An adaptive wind power smoothing method with energy storage system

This paper proposes a coordinated operational strategy of energy storage system (ESS) and wind farm to reduce wind power spillage and alleviate wind power fluctuation. Firstly, power curve of a wind farm, in the form of an equivalent wind turbine, is determined by least square fitting. Based on the power output characteristic of the wind farm and historic operating data, the statistical properties of wind power spillage and fluctuation can be obtained. Secondly, the target for wind farm and ESS power output is calculated. Power generation/absorption capabilities of ESS and available power output reducing range of the wind farm are quantified as well, considering the operational constraints of ESS and dispatched wind power output. Finally, a coordinated operational strategy is developed not only to adjust the combined ESS and wind farm to meet the dispatch requirement, but also to ensure ESS and the wind farm to satisfy operational constraints. Case studies are conducted on a practical wind farm with battery energy storage system installed, which demonstrate that the coordination of ESS can greatly boost the revenue and improve power quality of wind farm.

The integration of wind farms into the transmission network has raised various concerns and objections. To address these challenges, the deployment of series compensators has gained significance as an effective method for enhancing the power transmission capacity of existing lines, particularly for the integration of large-scale wind farms. However, the use of series reactive compensation lines can lead to a phenomenon known as sub-synchronous resonance (SSR) in turbo generators. This SSR can cause electrical instability at sub-synchronous frequencies and potential damage to the turbine’s generator shaft, particularly during periods of peak production. As a result, the assessment of SSR through comprehensive surveys is crucial for wind power engineers to make informed decisions and ensure the safety of turbines. This study explores the potential of SSR through the utilization of the black widow optimization technique. The analysis takes into account variables such as variations in the speed of the wind, compensation spectrum, and wind velocity and examines the eigenvalue and involvement components under various operating situations. To validate our findings, electromagnetic transient simulations are conducted using the PSCAD/EMTDC software, employing the initial IEEE reference systems. This research contributes to a deeper understanding of SSR and its implications for wind energy systems.

This paper presents an optimization model for determining the nominal capacity of an energy storage system is presented, which transfers excess amounts of electrical energy from solar power plants as part of a group of distributed generation power plants, based on the criterion of the minimum cost of supplying electricity to end consumers. The use of the developed optimization model allows to determine the optimal parameters of the energy storage system to achieve an economic balance between the excess amounts of electric energy of solar power plants that are transferred and the amount of restrictions on inverters that are subject to payment. Based on the developed method, based on the forecast level of electric energy consumption and statistical data on the level of electric energy production at wind and solar power plants for the territory of Ukraine, the installed capacity of the wind, solar, reserve power plant and the nominal capacity of the two-hour energy storage system were determined, which will provide the minimum levelized cost of energy of supplying to consumers during the entire period of commercial operation of a group of distributed generation power plants.

Aiming at meeting the requirement of balancing the fluctuating wind power, this study proposed an optimal control strategy for wind power hybrid energy storage system considering output power amendment. Firstly, fluctuant wind power is decomposed into low‐frequency, sub‐high frequency and high‐frequency components. Low‐frequency part is used as the expected value of wind power integration. Sub‐high frequency and high‐frequency components are used as the target value of output power of storage batteries and ultra‐capacitor energy storage system. Secondly, a double power amendment is proposed. In the first‐time power amendment, the amendment coefficient is calculated by fuzzy controller whose inputs are the target value of power and state of charge (SOC) of the energy storage system. On the other hand, complement of batteries and super‐capacitors are utilised in the second amendment. Through simulation analysis, it can be indicated that the configuration of the hybrid energy storage system and the control system design are feasible. This system can be widely used in wind farm, undertaking the task of balancing the fluctuating wind power.

Nowadays, integration of large-scale wind farms (WFs) into power systems is experiencing rapid growth. As this rapid integration can affect transient stability significantly, employing doubly fed induction generator (DFIG)-based wind turbines, which have shown better behavior regarding system stability, has attracted much attention. This research contributes to the literature by investigating the transient stability of the power system with increasing penetration of DFIG-based WFs. In the proposed framework, the current-balance form is utilized for the network equations, and in this way, transient stability is performed using time-domain simulation. According to the simulation results, when the rate of wind power generation exceeds 0.7 per-unit, the increasing trend of the critical clearing time (CCT) is reversed and the CCT decreases greatly with the increased wind power penetration. In addition, the reactive power compensation by DFIG, the gearbox ratio, the power system strength, and DFIG parameters are comprehensively investigated as effective parameters on transient stability. Since the rated rotor speed of DFIG significantly impacts the electrical torque and machine currents, the reduction of the rated rotor speed due to the change of the gearbox ratio has been investigated as one of the effective factors to improve the transient stability. The simulation results demonstrate the effectiveness of the proposed approach in improving power system transient stability.

