Wind Integrated Power System Research Articles

The influence of demand response on wind-integrated power system considering participation of the demand side

Demand response (DR) can serve as virtual reserve to cope the impact of wind power on system reliability. This paper describes a new approach to investigating the impact of DR in a wind-integrated power system from the perspective of generation adequacy. First, owing to the uncertainty of human behavior, DR cannot be trusted to provide a sufficient reserve. To characterize the associated uncertainty, we use a value function of prospect theory to depict the risk attitude of the customer. Based on this function, we propose a variant Roth-Erev algorithm to characterize the uncertainty of customer participation and measure the available capacity of DR. Second, we introduce the available capacity of DR into operational constraints and construct a DR scheduling model to reduce system operation costs. Finally, based on the uncertainty characterization of DR and a scheduling model, we extend the traditional assessment procedure using Monte-Carlo simulation and propose a novel procedure to evaluate the impact of DR on generation adequacy. Simulation results show that introducing DR can improve the generation adequacy of a wind-integrated power system. The proposed DR scheduling method reduces the operational cost and improves generation adequacy.

A Novel Wind Farm Control Strategy to Mitigate Voltage Dip Induced Frequency Excursion

In this paper, a novel wind farm control strategy is proposed to mitigate voltage dip induced frequency excursion in wind integrated power systems. In the proposed control strategy, conventional fixed reactive/active current injection priority is replaced by an optimum adaptive priority based reactive and active current injection. The control problem is formulated as a binary integer optimization problem, which simultaneously minimizes active power shortfall from wind generation during fault and complies with grid code requirements. Detailed wind farm model and wake effect are taken into consideration to achieve realistic response from the wind farm, while IEC 61400-27-1 wind turbine generator model is adopted for wind turbine modeling. Dynamic model of the test system has been developed in DIgSILENT PowerFactory, while the static model is also developed in MATLAB, and cosimulation platform has been used to test and validate the proposed control strategy. The proposed control strategy is applicable to variable speed wind turbine-based wind farm.

Analysis of the Propagation Characteristic of Subsynchronous Oscillation in Wind Integrated Power System

This paper proposes oscillation propagation factors to analyze power oscillations caused by the interharmonics of doubly fed induction generators (DFIG) at different points in the power system. First, a dynamic model of the DIFG is built, including the asynchronous generator, its transmission system, converters and the control systems. Then, the state space expression is formed by deducing the input and output matrices. From this, the oscillation propagation factor is proposed and denoted to exhibit the propagation mechanism of interharmonics in the view of frequency domain, by deducing the multi-input-multi-output transfer functions matrix. Along with this, the sensitivity of propagation is calculated for adjusting the parameters to block the oscillation propagating path. Finally, the modified four machine system with two DFIGs and the New-England 39 bus system with two DFIGs is used as a test system to verify the effectiveness of the oscillation propagation factor. From this the simulation results demonstrate that the subsynchronous interharmonics of DFIGs injected into the grid will propagate to the different points of the system and results in oscillation of the power. The oscillation propagation factor could quantize the oscillation magnitude propagating from one point to other point in the wind integrated power system.

Electric vehicle mobility and optimal grid reconfiguration as flexibility tools in wind integrated power systems

This paper investigates the optimal grid reconfiguration (OGR) strategy in the smart grids with the random behavior of the many electric vehicle mobility (EVM) fleets and wind energy uncertainty. The increased utilization of EVMs in the power system with stochastic volatile behavior along with the high penetration of wind energy sources (WESs) can create new challenges in the system that will affect the system flexibility greatly. Here, the electric vehicle is mobile and there are distributed devices with deferrable options to supply energy at various times and locations. Accordingly, in this paper, the OGR is used as the remedial action to enhance the system flexibility to handle uncertainties. The main aim of this paper is to increase system flexibility and reduce expected operating costs by the coordination between EVM fleets, OGR and WESs’ uncertainty. Beside, this paper provides a novel method to evaluate the system flexibility while explicitly considering thermal unit generation and the EVM fleets. Numerical tests demonstrate the effectiveness of the proposed approach for analyzing the impact of EVM fleets on the system flexibility and hourly wind energy dispatch.

