scholarly journals Cooperative Synthetic Inertia Control for Wind Farms Considering Frequency Regulation Capability

2021 ◽  
Vol 9 ◽  
Author(s):  
Qiaoming Shi ◽  
Lei Liu ◽  
Yongping Wang ◽  
Yu Lu ◽  
Qiang Zou ◽  
...  
Keyword(s):  
Wind Farm ◽  
Evaluation Method ◽  
Wind Farms ◽  
Fast Response ◽  
Frequency Regulation ◽  
Rotor Speed ◽  
Control Center ◽  
Frequency Drop ◽  
Inertia Control ◽  
Capability Evaluation

To fully utilize the frequency regulation (FR) capability of wind turbines (WTs) and to avoid a secondary frequency drop caused by the rotor speed recovery, this paper firstly proposes an FR capability evaluation method for wind farms based on the principle of equal rotational kinetic energy of WTs, and analyses the essence of cooperative rotor speed recovery for WTs. Based on these, a cooperative synthetic inertia control (CSIC) for wind farms considering FR capability is proposed. By introducing the cooperative coefficient, the CSIC can fully utilize the FR capability of WTs, maintain the fast response of WTs with synthetic inertia control, and reduce communication requirements for the wind farm control center. By directly compensating the auxiliary FR power of WTs, the CSIC realizes the cooperative rotor speed recovery for WTs between different wind farms, avoiding a secondary frequency drop and a complex schedule of rotor speed recovery for multiple WTs. Finally, the simulation results verify the effectiveness and feasibility of the proposed control.

scholarly journals Research on DFIG-ES System to Enhance the Fast-Frequency Response Capability of Wind Farms

Energies ◽  
2019 ◽  
Vol 12 (18) ◽  
pp. 3581
Author(s):  
Sijia Tu ◽  
Bingda Zhang ◽  
Xianglong Jin
Keyword(s):  
Frequency Response ◽  
Fuzzy Logic Controller ◽  
Wind Farms ◽  
Capacity Allocation ◽  
Frequency Regulation ◽  
Rotor Speed ◽  
Synchronous Generators ◽  
Frequency Drop ◽  
Inertia Control ◽  
Doubly Fed

With the increasing penetration of wind power generation, the frequency regulation burden on conventional synchronous generators has become heavier, as the rotor speed of doubly-fed induction generator (DFIG) is decoupled with the system frequency. As the frequency regulation capability of wind farms is an urgent appeal, the inertia control of DFIG has been studied by many researchers and the energy storage (ES) system has been installed in wind farms to respond to frequency deviation with doubly-fed induction generators (DFIGs). In view of the high allocation and maintenance cost of the ES system, the capacity allocation scheme of the ES system—especially for fast-frequency response—is proposed in this paper. The capacity allocation principle was to make the wind farm possess the same potential inertial energy as that of synchronous generators set with equal rated power. After the capacity of the ES system was defined, the coordinated control strategy of the DFIG-ES system with consideration of wind speed was proposed in order to improve the frequency nadir during fast-frequency response. The overall power reference of the DFIG-ES system was calculated on the basis of the frequency response characteristic of synchronous generators. In particular, once the power reference of DFIG was determined, a novel virtual inertia control method of DFIG was put forward to release rotational kinetic energy and produce power surge by means of continuously modifying the proportional coefficient of maximum power point tracking (MPPT) control. During the deceleration period, the power reference smoothly decreased with the rotor speed until it reached the MPPT curve, wherein the rotor speed could rapidly recover by virtue of wind power so that the secondary frequency drop could be avoided. Afterwards, a fuzzy logic controller (FLC) was designed to distribute output power between the DFIG and ES system according to the rotor speed of DFIG and S o C of ES; thus the scheme enabled the DFIG-ES system to respond to frequency deviation in most cases while preventing the secondary frequency drop and prolonging the service life of the DFIG-ES system. Finally, the test results, which were based on the simulation system on MATLAB/Simulink software, verified the effectiveness of the proposed control strategy by comparison with other control methods and verified the rationality of the designed fuzzy logic controller and proposed capacity allocation scheme of the ES system.

