High Wind Power Penetration Research Articles

Dynamic volatility spillover effects between wind and solar power generations: Implications for hedging strategies and a sustainable power sector

Large-scale wind and solar development is impeded severely by their inherent volatilities. This study applies a novel approach to reduce the renewable investment risks from the production perspective, although there are many related studies from the financial market perspective. Using daily data from the Gansu province of China between 2013 and 2018 based on a VAR-GARCH model, we first find that wind and solar power generation are volatile, negatively correlated, and exhibit strong time varying spillover effects . We then apply three different approaches to calculate the hedge ratios and optimal capacity portfolios of wind and solar in Gansu. The result from the best MVP approach shows that the optimal capacity weights are 28.3% for wind and 71.7% for solar. This study sheds light on designing a joint development strategy to reduce security risks and integration costs during transition toward a low carbon power sector. • A novel approach is applied to reduce the risks of high penetration of wind and solar power. • Time-varying volatility spillovers between wind and solar production are examined. • A significantly negative dynamic correlation between wind and solar is empirically demonstrated. • The complementarity relationship between wind and solar is employed to construct their optimal capacity weights.

Dynamic Economic Dispatching Considering Time-Coupling Spinning Reserve Response Risk with High Penetration of Wind Power

Aiming at the problem that the current dynamic economic dispatch (DED) fails to consider the response risk of spinning reserve caused by the fluctuation and uncertainty of wind power, we work out a DED problem considering time-coupling spinning reserve response risk while the stochasticity and variability arising from RESs are taken into consideration. The developed framwork unified the response risk of reserve caused by forced shutdown of the unit into the response risk caused by time coupling. The expected customer interruption cost (ECOST) and the expected abandoned wind cost considering this reserve response risk are added to the objective function. While seeking the minimum objective function, the system is automatically configured with suitable reserve to ensure the consistency of the system’s response risk in each period. An improved multi-universe parallel quantum genetic algorithm was used to solve the model. Numerical examples and analysis prove the effectiveness and feasibility of the proposed method.

Decentralized Grid-Forming Control Strategy and Dynamic Characteristics Analysis of High-Penetration Wind Power Microgrids

As wind power generation transits from centralized development mode to decentralized on-site consumption mode, microgrid (MG) can provide an efficient solution for wind power integration into the distribution network. However, the high-penetration wind power MG is the typical weak power grid system. The traditional wind turbine generator (WTG) participates in system frequency regulation through grid-following current source, which relies on the phase-locked loop for voltage phase synchronization and is unable to provide strong frequency support in weak power grid conditions. To fill this gap, this paper presents a decentralized grid-forming control strategy of high-penetration wind power MG. A wind power adaptive dynamic droop mechanism considering wind energy characteristics and rotor speed dynamic is proposed, cooperating with the implementation of wind maximum power point tracking (MPPT) for economical operation. A detailed small-signal model for voltage source wind power-based system considering electromechanical transients and adaptive droop mechanism is developed. The dominant modes are figured out and the critical control parameters are established and optimized. The proposed wind power adaptive droop mechanism can effectively provide frequency regulation and robust control performance. Theoretical analysis, time-domain simulation results and hardware-in-the-loop experiments under various scenarios verify the feasibility and effectiveness of the proposed strategy.

State-of-the-Art Using Bibliometric Analysis of Wind-Speed and -Power Forecasting Methods Applied in Power Systems

The integration of wind energy into power systems has intensified as a result of the urgency for global energy transition. This requires more accurate forecasting techniques that can capture the variability of the wind resource to achieve better operative performance of power systems. This paper presents an exhaustive review of the state-of-the-art of wind-speed and -power forecasting models for wind turbines located in different segments of power systems, i.e., in large wind farms, distributed generation, microgrids, and micro-wind turbines installed in residences and buildings. This review covers forecasting models based on statistical and physical, artificial intelligence, and hybrid methods, with deterministic or probabilistic approaches. The literature review is carried out through a bibliometric analysis using VOSviewer and Pajek software. A discussion of the results is carried out, taking as the main approach the forecast time horizon of the models to identify their applications. The trends indicate a predominance of hybrid forecast models for the analysis of power systems, especially for those with high penetration of wind power. Finally, it is determined that most of the papers analyzed belong to the very short-term horizon, which indicates that the interest of researchers is in this time horizon.