Social welfare maximisation of market based wind integrated power systems by simultaneous coordination of transmission switching and demand response programs

The non-preventable ever-increasing rate of wind power generation in market-based power systems faces the operators with challenging situations for making optimal decisions. So, it is essential to equip the operators with applicable control strategies and further corresponding control facilities. Moreover, the high-priority of cheap wind power utilisation increases the probability of transmission lines congestion. Therefore, different solutions such as transmission switching (TS) and demand response (DR) programs have been recently introduced to manage the intermittent wind power generations. Accordingly, this study addresses the social welfare maximisation problem with coordinated control of TS and DR facilities to handle the regarding uncertainties using yet another linear matrix inequality parser (YALMIP). In fact, rapid algorithm and powerful employed solvers as well as simplicity of use, make YALMIP a practical modelling and optimisation toolbox. In this respect, the MOSEK solver is preferred by YALMIP to solve the proposed mixed integer linear programming problem. In addition, wind power uncertainty is modelled using the discrete-time Markov chain approach and optimisations are performed on the 8-bus and the large-scale IEEE 118-bus test systems. Results show that the proposed control strategy is highly capable of maximising social welfare by determining the optimal control commands in a real-time manner.

Accommodation capability assessment of high‐voltage direct current with a large‐scale wind power integration system based on risk constraints of sub‐synchronous oscillation

Accommodation capability assessment of high‐voltage direct current with a large‐scale wind power integration system based on risk constraints of sub‐synchronous oscillation

Frequency Regulation of Wind Integrated Power System using Dual Mode Fuzzy

Owing to the increase in electrical load demand the dimension of interconnected energy system is increasing day by day and getting more complex with power injection from renewable technologies such as wind energy in order to supply and meet rising energy demands as well as to limit the dependency on conventional sources of power generation. However, the rising trends towards power generation via wind power will cause the challenging task to maintain the equilibrium between the power generation and load demand and hence to keep the power system frequency to standard value. Hence, in this work a new control design based on switching logic having additional fuzzy intelligence is proposed for wind integrated energy system. In addition, it is also tried to reduce the rule base for proposed design and hence to reduce the complexity of fuzzy based design. The proposed design is tested for standard load change and the results are matched with fuzzy PI and with natural response of the system to show the power of the proposed design. Further, it is also shown that doubly fed induction generator (DFIG) wind integrated system with proposed control design have the capability to improve the standard frequency profile in case of sudden change in the power demand of the energy system and hence it helps to deliver the required power to the modern clients.

Interval based robust chance constrained allocation of demand response programs in wind integrated power systems

This study presents an interval based robust chance constrained (IBRCC) optimisation model for allocating demand response program to effective buses of the power systems considering wind uncertainty and equipment failures. In the proposed formulation, an interval based robust approach is applied to evaluate the highest uncertainty spectrum of the wind power generation that the power system can tolerate. Accordingly, to cope with the uncertainty sources, chance-based constraints are implemented. In the proposed IBRCC optimisation framework, the level of the optimal solution robustness is probabilistically maximised subject to a set of operational constraints. Besides, to facilitate the massive integration of uncertain wind generation and to mitigate congestion in the transmission grid, an efficient allocation, and scheduling scheme of demand response programs is proposed. The proposed model is evaluated on the IEEE 24 bus system.

Integrated resource expansion planning of wind integrated power systems considering demand response programmes

Here, an optimisation framework is proposed for integrated resource expansion planning (IREP) including conventional generation units, wind generation units, and transmission lines while taking into account the role of demand response program (DRP) aggregators. This problem is a bi-level optimisation problem. In the upper-level problem, the objective function is to maximise the profit for each resource, that is, the generation company (GENCO), wind generation company (WINDCO), and transmission company (TRANSCO) as well as the DRP aggregator. Also, the lower-level problem considers a market model with the participation of private GENCOs, WINDCOs, TRANSCOs, and DRP aggregators. The lower-level problem minimises energy cost subject to AC power flow (PF) equations, power network limitations, pollution constraint, GENCO, WINDCO, TRANSCO constraints, and technical limitations of DRPs. Here, the lower-level problem is non-linear and non-convex. Accordingly, to facilitate the solution of the proposed bi-level optimisation problem, a linear model is proposed. Then, the proposed bilevel optimisation problem is converted into an integrated single-level one using the Karush-Kuhn-Tucker (KKT) conditions. Eventually, a mixed-integer linear programming (MILP) model is proposed. The proposed method is applied to the IEEE 6-bus and the IEEE 30-bus test systems, and finally, the capabilities of the proposed scheme are evaluated.

Lagrange interpolating polynomial–based deloading control scheme for variable speed wind turbines

In this paper, an adaptive deloading scheme is proposed for enhancing the output power from the deloaded variable speed wind turbine generator (VSWTG). The deloading operation of a wind turbine generator (WTG) creates a reserve power margin at its maximum power point operation that can be utilized for stabilizing the frequency deviations of the power system during system contingencies. The output power of the deloaded WTG is regulated dynamically during the system events for improving the primary frequency response. The nonlinear power characteristic curve of the wind turbine is treated with a Lagrange interpolating polynomial (LIP) technique for increasing the output power of the deloaded WTG. Moreover, LIP-based deloading of WTG contributes a better frequency dynamic performance during different power system scenarios such as the fluctuations in wind speed and change in load than the traditional control scheme. Due to the smoothing in frequency response with a faster settling time, the proposed LIP-based deloading scheme can comply with the necessities of the grid codes of the wind-integrated power system. The real-time hardware-in-the-loop (HIL) simulation results are exhibited to validate the proposed deloading methodology in support of the theory. The HIL platform is realized by using the real-time simulator manufactured by OPAL-RT Technologies.

