Wind-storage Combined System Research Articles

Participation of wind-storage combined system in the secondary frequency regulation control strategy of power grid

Abstract The secondary frequency modulation of the unit, that is, the automatic generation control (AGC), is the process of increasing or decreasing the power of the power generation unit by the power plant unit according to the dispatching command issued by the power grid dispatching center, and then using the frequency modulator to restore the frequency. Based on the principle of AGC, this paper establishes a frequency dynamic response model of the secondary frequency modulation of the traditional unit and the wind storage participation system including load frequency control (LFC) and traditional proportional-integral-derivative (PID) controllers, determines the frequency modulation control strategy of wind storage, and uses the distribution mode based on Area Control Error (ACE) signal to assist in the secondary frequency modulation. In order to solve the parameter optimization problem of the classical PID controller when the wind-storage combined system participates in the secondary frequency modulation under the large load disturbance, a parameter optimization model of the controller with PID was established, and the ITAE evaluation index was finally selected as the fitness function by comparing different fitness evaluation indexes. To overcome the problem that the conventional Particle Swarm Optimization (PSO) is prone to local extremum, the inertia weights and learning factors are adjusted nonlinearly to balance and optimize the global and local optimization capabilities and improve the search efficiency, and the parameters of the PID controller are optimized by the improved PSO algorithm. The simulation results show that the proposed algorithm improves the secondary frequency modulation effect under the background of a high proportion of renewable energy connected to the power grid.

Pilot protection scheme for transmission line of wind-storage combined system based on one-mode current similarity

With the gradual growth of the scale of energy storage devices for wind power generation, a large-scale grid-connected wind-storage combined system (WSCS) has been formed. When the external transmission line fails, its control strategy will lead to problems such as limited output short-circuit current amplitude, frequency deviation from power frequency, and uncertain phase angle, which makes the traditional pilot protection possible to malfunction and refuse to operate. In order to solve this problem, this paper first analyzes the fault current output characteristics of the WSCS during low voltage ride through (LVRT), and its impact on the traditional pilot protection scheme. Secondly, considering the difference of fault current amplitude and phase change at both sides of the transmission line, the similarity relationship of one-mode current is verified. Finally, a pilot protection scheme based on one-mode current similarity is proposed in this paper. The simulation results conducted using PSCAD/EMTDC demonstrate that the proposed scheme exhibits robust anti-interference capability, capable of withstanding significant transitional resistance and noise, while maintaining good selectivity and reliability.

Hybrid energy storage system control and capacity allocation considering battery state of charge self-recovery and capacity attenuation in wind farm

Hybrid energy storage system (HESS) can cope with the complexity of wind power. But frequent charging and discharging will accelerate its life loss, and affect the long-term wind power smoothing effect and economy of HESS. Firstly, for the operational control of HESS, a bi-objective model predictive control (MPC) -weighted moving average (WMA) strategy for energy storage target power controlling is proposed, considering both energy storage state of charge (SOC) self-recovery and grid-connected power stabilization. The strategy can quickly adjust the SOC of HESS in the wind power smoothing process and reduce the battery's life loss. Then, since the energy storage capacity determines its power smoothing ability, this paper proposes a battery life model considering the effective capacity attenuation caused by calendar aging, and introduces it into the HESS cost calculation model to optimize the capacity allocation. Finally, combined with the wind power data, the simulation verifies that the proposed strategy can effectively balance the contradiction between energy storage lifetime and wind power smoothing effect. Simultaneously, the HESS optimized capacity allocation results considering battery's effective capacity attenuation can ensure the long-term wind power smoothing effect and better HESS operational states, contributing to the long-term and stable operation of wind-storage combined system.