Adaptive under‐frequency load shedding scheme for power systems with high wind power penetration considering operating regions

With the ever-increasing penetration of wind power into power systems, wind turbine generators (WTGs) are required to provide frequency regulation services to maintain the system frequency stability. For variable-speed WTGs, the adaptability of dissimilar frequency control strategies to different operating regions is distinct, which impacts the system frequency response. However, existing under-frequency load shedding (UFLS) schemes do not take that impact into account, causing improper load shedding after a loss of generation. To this end, this paper proposes an adaptive UFLS scheme for power systems with high wind power penetration considering operating regions. Based on the WTG operating characteristics in different operating regions, the appropriate frequency control strategy for each operating region is elaborated. The simplified frequency response model of the power system considering WTGs participating in frequency regulation is then established. According to the WTG active power response characteristics in different operating regions, the impact of WTGs participating in frequency regulation on UFLS is analysed. Accordingly, the method of accurately estimating the magnitude of the power deficiency and calculating the amount of load to be shed is proposed. Finally, the feasibility and effectiveness of the proposed UFLS scheme are verified through simulations on the IEEE 39-bus test system.

A Novel Continuous Permutation Method for Wind Power Correlation Analysis

Wind speeds in geographically adjacent areas are highly correlated, which correspondingly leads to wind power correlation. It is essential to consider the wind power correlation for steady-state related calculations in the modern power system with high wind power penetration. This short article presents a novel continuous permutation method for wind power correlation analysis. With the novel eigen-permutation, the proposed method is applicable to tackle the correlation analysis even the correlation matrix of random variables is not positive definite. A continuous permutation is then proposed to reduce the permutation deviation and, hence, to reduce the error of steady-state related calculations. Simulation results show the effectiveness of the proposed method in dealing with the nonpositive definite correlation matrix of the wind speeds. Also, compared to the traditional methods, the proposed method achieves more than an 80% reduction of the general error in the correlation analysis, which also contributes to higher accuracy in the power flow calculation.

A novel frequency response analysis model applicable to high-penetration wind power grid

The decoupling relationship and low inertia characteristics of wind turbine generator system (WTGS) make the system frequency response more complex. In order to evaluate the frequency stability of high-penetration wind power grid, it is significant to establish an exactly frequency response analysis model. Due to the features of wide spatial distribution and large number of WTGS in the power grid, the wind speed and actual operating state faced by WTGS in different regions have obvious discrepancy, which makes the traditional frequency response models that merely considers the single operating state of WTGS have evident limitations. Therefore, in order to consider the discrepancy of frequency regulation characteristics caused by the spatial dispersion of WTGS, an improved frequency response modeling method which can take into account the frequency regulation characteristics of multiple wind speeds is proposed. This method uses small signal analysis theory and fuzzy control method to construct an improved equivalent aggregation model of WTGS. Combining this model with the typical system frequency response (SFR) model, a novel frequency response model considering different wind conditions and different frequency regulation characteristics of WTGSs is established. Finally, an improved IEEE-118 bus system is used for case analysis to verify the correctness and superiority of the proposed method for high-penetration wind power grid.

Dynamic spatio-temporal correlation and hierarchical directed graph structure based ultra-short-term wind farm cluster power forecasting method

Accurate wind farm cluster power forecasting is of great significance for the safe operation of the power system with high wind power penetration. However, most of the current neural network methods used for wind farm cluster power forecasting have the following three problems: (1) lack of consideration of dynamic spatio-temporal correlation among adjacent wind farms; (2) simultaneously forecasting all wind farms’ power to obtain the total power will produce numerous error sources; (3) ignoring the causal relationship among input variables. Therefore, to solve the above problems, this paper proposes an ultra-short-term wind farm cluster power forecasting method based on dynamic spatio-temporal correlation and hierarchical directed graph structure. Firstly, three different types of nodes (wind speed nodes, wind power nodes, and target node) and input samples are defined, and then the spatio-temporal correlation matrices that can describe the correlation of adjacent wind farms are also calculated. Secondly, directed edges are defined to connect different nodes in order to obtain the hierarchical directed graph structure. Finally, this graph structure with dynamic spatio-temporal correlation information is used to train the forecasting model. In case study, compared with other benchmark methods, the proposed method shows excellent performance in improving accuracy of power forecasting.