Enhancing voltage stability and LVRT capability of a wind-integrated power system using a fuzzy-based SVC

The static var compensator (SVC) has widespread applications in voltage regulation and stability improvement of power systems. This paper studies the SVC performance in a single machine (doubly-fed induction generator (DFIG) employed in a wind farm) infinite bus (SMIB) system. The SVC is employed to improve the voltage stability of the system and the low voltage ride-through (LVRT) capability of the wind farm. To enhance the effectiveness of the SVC, a supplementary fuzzy-based controller (FC) is proposed and is integrated into the SVC controller. The use of the proposed FC leads to the increasing the accuracy of the SVC controller that results in improving its performance in both transient and steady state. By using the proposed controller, the steady state voltage is enhanced and the maximum voltage drop under fault situations is decreased. Less voltage drop after the fault occurrence using the proposed FC results in improving the LVRT capability and makes the wind farm able to meet the grid code requirements in a larger range of load variations in the system. Using extensive simulations in MATLAB/Simulink, the effectiveness of the proposed method in improving the voltage stability and LVRT capability is validated and its effects on the performance of the DFIG-based wind turbine are studied. Three different cases are investigated in the system simulation, in which by using the proposed FC, the steady state voltage error at the load bus and the maximum voltage drop after the fault occurrence at the generator (wind farm) bus are decreased by 74.44% and 25.16% on average, respectively.

Fault direction identification for wind power integration system

Fault direction identification for wind power integration system

Robust Centralized Fixed Order Wide Area Damping Controller for wind integrated power system

This paper presents a robust MIMO centralized fixed order wide area damping controller with reserve input/output control signals to damp inter-area oscillation for wind integrated power system. The proposed approach is robust with respect to multi-model uncertainty, fixed and propagated time delay. Multi-model uncertainty in wind integrated power system comes from different percentage of wind penetration as well as replacing synchronous generator with wind turbine generators. This centralized controller has some reserve input and output channels to deal with possible communication dropouts. It is based on loop shaping. The method is applied to a two-areas, four machines system under multi-model uncertainty, uncertain time delay, etc..

Multi-Timescale Active and Reactive Power-Coordinated Control of Large-Scale Wind Integrated Power System for Severe Wind Speed Fluctuation

Wind speed fluctuations are extremely easy to cause the voltage change frequently. The existing voltage control methods are lacking in adjustment range and response speed. When wind speed fluctuates substantially or rapidly, voltage exceeding limit and the resulting grid safety problems cannot be avoided. Therefore, reasonably distributing and utilizing the reactive power of variable speed wind turbines in the whole network are an inevitable choice. However, the controllable reactive capacity of wind turbines is limited by converter capacity and active power, and thus, the grid demand may not be met. A new idea of active and reactive power-coordinated control for preventing voltage exceeding limit due to wind speed fluctuations was proposed. The effects of wind speed fluctuations on voltage were analyzed, and the controllable reactive capacity of variable speed wind turbines under wind speed fluctuations was studied. The relationship between voltage and the active and reactive power of wind farms was deduced. The theory and method of active and reactive power coordinated control before wind speed fluctuations were proposed based on the model predictive control theory. The control model based on multi-timescale was established. Finally, it was verified that the method can solve the voltage problems and maximize the system economy.

Adaptive Damping Control Strategy of Wind Integrated Power System

Random variation of grid-connected wind power can cause stochastic variation of the power system operating point. This paper proposes a new scheme to design an adaptive damping controller by tracking the variation of system operating points and updating the controller’s functions to achieve a robust damping control effect. Firstly, the operating space is classified into different modes according to the classification of wind power outputs. Multiple power system stabilizers (PSSs) are then designed. Secondly, the method of optimal classification and regression decision tree (CART) is utilized for classifying subspaces of system operating point and it is proposed that the on-line measurements from wide area measurement system (WAMS) are used for tracking the dynamic behaviors of stochastic drifting point and thus guide the updating of appropriate PSSs be switched on adaptively. A 16-generator-68-bus power system integrated with wind power is presented as a test system to demonstrate that the adaptive control scheme by use of the CART can damp multi-mode oscillations effectively when the wind power output changes.

