) could be estimated so that it will not infringe its respective predetermined limits indispensable for the expansion planning of WTG using the stochastic approach. The modified IEEE RTS-79 system is used as a case study to verify effectiveness of the proposed method in the determination of WTG expansion planning. The results have shown improvement on the EUE and LOLE in relation with optimal expansion of the WTG units determined by using the proposed method.

Impact of Different PQ Models of Wind Turbine Generating Units (WTGUs) on System Voltage Performance

AbstractThis paper presents the voltage performance analysis of the system with various types of wind turbine generating units (WTGUs). A detailed voltage performance analysis is carried out by considering the different PQ models used for computing the reactive power output of the WTGUs (fixed/semi-variable speed and variable speed WTGUs). The different PQ models of fixed/semi-variable speed WTGUs incorporated for the studies are voltage dependent model, voltage independent model, power factor based model, and PX model. In addition, the variable speed WTGUs are also considered in different fixed power factor mode of operation. Based on these models, a comparative analysis is presented. A modified 27-bus equivalent distribution test system with dispersed wind generation is considered for the studies. Further, the case studies have been carried out by considering the various wind power output levels of WTGUs to examine its impact on system voltage performance. From the comparative analysis, the power factor based model can be the best choice over the other models (which are based on voltages) for the system studies with fixed/semi-variable speed WTGUs.

Optimal placement and sizing of wind / solar based DG sources in distribution system

Proper placement and sizing of Distributed Generation (DG) in distribution system can obtain maximum potential benefits. This paper proposes quantum particle swarm algorithm (QPSO) based wind turbine generation unit (WTGU) and photovoltaic (PV) array placement and sizing approach for real power loss reduction and voltage stability improvement of distribution system. Performance modeling of wind and solar generation system are described and classified into PQ\\PQ (V)\\PI type models in power flow. Considering the WTGU and PV based DGs in distribution system is geographical restrictive, the optimal area and DG capacity limits of each bus in the setting area need to be set before optimization, the area optimization method is proposed . The method has been tested on IEEE 33-bus radial distribution systems to demonstrate the performance and effectiveness of the proposed method.

제주도 계통에서의 풍력발전기 및 ESS를 고려한 신뢰도 평가

This paper proposes probabilistic reliability evaluation model of power system considering Wind Turbine Generator(WTG) integrated with Energy Storage System(ESS). Monte carlo sample state duration simulation method is used for the evaluation. Because the power output from WTG units usually fluctuates randomly, the power cannot be counted on to continuously satisfy the system load. Although the power output at any time is not controllable, the power output can be utilized by ESS. The ESS may make to smooth the fluctuation of the WTG power output. The detail process of power system reliability evaluation considering ESS cooperated WTG is presented using case study of Jeju island power system in the paper.

Multi-linear Monte Carlo simulation method for probabilistic load flow of distribution systems with wind and photovoltaic generation systems

In this paper, a probabilistic method is proposed to analyze the steady-state operating conditions of an active electrical distribution system with Wind (WD) and Photovoltaic (PV) generation plants. This method takes into account the uncertainties of power load demands and power production from renewable generation systems and combines Monte Carlo simulation techniques and multi-linearized power flow equations. The power flow equations include models of wind turbine and PV generation units and multi-linearization is accomplished by applying a criterion based on the total active power of the system. The method properly extends a probabilistic method proposed in the relevant literature for traditional passive electrical distribution systems to the field of an active electrical distribution system with WD and PV generation units. Numerical applications are presented and discussed with reference to a 17-bus test distribution system characterized by WD and PV systems connected at different busbars. The results obtained with the proposed algorithm are compared with the results obtained using a Monte Carlo simulation algorithm that included non-linear power flow equations.

Reliability models of wind farms considering wind speed correlation and WTG outage

Wind speed correlation and wind turbine generator (WTG) outage are two factors affecting the reliability model of wind farms, but they are not addressed simultaneously in the existing literature. Meanwhile, WTG outage is reported to be dependent with wind speed to some extent. Therefore, the extended reliability models of wind farms incorporating both of these two factors and the dependency between WTG outage and wind speed are proposed in this paper. To consider the uncertainties and dependencies of wind speed and WTG failure, Copula method is applied to simulate correlated random variables representing for wind speed and the number of failed WTG units. Moreover, the linear apportioning technique is used to create multistate reliability models of wind farms from hourly wind power models. A number of sensitivity analyses on the modified IEEE RTS with wind power are conducted to validate the proposed reliability models for generation adequacy assessment. Case studies show that the generation adequacy indices increase with the correlation of wind speed and WTG forced outage rate (FOR). It is meaningful to point out that the effect of dependency between wind speed and WTG FOR on generation adequacy is minimal when WTG outages are independent, but it will be substantially larger when WTG outages are highly dependent. The proposed multistate reliability models of wind farms provide foundation for the reliability assessment of power systems with wind power integrated.