Integrated AHP-BPNN Model for Wind Farm Investment Evaluation

2014 ◽  
Vol 541-542 ◽  
pp. 966-971
Author(s):  
Xiang Feng Zhang ◽  
Tian Yu Liu ◽  
Bin Jiao
Keyword(s):  
Wind Farm ◽  
Evaluation Method ◽  
Back Propagation ◽  
Wind Farms ◽  
Back Propagation Neural Network ◽  
Analytic Hierarchy ◽  
Farm Investment ◽  
Hierarchy Process ◽  
Power Project ◽  
Bpnn Model

The construction of wind farms grows quickly in China. It is necessary for stakeholders to estimate investment costs and to make good decisions about a wind power project by making a budget for the investment. This paper proposed an evaluation method by integrating the analytic hierarchy process (AHP) with back-propagation neural network (BPNN) to evaluate wind farm investment. In the AHP-BPNN model, the AHP method is used to determine the factors of wind farm investment. The factors with high importance are reserved while those with low importance are eliminated, which can decrease the number of inputs of the BPNN. The experiment results show that the integrated model is feasible and effective.

Combining AHP and TOPSIS Methods to Evaluate Investment for Wind Farm Construction

2013 ◽  
Vol 860-863 ◽  
pp. 280-286 ◽  
Author(s):  
Xiang Feng Zhang
Keyword(s):  
Alternative Energy ◽  
Wind Farm ◽  
Evaluation Method ◽  
Evaluation Criteria ◽  
Wind Farms ◽  
Investment Strategy ◽  
Analytic Hierarchy ◽  
Multi Criteria Evaluation ◽  
Order Preference ◽  
Rational Investment

Wind is one of the most promising sources of alternative energy. The construction of wind farms grows quickly in China. It is necessary for stakeholders to estimate investment costs and make good decisions on a wind power project by making a budget for the investment. However, the identification of rational investment practices is technically challenging because of the lack of scientific tools to evaluate optimal decisions. A multi-criteria evaluation method was proposed to select rational investment strategy for wind farm construction. The method is based on the analytic hierarchy process (AHP) together with a technique for order preference by similarity to ideal solution (TOPSIS). A decision problem hierarchy with three layers were investigated. The top layer is an objective layer for evaluating the investment rationality. The intermediate layer includes three evaluation criteria, that is, configuration of wind turbine generator systems, physical environment and social environment. Some relative and important indicators for each criterion are in the low layer. The evaluation results illustrate that the proposed method is practical and helpful to indentify the investment rationality for wind farms.

scholarly journals Wind farms providing secondary frequency regulation: Evaluating the performance of model-based receding horizon control

2017 ◽  
Author(s):  
Carl R. Shapiro ◽  
Johan Meyers ◽  
Charles Meneveau ◽  
Dennice F. Gayme
Keyword(s):  
Dynamic Model ◽  
Wind Farm ◽  
Wind Farms ◽  
Static Model ◽  
Receding Horizon Control ◽  
Frequency Regulation ◽  
Control Approach ◽  
Model Based ◽  
Model Control ◽  
Wake Model

Abstract. We investigate the use of wind farms to provide secondary frequency regulation for a power grid using a model-based receding horizon control framework. In order to enable real-time implementation, the control actions are computed based on a time-varying one-dimensional wake model. This model describes wake advection and wake interactions, both of which play an important role in wind farm power production. In order to test the control strategy, it is implemented in a large eddy simulation (LES) model of an 84-turbine wind farm using the actuator disk turbine representation. Rotor-averaged velocity measurements at each turbine are used to provide feedback for error correction. The importance of including the dynamics of wake advection in the underlying wake model is tested by comparing the performance of this dynamic-model control approach to a comparable static-model control approach that relies on a modified Jensen model. We compare the performance of both control approaches using two types of regulation signals, "RegA'" and "RegD", which are used by PJM, an independent system operator in the Eastern United States. The poor performance of the static-model control relative to the dynamic-model control demonstrates that modeling the dynamics of wake advection is key to providing the proposed type of model-based coordinated control of large wind farms. We further explore the performance of the dynamic-model control via composite performance scores used by PJM to qualify plants for regulation. Our results demonstrate that the dynamic-model controlled wind farm consistently performs well, passing the qualification threshold for all fast-acting RegD signals. For the RegA signal, which changes over slower time scales, the dynamic-model control leads to average performance that surpasses the qualification threshold, but further work is needed to enable this controlled wind farm to achieve qualifying performance for all regulation signals.