Non-linear sliding mode control for frequency regulation with variable-speed wind turbine systems

This paper presents a new control strategy to minimize mismatch between the generations and loads in the wind integrated power system. This in turn enhances the integration level smoothly and reduces frequency deviation in the system. The proposed control strategy is able to establish better dynamic response and provide better coordination between conventional two-area and wind power systems. The said objective is achieved by designing a non-linear sliding mode control in two-area thermal system, in addition with droop control and modified pitch angle control for wind generator to provide frequency support. The proposed controller has ability to vary closed-loop system damping property according to uncertainties and load disturbances and thus ensures asymptotic stability. The wind power output and frequency regulation remain insensitive to gusts, changes in wind speed and as well as inertia. Several simulations are performed on two-area with wind integration and IEEE 39 bus system to illustrate the effectiveness of the proposed controller design.

Active control method of large‐scale wind integrated power system with enhanced reactive power support for wind speed fluctuation

A regional power grid containing high-density wind power is generally connected to a load centre through long-distance transmission lines. Voltage problems, caused by wind speed fluctuation, in the sending-end grid have become increasingly serious. The variable speed wind turbine has been used to compensate the deficit in reactive power. However, the available methods could not meet the requirement because the controllable range of reactive power contributed by wind farms cannot be adjusted. A new idea of reactive power control realised by the active control before wind speed fluctuation was proposed to prevent the voltage variation. Firstly, the influence of wind speed fluctuation on voltage was analysed, and the power controllable range of wind turbines was studied. The principle and strategy of the active control of reactive power were proposed based on the model predictive control theory. Then, the active control model was established according to the system dynamic demand for reactive power. According to wind speed forecasting, the reactive control capability of wind turbine was excavated to meet the grid demand by adjusting active power before wind speed variation, and the reduced active power of wind farms is optimally compensated by thermal powers. Finally, the method was proven to solve voltage problems.

Online load frequency control in wind integrated power systems using modified Jaya optimization

The Jaya optimization algorithm is recognized as a simple and faster population-based heuristic search algorithm. However, due to the absence of algorithm-specified parameter, its performance may degrade in terms of convergence speed and obtain the optimal value for the real-world complex optimization problems which are usually nonlinear and non-differentiable in nature. To deal with the aforesaid scenarios, a modified Jaya optimization algorithm (MJOA) is proposed by considering a weight parameter in the search process. Two methods are proposed on the basis of the selection of weight parameter, one is a linear weight (LW) and the other is a fuzzy logic based mechanism. It is found that MJOA is quite accurate and faster in convergence for complex problems. The proposed MJOA has used for online tuning the controller parameters of automatic generation control (AGC) of wind integrated power system. Further, a frequency deviation tolerance concept is proposed to reduce the number of executions of MJOA. The proposed methodology helps in recovering the frequency excursions of the power system with a faster convergence performance and requirements of less computational burden. Such features are very important in smart-grid operational necessities for improving its stability performance. The real-time simulation studies are carried out on an embedded platform using xPC target board of the wind farm integrated IEEE-39 bus test system.

MPC-based approach for online demand side and storage system management in market based wind integrated power systems

Ever-increasing rate of wind power generation as an uncertain and variable source of energy, face new challenges in power system operation. For this reason, optimal real-time operation of wind integrated power systems in profit based markets considering the effects of probabilistic future variations of wind speed is one of the main concerns of system operators. For this purpose, some solutions such as demand response (DR) programs and energy storage systems (ESS) are widely being used to cover and manage wind generation uncertainty. But some of them such as DR programs can add some extra sources of uncertainty due to unpredictable customer’s behavior. To this end, this paper proposes an online model-based predictive control approach for optimal real-time operation of wind integrated power systems including DR and ESS facilities. Discrete-time manner, re-optimization characteristic, and adaptability are the main features of the proposed MPC method which make it well-suited to address high uncertainties regarding wind power generation and customer’s behavior. Besides, MPC considers all interactive effects of the control facilities in accordance with the expected wind farm output power in the future prediction horizon to maximize wind power utilization and so enhance social welfare. In addition, the uncertain nature of wind power is modeled using Markov chain Monte Carlo method. For efficiency evaluation of the proposed approach, simulation is implemented in MATLAB software using YALMIP optimization toolbox for the 8-bus test system. Results confirm the acceptable performance of the proposed approach in reducing operation cost through optimal uncertainties management.

Retraction notice to “Active robust optimization for wind integrated power system economic dispatch considering hourly demand response” [Renew. Energy 97 (2016) 798–808

Retraction notice to “Active robust optimization for wind integrated power system economic dispatch considering hourly demand response” [Renew. Energy 97 (2016) 798–808