The anti-peak shaving characteristics of wind power is an important factor that limits the consumption of wind power. The use of the space-time translation capability of a battery energy storage system is one of the effective means for promoting wind power consumption. Thus, this study proposes an energy storage system smoothing wind power fluctuation control strategy considering wind power consumption to improve the utilization level and economy of an energy storage system. First, the statistical characteristics of wind power are analyzed, and the scene division principle of a multiscenario regulation of an energy storage system is formulated using a correlation coefficient. On this basis, the charging and discharging intervals of the energy storage system in each scenario are determined by comprehensively considering the wind power and the time domain distribution law of load. Then, the control strategy of energy storage system based on inter-zone control is proposed based on the division of charging and discharging intervals. During the charging interval, smoothing the upward fluctuation of wind power or reducing the amount of abandoned wind power is aimed at storing electricity. During the discharge interval, electricity is released to smooth the downward fluctuation of wind power. Finally, considering the real-time state of charge and wind power consumption of the energy storage system, a method of charging and discharging power correction based on fuzzy control is proposed. Taking the actual data of a wind farm as an example, a test is performed on a simulation platform of a combined wind storage power generation system to verify the feasibility and superiority of the proposed control strategy.

ABSTRACTThe intermittent and fluctuating nature of wind turbine output power is increasingly being recognized as a significant issue adversely impacting the power quality and stability of electrical grids. With the increasing integration of wind power, this challenge cannot be underestimated. However, a potential solution for mitigating the adverse effects of such fluctuations lies in the Hybrid Energy Storage System (HESS), which encompasses battery energy storage systems (BESS) and supercapacitors (SC). The HESS is equipped with flexible operational modes for charging and discharging, thus enabling grid‐connected microgrids to possess the ability to counteract these oscillations. In this article, a control strategy based on the combination of Q‐learning and fuzzy logic control approaches is presented for tuning the parameters of a utilized two‐stage variable time constant low‐pass filter (LPF) in a grid‐connected microgrid. The proposed strategy adaptively tunes the time constants of LPFs to mitigate wind power fluctuations. Furthermore, practical constraints for the energy storage systems and their interfaced converters, such as preventing overcharge/discharge, ramp rate requirements, and certain maximum power conversion ranges, have been taken into account. Numerical simulation results verify the effectiveness of the proposed two‐stage variable time constant LPF for output wind power fluctuation reduction considering practical constraints of HESS.

Wind power is also known as junk. This is because wind power fluctuations affect the security and stability operation. Wind power wind turbines created is mainly concerned with the speed of wind. Because of the wind direction uncertain, intermittent, and wake effects between each unit wind farm, wind turbines cannot make that kind of power according to the demand for energy as conventional generators. Due to the lack of experimental data, assess the volatility of wind power is still a lack of effective methods. This article studies the sample in a northeast wind farm power, and based on a sliding differential algorithm, distribution fitting and quantitative calculations describe the characteristics of wind power fluctuations. This article studies the sample in a northeast wind farm power, and based on a sliding difference algorithm, through the analysis showed that wind power fluctuations obey t location scale distribution. And it is affected by factors such as spatial and temporal distribution, there is a big difference between the output power fluctuation characteristics of wind farm output power and single wind turbine. This is due to the wind turbine suffered varying differences, and wake effects between field units, making the distribution of frequent power fluctuations; relative to a single unit, the fluctuation of the whole wind farm is more gentle, that is to say with the spatial distribution increased scale, wind power fluctuations presents certain "gentle effect."

To reduce the impact of wind power fluctuations on the power grid, this paper proposes a hybrid energy storage system (HESS) capacity optimization configuration method for wind power fluctuation smoothing. The method utilizes a Global Search Whale Optimization Algorithm (GSWOA) to optimize Variational Mode Decomposition (VMD) parameters. First, GSWOA determines the optimal parameter combination (K, α) for VMD. The optimized VMD then decomposes the wind power into a component suitable for direct grid integration and a component requiring smoothing. The smoothing-required component undergoes secondary allocation. Subsequently, an HESS capacity optimization model, considering system costs, is established. This approach achieves efficient wind power fluctuation smoothing and economically optimized operation of the HESS. Case study results demonstrate that the proposed method (GSWOA-VMD) offers superior calculation accuracy and convergence speed compared to alternatives. Furthermore, the HESS configuration exhibits a higher smoothing rate and lower comprehensive cost than single energy storage systems.