Tracking-dispatch of a combined wind-storage system based on model predictive control and two-layer fuzzy control strategy

To maximize improving the tracking wind power output plan and the service life of energy storage systems (ESS), a control strategy is proposed for ESS to track wind power planning output based on model prediction and two-layer fuzzy control. First, based on model predictive control, a model with deviations of grid-connected power from the planned output and the minimum deviation of the remaining capacity of the ESS from the ideal value is established as the target. Then, when the grid-connected power exceeds the allowable deviation band of tracking, the weight coefficients in the objective function are adjusted by introducing the first layer of fuzzy control rules, combining the state of charge (SOC) of the ESS with the dynamic tracking demand of the planned value of wind power. When the grid-connected power is within the tracking allowable deviation band, the second layer of fuzzy control rules is used to correct the charging and discharging power of the ESS to improve its ability to track the future planned deviation while not crossing the limit. By repeatedly correcting the charging and discharging power of the ESS, its safe operation and the multitasking execution of the wind power plan output tracking target are ensured. Finally, taking actual data from a wind farm as an example, tests on a simulation platform of a combined wind-storage power generation system verify the feasibility and superiority of the proposed control strategy.

The Frequency Control Strategy of a Wind–Storage Combined System Considering Battery SOC

The wind power capacity has increased a lot recently and the number of close energy storage systems has also rapidly increased. To enhance the frequency stability support ability of such wind–storage combined systems, this paper proposes a virtual synchronous control strategy for a wind–storage combined system considering the battery state of charge (SOC). The virtual synchronous control is used to make the wind turbine generate more active power when the system is in disturbance. Most importantly, to ensure that the stored energy is used efficiently, the wide-area SOC concept of the energy storage system is considered, which is realized by designing the batteries with additional control that is related to the other batteries’ SOCs. This means that the low-SOC energy storage system’s power shortage can be compensated for by the high-SOC batteries. The above unified control enhances the wind–storage combined system’s frequency supporting ability. According to the simulations, the frequency drop can be suppressed through the help of the virtual synchronous control and the stored energy. Additionally, the instability can also be eliminated when wide-area SOC is considered, such that the proposed efficiency and correctness are finally verified through the simulations.

Wind-storage combined system based on just-in-time-learning prediction model with dynamic error compensation

High-performance wind power prediction (WPP) models can decrease the uncertainty of the whole energy system to balance energy supply and demand more effectively. However wind power process is characterized by the complicated mechanism and strong nonlinearity, which makes it difficult to establish a high-performance WPP model. In this paper, wind-storage combined system (WSCS) based on just-in-time-learning (JITL) prediction model with dynamic error compensation is proposed for high-performance WPP. This method can describe the characteristics of local wind power process efficiently and accurately by approximating the nonlinear process into a composite process with dynamic linear autoregression and static nonlinear error compensation. What's more, a WSCS model is proposed to indirectly improve the prediction accuracy. The model employs energy storage systems (ESS) to complement wind farm output to improve the wind power fluctuation and the performance of WPP. Simulation results verify that the proposed model has high prediction performance and generalization ability. Specifically, the RMSE, MAE and MAPE are 58.8728KW, 33.1277KW, 4.5877 % for gale season in a month. The RMSE, MAE and MAPE are 52.2014KW 33.2680KW, 2.3628 % for breeze season in a month. And WSCS indirectly improved the accuracy of the day-ahead prediction that reduced the RMSE from 414.4409KW to 182.2397KW. Accordingly, the research results can improve the WPP technology and reduce the redundant energy of wind power through ESS to facilitate the storage of ESS and improve the wind power fluctuation.

Energy storage capacity optimization strategy for combined wind storage system

The rapid development of wind power has imposed many challenges on the operation of the power system. Energy storage system has broad application prospects in promoting wind power to the grid. However, the high price of the energy storage restricts the development of the combined wind energy-storage system. In order to deal with the power fluctuation of the large-scale wind power grid connection, we propose an allocation strategy of energy storage capacity for combined wind-storage system considering the wind power output volatility and battery storage system’s own operational constraints. The model aims to maximize the annual avenue of the cogeneration system, which allows for the investment fee, operation and maintenance fee and penalty cost of the combined system. The calculation results validate the effectiveness of the optimal allocation strategy.