Coordinated Control of Wind Energy Conversion System during Unsymmetrical Fault at Grid

High penetration of wind power into the grid necessitates the coordinated action of wind energy conversion systems and the grid. A suitable generation control is required to fulfill the grid integration requirements, especially during faults. A system using a pair of voltage source converters with a squirrel cage induction generator coupled to a wind turbine is proposed to provide fault ride-through during grid faults. A threefold action is used for providing the effective fault ride-through via coordinated action of the machine side and the grid side converter. The entire wind energy conversion system is controlled such that the wind turbine remains connected even during the faults. To implement the threefold action: (i) A decoupled current controller is placed in the grid side converter, which separately controls the positive and negative sequence currents arising during faults. The grid side converter controller is capable of eliminating the double frequency oscillations at the dc-link voltage and, hence, real power, which arises during the unsymmetrical faults; (ii) Reactive power injection is additionally provided by the grid side converter for better grid support; and (iii) The vector control technique is used in machine side converter along with the droop control to adjust the generator speed and the torque resulting in actuation of the pitch control mechanism to limit power generation without shutdown of the turbine.

Inertia Optimization Control and Transient Stability Analysis of Wind Power Grid-Connected System

The virtual inertia control effectively makes up for the insufficient inertia caused by the high penetration wind power grid connection. However, it has an impact on the mechanical part of the wind turbine and greatly increases the difficulty of the dynamic stability analysis of the system, resulting in limited engineering practicability. Therefore, the state equation of the wind power grid-connected system is established in this paper, and the influence of virtual inertia control on wind turbine shafting oscillation is analyzed based on the small-signal theory. Secondly, the nonlinear extended disturbance observer is designed as the compensation signal of inertia control to improve its dynamic stability supportability. Based on the integral manifold method, the shafting model of the wind turbine is reduced, and the transient energy function of shafting is established, which provided the basis for the design of the shafting stability controller. Finally, a grid-connected wind power system with high permeability is installed, and the results demonstrate that under the proposed control strategy, the swing stability of power angle is significantly improved, and the wind turbine shafting oscillation is suppressed.

Two-Stage Chance-Constrained Coordinated Operation of an Integrated Gas–Electric System

Under the background that the high penetration of renewable energy generation, which mainly consists of wind power, will have a significant impact on electric power systems due to the volatility and uncertainty of renewable energy, energy systems with gas–electric coupling and interconnections have been widely studied to accommodate renewable energy generation. This paper proposes a two-stage chance-constrained coordinated operation model of an integrated gas–electric system and fully considers the uncertainty and high penetration of wind power. The Taylor series expansion method is used to linearize the Weymouth gas flow equation of a natural gas system and finally obtains a mixed integer linear programming model. Case studies show the effectiveness of the integrated energy system for peak shaving, valley filling, and promoting wind power accommodation. The proposed model ensures the consumption of wind power generation and also reduces the operation cost by about 0.7%.

Reactive Voltage Control Strategy for PMSG-Based Wind Farm Considering Reactive Power Adequacy and Terminal Voltage Balance

To improve the ability of the power system to accommodate high penetration wind power, wind turbines (WTs) need to realize the mode transformation from grid-following to grid-forming, thus actively participating in the voltage regulation of the power grid with a high proportion of wind power. In this work, a reactive voltage control strategy for wind farms considering reactive power adequacy and terminal voltage balance is proposed. Firstly, the expression of the maximum reactive power regulation capacity of WT, namely reactive power adequacy, is derived under the complete wind condition based on the mathematical model and operating characteristics of WT, to study the influence of wake effect on reactive power adequacy of a wind farm. Then, the point of common coupling (PCC) voltage and terminal voltage are expressed analytically based on the radiative topology equivalent model of a wind farm, to analyze the influence of electrical distance on active power loss of wind farm. Finally, the calculation method of the adaptive gain coefficient of WT is put forward, which comprehensively considers the input wind speed and the electrical distance, to regulate the PCC voltage and terminal voltage simultaneously. The comprehensive effectiveness of the proposed strategy is demonstrated on a permanent magnet synchronous generator (PMSG)-based wind farm integration simulation model. While supporting the PCC voltage, the proposed strategy maintains the balance of the terminal voltage in the wind farm, thereby improving the friendliness of wind power grid connection.