scholarly journals Wind farms providing secondary frequency regulation: evaluating the performance of model-based receding horizon control

2018 ◽  
Vol 3 (1) ◽  
pp. 11-24 ◽  
Author(s):  
Carl R. Shapiro ◽  
Johan Meyers ◽  
Charles Meneveau ◽  
Dennice F. Gayme
Keyword(s):  
Dynamic Model ◽  
Wind Farm ◽  
Wind Farms ◽  
Static Model ◽  
Receding Horizon Control ◽  
Frequency Regulation ◽  
Control Approach ◽  
Model Based ◽  
Model Control ◽  
Wake Model

Abstract. This paper is an extended version of our paper presented at the 2016 TORQUE conference (Shapiro et al., 2016). We investigate the use of wind farms to provide secondary frequency regulation for a power grid using a model-based receding horizon control framework. In order to enable real-time implementation, the control actions are computed based on a time-varying one-dimensional wake model. This model describes wake advection and wake interactions, both of which play an important role in wind farm power production. In order to test the control strategy, it is implemented in a large-eddy simulation (LES) model of an 84-turbine wind farm using the actuator disk turbine representation. Rotor-averaged velocity measurements at each turbine are used to provide feedback for error correction. The importance of including the dynamics of wake advection in the underlying wake model is tested by comparing the performance of this dynamic-model control approach to a comparable static-model control approach that relies on a modified Jensen model. We compare the performance of both control approaches using two types of regulation signals, “RegA” and “RegD”, which are used by PJM, an independent system operator in the eastern United States. The poor performance of the static-model control relative to the dynamic-model control demonstrates that modeling the dynamics of wake advection is key to providing the proposed type of model-based coordinated control of large wind farms. We further explore the performance of the dynamic-model control via composite performance scores used by PJM to qualify plants for regulation services or markets. Our results demonstrate that the dynamic-model-controlled wind farm consistently performs well, passing the qualification threshold for all fast-acting RegD signals. For the RegA signal, which changes over slower timescales, the dynamic-model control leads to average performance that surpasses the qualification threshold, but further work is needed to enable this controlled wind farm to achieve qualifying performance for all regulation signals.

scholarly journals Optimal Inertia Reserve and Inertia Control Strategy for Wind Farms

Energies ◽  
2020 ◽  
Vol 13 (5) ◽  
pp. 1067
Author(s):  
Youming Cai ◽  
Zheng Li ◽  
Xu Cai
Keyword(s):  
Wind Turbine ◽  
Wind Power ◽  
Control Strategy ◽  
Wind Farm ◽  
Power Grid ◽  
Wind Farms ◽  
Exit Point ◽  
Inertia Control ◽  
The Impact ◽  
Inertia Response

It is important to reduce the impact of the high penetration of wind power into the electricity supply for the purposes of the security and stability of the power grid. As such, the inertia capability of wind farms has become an observation index. The existing control modes cannot guarantee the wind turbine to respond to the frequency variation of the grid, hence, it may lead to frequency instability as the penetration of wind power gets much higher. For the stability of the power grid, a simple and applicable method is to realize inertia response by controlling wind farms based on a high-speed communication network. Thus, with the consideration of the inertia released by a wind turbine at its different operating points, the inertia control mechanism of a doubly-fed wind turbine is analyzed firstly in this paper. The optimal exit point of inertia control is discussed. Then, an active power control strategy for wind farms is proposed to reserve the maximum inertia under a given power output constraint. Furthermore, turbines in a wind farm are grouped depending on their inertia capabilities, and a wind farm inertia control strategy for reasonable extraction of inertia is then presented. Finally, the effectiveness of the proposed control strategy is verified by simulation on the RT-LAB (11.3.3, OPAL-RT TECHNOLOGIES, Montreal, Quebec, Canada) platform with detailed models of the wind farm.

scholarly journals Sensor Fusion and State Estimation of IoT Enabled Wind Energy Conversion System