Wind-Storage Combined Virtual Inertial Control Based on Quantization and Regulation Decoupling of Active Power Increments

With the increasing proportion of wind turbines in power grids, they are required to have capabilities of active and efficient virtual inertial response to maintain grid frequency stability. However, the virtual inertial control methods currently used in doubly-fed induction generator (DFIG) units suffer from a secondary frequency drop (SFD) problem. Although the SFD can be inhibited by reducing the active power support strength of the DFIG units during inertia response, it will undoubtedly weaken the virtual inertia of the units. Therefore, how to eliminate the SFD while increasing the virtual inertia of the units is a worthy issue for studying. To solve this issue, a wind-storage combined virtual inertial control system based on quantization and regulation decoupling of active power increments is proposed in this paper. First, by setting the parameters of a proportional–differential (P-D) algorithm, the total active power increments required for virtual inertial response are quantified at the DFIG level. Secondly, a curve-shifting method based on the rate of change of frequency is adopted to adjust the active power output of the DFIG units. Finally, a battery energy storage system (BESS) is used to compensate for the power shortages of the units according to the quantized value of the active power increments. Simulations show that the control method can not only eliminate SFD but also effectively increase the system’s virtual inertia.

Research on the Optimized Operation of Hybrid Wind and Battery Energy Storage System Based on Peak-Valley Electricity Price

The combined operation of hybrid wind power and a battery energy storage system can be used to convert cheap valley energy to expensive peak energy, thus improving the economic benefits of wind farms. Considering the peak–valley electricity price, an optimization model of the economic benefits of a combined wind–storage system was developed. A charging/discharging strategy of the battery storage system was proposed to maximize the economic benefits of the combined wind–storage system based on the forecast wind power. The maximal economic benefits were obtained based on scenario analysis, taking into account the wind-power forecast error, and costs associated with the loss of battery life, battery operation, and maintenance. Case simulation results highlight the effectiveness of the proposed model. The results show that the hybrid wind–storage system is not only able to convert cheap electricity in the valley period into expensive electricity in the peak period, thus resulting in higher economic benefits, but can also balance the deviation between actual output and plans for the wind power generator to decrease the loss penalty. The analyzed examples show that, following an increase in the deviation of the forecast wind power, the profit of the combined wind–storage system can increase by up to 45% using the charging/discharging strategy, compared with a wind farm that does not utilize energy storage. In addition, the profit of the combined wind–storage system can increase by up to 16% compared with separate systems, following an increase in the deviation penalty deviation coefficient.

Dynamic economic dispatch of wind-storage combined system based on conditional value-at-risk

Wind power's uncertainty is from the intermittency and fluctuation of wind speed, which brings a great challenge to solving the power system's dynamic economic dispatch problem. With the wind-storage combined system, this paper proposes a dynamic economic dispatch model considering AC optimal power flow based on Conditional Value-at-Risk (CVaR). Since the proposed model is hard to solve, we use the big-M method and second-order cone description technique to transform it into a trackable mixed-integer second-order conic programming (MISOCP) model. By comparing the dispatching cost of the IEEE 30-bus system and the IEEE 118-bus system at different confidence levels, it is indicated that CVaR method can adequately estimate dispatching risk and assist decision-makers in making reasonable dispatching schedules according to their risk tolerance. Meanwhile, the optimal operational energy storage capacity and initial/final energy storage state can be determined by analyzing the dispatching cost risk under different storage capacities and initial/final states.

Cooperative control strategy for distributed wind-storage combined system based on consensus protocol

To realize real-time wind farm output power regulation with power-sharing among storage devices that have different state of charges (SoCs), this paper proposes the cooperative control of the distributed wind-storage combined systems (WSCSs). It firstly establishes the mathematical model of doubly-fed induction generator (DFIG) and hybrid energy storage system (HESS) and implements the controls for two devices, respectively. Secondly, based on the power consensus protocol, an active power cooperative control strategy of the distributed WSCSs is proposed. It ensures that the energy storage devices can cooperatively compensate for wind power according to their different capacities to regulate the output power of the wind farm (WF) in real-time. At the same time, the high- and low- frequency power fluctuations can be effectively shared by the supercapacitors (SCs) and batteries, overcoming the deficiencies of the conventional battery energy storage system (BESS). Then, considering that the SoCs of the batteries are not identical, this paper further proposes a DFIG grid-side reference power adjustment strategy based on consensus protocol. It guarantees that each HESS can effectively achieve power-sharing while regulating the output power according to the SoCs of batteries. Finally, simulations in PSCAD/EMTDC under various scenarios are conducted to demonstrate the effectiveness of the proposed control strategy.