Day-ahead scheduling strategy for integrated heating and power system with high wind power penetration and integrated demand response: A hybrid stochastic/interval approach

The accommodation of wind energy is restricted due to the heat-led operation mode of CHP units. Comprehensive utilization of multi-energy coordinated supply and integration of wind energy, is deemed as an efficient solution for improving energy conservation and operational flexibility. Therefore, a novel hybrid stochastic/interval optimization for an integrated heating and power system (IHPS) day-ahead scheduling is proposed in this paper. Considering the bilateral uncertainties that exist on both sides of supply and demand, the scenario-based stochastic analyze is adopted to generate a set of possible scenarios for describing uncertainties of electrical and thermal loads. Also, the information gap decision theory (IGDT) is proposed to deal with the severe uncertainty caused by high wind power penetration. For the operation of district heating network (DHN), temperature dynamics and transmission delay are studied to exploit the heating system as a virtual storage for managing the dispatch of wind power. To further improve the system economic, the concept of price-based integrated demand response (IDR) under the background of multi-energy coupling is also introduced and the characteristics of energy substitution and load timing transfer are modeled. Simulation results show that the benefits of the proposed method for enhancing the system operation flexibility.

Increasing or Diversifying Risk? Tail Correlations, Transmission Flows and Prices across Wind Power Areas

As wind power costs have declined, capacity has grown quickly, often times in adjacent areas. Price and volatility risk from wind power’s intermittency can be mitigated through geographic diversification and transmission. But wind power generation has a fat-tailed and right-skewed distribution. In this article we investigate how geographic diversification of wind power and the effect of wind power on market prices varies across the distribution of production. In a case study from Denmark and Sweden, we show that during tail-end production periods, correlations between areas increase substantially as does congestion in the transmission network. This leads to highly non-linear price effects. The marginal effect of wind power on the local prices is shown to be substantially higher at the 10th decile of wind power production. This has implications for valuation models of wind power projects and for operations of electricity markets with high penetrations of wind power.

Deep Learning Based Model-Free Robust Load Restoration to Enhance Bulk System Resilience With Wind Power Penetration

This paper proposes a new deep learning (DL) based model-free robust method for bulk system on-line load restoration with high penetration of wind power. Inspired by the iterative calculation of the two-stage robust load restoration model, the deep neural network (DNN) and deep convolutional neural network (CNN) are respectively designed to find the worst-case system condition of a load pickup decision and evaluate the corresponding security. In order to find the optimal result within a limited number of checks, a load pickup checklist generation (LPCG) algorithm is developed to ensure the optimality. Then, the fast robust load restoration strategy acquisition is achieved based on the designed one-line strategy generation (OSG) algorithm. The proposed method finds the optimal result in a model-free way, holds the robustness to handle uncertainties, and provides real-time computation. It can completely replace conventional robust optimization and supports on-line robust load restoration which better satisfies the changeable restoration process. The effectiveness of the proposed method is validated using the IEEE 30-bus system and the IEEE 118-bus system, showing high computational efficiency and considerable accuracy.

Investigation of spatial correlation on optimal power flow with high penetration of wind power: A comparative study

Spatial correlation is a critical characteristic of adjacent wind farms, but its importance is always ignored in wind power modeling, further resulting in modeling bias. In order to investigate the necessity of involving spatial correlation and validate whether it has effects on power system, this paper proposes a method to construct the spatial correlation model and applies it into an IEEE test system. Specifically, a 7-dimensional t-copula method is used to capture the spatial dependence by forming a multi-variable distribution function, from which different scenarios are generated. Subsequently, a k-means clustering method is used for scenario reduction. As for the case study, a modified IEEE 39-bus test system with 7 wind farms deriving from the AEMO dataset is utilized to conduct optimal power flow under the circumstance with and without considering spatial dependence. Based on this, the cost of generation, including traditional fuel cost and levelized cost of wind power is obtained. Through comparing the cost results and analyzing the gap, it can be concluded that the spatial correlation has significant effects that when levelized cost of wind power exceeds a particular value, the generation cost can be greatly underestimated if ignoring spatial correlation with a high penetration of wind power.