Sensors ◽  
2019 ◽  
Vol 19 (7) ◽  
pp. 1566 ◽  
Author(s):  
Md. Noor-A-Rahim ◽  
M. Khyam ◽  
Xinde Li ◽  
Dirk Pesch
Keyword(s):  
Renewable Energy ◽  
Wind Turbine ◽  
Wind Turbines ◽  
Wind Farm ◽  
Wind Farms ◽  
Wireless Channel ◽  
The State ◽  
Fusion Algorithm ◽  
Control Center ◽  
Communication Framework

The use of renewable energy has increased dramatically over the past couple of decades. Wind farms, consisting of wind turbines, play a vital role in the generation of renewable energy. For monitoring and maintenance purposes, a wind turbine has a variety of sensors to measure the state of the turbine. Sensor measurements are transmitted to a control center, which is located away from the wind farm, for monitoring and maintenance purposes. It is therefore desirable to ensure reliable wireless communication between the wind turbines and the control center while integrating the observations from different sensors. In this paper, we propose an IoT based communication framework for the purpose of reliable communication between wind turbines and control center. The communication framework is based on repeat-accumulate coded communication to enhance reliability. A fusion algorithm is proposed to exploit the observations from multiple sensors while taking into consideration the unpredictable nature of the wireless channel. The numerical results show that the proposed scheme can closely predict the state of a wind turbine. We also show that the proposed scheme significantly outperforms traditional estimation schemes.

scholarly journals Analysis of Doubly Fed Induction Generators Participating in Continuous Frequency Regulation with Different Wind Speeds Considering Regulation Power Constraints

Energies ◽  
2019 ◽  
Vol 12 (4) ◽  
pp. 635 ◽  
Author(s):  
Tingting Cai ◽  
Sutong Liu ◽  
Gangui Yan ◽  
Hongbo Liu
Keyword(s):  
Power Systems ◽  
Wind Farm ◽  
Frequency Regulation ◽  
Adjustment Coefficient ◽  
Rotor Speed ◽  
Wind Speeds ◽  
Power Constraints ◽  
Bidirectional Regulation ◽  
Continuous Frequency ◽  
Doubly Fed

Wind turbines (WTs) participate in frequency regulation, which is one of the means to solve the problem of inadequate regulation capacity in power systems with a high proportion of renewable energy. The doubly fed induction generator (DFIG) can reserve part of power to achieve bidirectional regulation capability through rotor over-speed and increasing pitch angle. In this paper, it is pointed out that the available bidirectional regulation power of the WT is constrained by the maximum regulation power under the rotor speed regulation. The regulation power constraints under the pitch regulation considering the time scale are calculated. The adjustment coefficient of WT participating in frequency regulation is designed. Considering the regulation power constraints, the frequency difference interval in which the WT can provide the regulation power according to the adjustment coefficient is analyzed. The rotor speed and pitch coordinated control strategy of DFIG with different wind speeds is designed. Based on 24-hour measured data from a wind farm, the power constraints and their effects of WTs in the wind farm participating in frequency regulation are verified by simulation. The regulation power of the wind farm, frequency quality, and wind power utilization under the different control strategies are analyzed. The results show that the effects of bidirectional power constraints must be taken into account when evaluating the effectiveness of WTs in continuous frequency regulation.

Study on Megawatt-Class Wind Turbine Hydraulic System and its Materials

2012 ◽  
Vol 531 ◽  
pp. 617-621
Author(s):  
Hong Mei Sun ◽  
Ming Gao
Keyword(s):  
Wind Turbine ◽  
Hydraulic System ◽  
Wind Farm ◽  
Wind Farms ◽  
Fast Response ◽  
Climatic Conditions ◽  
Materials Selection ◽  
Technical Parameters ◽  
Actual Use ◽  
Use Of Assessment

Compared with electric pitch, hydraulic pitch has the merits— fast response, stable pitch, safe , reliable, etc., and is generally used in the megawatt-class wind turbine. The problems faced by the localization process of the hydraulic system, considering most of our wind farms of the unique climatic conditions and use characteristics, the localization of technical parameters of the hydraulic system and component materials selection requirements and design methods are put forward. Wind turbine pitch hydraulic system with independent intellectual property rights is developed, and is passed the actual use of assessment of the wind farm

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