Adjustable robust power dispatch with combined wind-storage system and carbon capture power plants under low-carbon economy

This paper proposes an adjustable robust power dispatch (ARPD) model under low-carbon economy to accommodate the uncertainty of wind power with combined wind-storage system (CWSS) and carbon capture power plants (CCPPs). First, battery energy storage (BES), which is considered as adjustable under worst-case scenarios, is introduced to wind power plants to form a combined wind storage system structure to improve operation flexibility. Then, a dispatching model of CCPPs is presented and analysed. The operating characteristics of CCPPs make it possible to control net power outputs and carbon emissions independently and flexibly. The integration of BES and carbon capture and storage (CCS) improves the operation flexibility of both wind power plants and conventional power plants. The objective function of the proposed model under interval-uncertain wind power is to minimize the total cost under the worst wind power output case and the context of low-carbon economy. The proposed model is implemented on the modified PJM 5-bus system with one wind farm and the IEEE-118 bus system with five wind farms. Numerical results demonstrate that the proposed model is effective at reducing carbon emissions and wind power curtailment, and verify that as the number of CCPPs increases, the overall costs come down.

Research on Capacity Optimization of Wind-Storage System Based on Fuzzy Control Strategy

The wind storage combined power generation mode can effectively solve the technical bottlenecks of large-scale wind power grid connected operation and improve the grid's ability to accept wind power. However, due to the high cost of energy storage and the imperfection of the electricity price mechanism, it is necessary to study the capacity optimization of wind-storage combined generation system. Based on the fuzzy control strategy, this paper determined the charge and discharge model of the wind-storage system, and established the Monte Carlo reliability evaluation model and the economic evaluation model that aims at maximizing the annual economic benefits of the system. Then the optimal allocation of wind-storage capacity was obtained by analyzing the reliability index and economic index of the different wind storage capacity rate through the actual wind field test data. Finally, the State of Charge (SOC) at the optimal capacity allocation was analyzed. The result shows that the reasonable allocation of wind-storage capacity is conducive to the reliable and economic operation of the system.

Coordinated control strategy for improving the two drops of the wind storage combined system

In the power system with high permeability wind power, due to wind power fluctuation, the operation of large-scale wind power grid connected to the system brings challenges to the frequency stability of the system. When the doubly fed wind power generation unit does not reserve spare capacity to participate in the system frequency regulation, the system frequency will produce two drops in different degrees when the wind power exits frequency modulation and enters the speed recovery stage. To solve this problem, based on the complementary advantages of wind turbines and energy storage systems in power transmission and frequency modulation, a wind storage combined frequency modulation strategy based on sectional control is proposed in this paper. Based on the TOP wind power frequency modulation strategy, the wind power output reference value is determined according to the linear relationship between the output and the speed of the wind turbine, and the auxiliary wind power load reduction is controlled when the wind power exits frequency modulation into the speed recovery stage, so that the wind turbine is recovered to run at the optimal speed. Then, according to the system frequency and the wind turbine operation state, set the energy storage system frequency modulation output. Energy storage output active support is triggered during wind speed recovery. And then when the system frequency to return to the normal operating frequency range, reduce energy storage output or to exit frequency modulation. The simulation results verify the effectiveness of the proposed method.

Black start research of the wind and storage system based on the dual master-slave control

Black start is the key to solving the problem of large-scale power failure, while the introduction of new renewable clean energy as a black start power supply was a new hotspot. Based on the dual master-slave control strategy, the wind and storage system was taken as the black start reliable power, energy storage and wind combined to ensure the stability of the micorgrid systems, to realize the black start. In order to obtain the capacity ratio of the storage in the small system based on the dual master-slave control strategy, and the black start constraint condition of the wind and storage combined system, obtain the key points of black start of wind storage combined system, but also provide reference and guidance for the subsequent large-scale wind and storage combined system in black start projects.