A Group-Based Droop Control Strategy Considering Pitch Angle Protection to Deloaded Wind Farms

To promote the frequency stability of a system with high penetration of wind power integrated into it, this paper presents a systematic frequency regulation strategy for wind farms (WFs). As preparation for frequency response, a coordinated deloading control (CDC) scheme combining the over-speed control (OSC) and the pitch angle control (PAC) methods is proposed for wind turbine generators (WTGs) to preserve power reserve. The novelty lies in the consideration of high wind speed situations and pitch angle protection. Then, a group-based droop control (GBDC) scheme is proposed for a WF consisting of WTGs with the CDC. In this scheme, WTGs are divided into two groups for different controls. To improve the frequency response performance and ensure stable operation, the droop coefficients of the WF, groups, and all WTGs are determined according to their frequency regulation capabilities (FRCs). Moreover, pitch angle protection during the frequency response process is considered in this scheme. The effectiveness of the GBDC scheme is verified by comparing it with several existing droop control schemes in various situations.

Distributionally robust optimal dispatch in the power system with high penetration of wind power based on net load fluctuation data

The power system with high penetration of wind power faces a great challenge for system dispatch due to the high volatility and intermittency of the wind power. This work proposes a day-ahead optimal dispatch model which is formulated for a power system with thermal power, hydropower, and controllable load as dispatchable resources. According to the anti-peak regulation, the system dynamic power regulation margin model considering adjacent time periods is established to address the uncertainty in the fluctuation rate of net load power, and to sufficiently use the dispatchable resources to reduce wind curtailment. However, in some circumstances, curtailing wind has to be considered to ensure secure operation of the system and maintain the economic goal from the total cost point of view. The risk of curtailing wind is formulated using conditional value at risk (CVaR), and is minimized as part of the total operating cost. Another objective function of the proposed dispatch model is to maximize the power regulation margin. Uncertainty in the fluctuation rate of net load power is modelled for different weather conditions using moment-based ambiguity set. The moment information is obtained from large amount of historical data using clustering methodologies. The proposed optimal dispatch model with uncertainty and CVaR formulation is reformulated and solved under the distributionally robust conditional value at risk (DRCVaR) framework. The model is transformed into a semi-definite programming problem through the duality theory and can be solved efficiently by commercial solvers. Simulation results show that the proposed dispatch model can effectively strengthen wind power absorption, ensure secure operation, and improve the robustness of the dispatch strategy facing the uncertainty from the wind power.

Output fluctuations minimization of wind integrated hybrid power system using electronic coordinated control of governor and blade

Using electronic coordinated control of governor and blade in the wind integrated hybrid power system, this study evaluated four proposed techniques for minimizing output fluctuations owing to high wind power penetration. Four cases were investigated for simulation analysis in this study. The power system frequency and energy generation were used as indexes to evaluate the best-proposed techniques. The control of all wind turbine blade angles was demonstrated using a constant and variable reference power generating technique. In terms of wind farm output power characteristics, grid frequency fluctuations, and wind farm energy levels, case 2 performed better than other suggested systems (cases 1, 3, and 4). Frequency deviations were kept to a minimum of ±0.2 Hz. The performance of the power system with higher wind power penetration was investigated using a numerical analysis employing a multi-machine power system model. The real wind speed data were recorded on Hokkaido Island, Japan.

A Study on Frequency Stability and Primary Frequency Response of the Korean Electric Power System Considering the High Penetration of Wind Power

The high penetration of wind power decreases the system inertia and primary frequency reserve while replacing the conventional synchronous generators (SGs). Therefore, if the system operator does not take appropriate action on the remaining generation units (GUs) operation, high penetration of wind power will aggravate the frequency stability. To solve this problem, wind power plants (WPPs) may provide the inertial response and primary frequency response (PFR) to support the frequency stability. However, due to the variability of renewable energy, WPPs may not provide adequate frequency response whenever it is required. This paper proposes an algorithm to determine the operation of GUs to provide appropriate PFR for a power system with high penetration of wind power. Through the proposed algorithm, it calculates the required PFR to restore the decreased frequency stability caused by the high penetration of wind power. Then, while considering the available PFR from WPPs, it redetermines the droop coefficient of SGs governor to provide the sufficient PFR to recover the frequency stability. Finally, the effectiveness of the proposed algorithm is verified on the practical Korean electric power system.