The scheme of wind-storage combined system capacity configuration based on random fuzzy chance constrained bi-level programming

A random fuzzy chance constrained bilevel programming scheme for distributed wind-storage combined system is proposed. The random fuzzy simulation is used to describe the uncertainty of distributed wind power output. The reliability of randomness and ambiguity is taken as the index to evaluate the capacity allocation scheme of the distributed wind-storage combined system. Considering system power balance, opportunity measurement constraint of static security index and active management (AM) measures, the random fuzzy expectation value of maximum annual profit is set as the upper optimization goal, and the minimum random fuzzy expectation value of the distributed wind power active reduction is set as the lower optimization target. The scheme is constructed by judging whether the static security index of the upper goal satisfies the confidence level of the random fuzzy chance constraint and the coordination of the upper and lower goals. Finally, the random fuzzy simulation, the forward pushback power flow calculation and the genetic algorithm (GA) are applied to solve the model. The simulation result of IEEE 14-bus example shows the effectiveness and superiority of the model and scheme.

Joint Planning Of Energy Storage and Transmission Considering Wind-Storage Combined System and Demand Side Response

In response to the new requirements of the operation mode of wind-storage combined system and demand side response for transmission network planning, this paper presents a joint planning of energy storage and transmission considering wind-storage combined system and demand side response. Firstly, the charge-discharge strategy of energy storage system equipped at the outlet of wind farm and demand side response strategy are analysed to achieve the best comprehensive benefits through the coordination of the two. Secondly, in the general transmission network planning model with wind power, both energy storage cost and demand side response cost are added to the objective function. Not only energy storage operation constraints and but also demand side response constraints are introduced into the constraint condition. Based on the classical formulation of TEP, a new formulation is developed considering the simultaneous addition of the charge-discharge strategy of energy storage system equipped at the outlet of the wind farm and demand side response strategy, which belongs to a typical mixed integer linear programming model that can be solved by mature optimization software. The case study based on the Garver-6 bus system shows that the validity of the proposed model is verified by comparison with general transmission network planning model. Furthermore, the results demonstrate that the joint planning model can gain more economic benefits through setting up different cases.

Economic dispatch of wind integrated power systems with energy storage considering composite operating costs

An economic dispatch (ED) model is proposed in this study for accommodating high penetrations of wind power with the integration of battery energy storage (BES) in power systems. In the proposed ED model, a wind-storage combined system (WSCS) model is studied to collectively mitigate the output fluctuations and improve the wind power utilisation. In addition, the proposed concept of composite operating costs include the unit operation cost, environmental cost, reserve cost, compensation cost for wind power curtailment, and energy loss cost of ES. With the minimisation of the composite operating costs as the objective function of the proposed ED model with WSCS, a modified bacterial foraging algorithm (MBFA) is proposed to solve the optimisation problem based on a combination of the bacterial foraging algorithm (BFA) and the Particle Swarm Optimisation (PSO). Furthermore, the case study on the IEEE 30-bus system has been used to demonstrate the feasibility and effectiveness of the proposed ED model and the performance improvement of the MBFA algorithm over BFA or PSO alone. The comparison between different scenarios shows that the integration of ES in the proposed model effectively improves the wind power utilisation and the system efficiency.

Planning and Operating Combined Wind-Storage System in Electricity Market

The increasing penetration of renewable sources in power systems yields various issues in network operation. Most of them are related to uncertainties of energy production. In particular, the variability of wind source does not allow for accurate forecasting of power generation. Production plans may not be accomplished, incurring penalties for system unbalance. For this reason, the use of an energy storage system can improve integration of wind energy in production planning and dispatch. In this paper, an approach for planning and operating an energy storage system for a wind farm in the electricity market is proposed. To this purpose, electrochemical batteries are employed to compensate for generation variations in order to set up a reliable hourly delivery profile, complying with market requirements. The delivery plan can be settled according to energy prices, as well. Moreover, an economic feasibility analysis is carried out on the combined wind-storage system.

Installation Determination Method of the Combined Wind-Storage System Aiming at Smooth Effects

The energy storage system can be engaged to smooth the fluctuation output of wind power for better power quality and stability of power grid. The paper proposes a low-pass-filter-based smooth control model of the wind-storage combined system. Then the paper proposes the evaluation indices which depict power fluctuation of the combined system without/with smooth control, on which the installation storage capacity is optimized. All simulation is done on the basis of measured data