In the European UCTE system the share of renewable energy particularly of wind energy will grow essentially in the near future. Renewable energy is supported by the European union and the national governments. In Germany it is planned to extend the wind power generation from about 14000 MW at present to more than 40000 MW in 2030, In the present wind power generation was located in the medium voltage distribution systems with small wind parks size below 100 MW. The locations and the available wind onshore for larger units are limited. The new tendency is to install large wind parks off-shore with hundreds of MW power size in the North Sea and Baltic Sea. Depending on the size and distance to the on-shore transmission grid high voltage sea cable connections with distances up to 200 km have to be planned and installed. The transmission system operator (TNO) defines a wind park to operate in the same way as a conventional power plant. New rules have been collected in the grid code to define the interconnection with the grid and the control behaviour of the wind generators. Depending on the increase of wind energy an overcapacity of existing plants has to be retired. As a consequence of the wind nature wind generators are related to lower reliability and low average output in undesired time periods. Offering the necessary system reserve will become more and more an expensive and complex task. A second severe aspect are the uncontrolled load flows in and out of the control areas of the TNO's depending on the changing wind conditions. In some cases the (n-l)-principle of the transportation system can not be fulfilled as a consequence of additional wind energy flows through the system. These congestions have a high impact on the security and safety margins of the system and reduce free trading of power in the system. A very precise wind forecast is of essential importance in addition to a suitable reliability of the wind parks itself. The transmission system operator demand active and-reactive power support of wind generators to the grid during and after faults.

The increasing integration of renewable energy generation (REG) makes the capacity value (CV) estimation for the REG become more important in the process of generation expansion planning. However, most researches on the CV ignore the hybrid generation system based on multiple complementary energy resources, as well as the operation strategy of energy storage system (ESS). To solve these problems, the models of available capacity of ESS are developed based on three different strategies. Then, using the sequential Monte-Carlo simulation method, the models and methods are developed for reliability assessment of generation system and capacity value estimation for the hybrid power generation system based on WT/PV/ES (HGS-WPE). By the application in IEEE-RTS79, the feasibility of models and estimation methods are verified. Finally the impacts of the complementation of HGS-WPE, the capacity and operation strategy of ESS on the reliability assessment and capacity value estimation are analyzed.

Rolling optimization of transmission network recovery and load restoration considering hybrid wind-storage system and cold load pickup

For stable integration of large-scale wind farms, integration standards (Grid codes) have been proposed by the system operator. In particular, voltage control of large-scale wind farms is gradually becoming important because of the increasing size of individual wind farms. Among the various voltage control methods, Secondary Voltage Control (SVC) is a method that can control the reactive power reserve of a control area uniformly. This paper proposes hybrid SVC when a large-scale wind farm is integrated into the power grid. Using SVC, the burden of a wind turbine converter for generating reactive power can be reduced. To prove the effectiveness of the proposed strategy, a simulation study is carried out for the Jeju system. The proposed strategy can improve the voltage conditions and reactive power reserve with this hybrid SVC.

Difference between grid connections of large-scale wind power and conventional synchronous generation

Repowering a wind farm enhances its ability to generate electricity, allowing it to better utilize areas with high mean wind speeds. Pakistan’s present energy dilemma is a serious impediment to its economic development. The usage of a diesel generator as a dependable backup power source raises the cost of energy per kWh and increases environmental emissions. To minimize environmental emissions, grid-connected wind farms enhance the percentage of wind energy in the electricity system. These wind generators’ effects, on the other hand, are augmented by the absorption of greater quantities of reactive electricity from the grid. According to respective grid codes, integration of commercial onshore Large-Scale Wind Farms (LSWF) into a national grid is fraught with technical problems and inter-farm wake effects, which primarily ensure power quality while degrading overall system operation and limiting the optimal use of attainable wind resources. The goal of this study is to examine and estimate the techno-economic influence of large-scale wind farms linked to poor transmission systems in Pakistan, contemplating the inter-farm wake effect and reactive power diminution and compensating using a range of voltage-ampere reactive (VAR) devices. This study presents a partial repowering technique to address active power deficits produced by the wake effect by raising hub height by 20 m, which contributed to recovering the active power deficit to 48% and so reduced the effects of upstream wind farms. Simulations were conducted for several scenarios on an actual test system modeled in MATLAB for comparative study using capacitor banks and different flexible alternating current transmission system (FACTS) devices. Using the SAM (System Advisor Model) and RETscreen, a complete technical, economic, and environmental study was done based on energy fed into the grid, payback time, net present value (NPV), and greenhouse gases (GHG) emission reduction. The studies suggest that the unified power flow controller (UPFC) is the optimum compensating device via comparison analysis as it improved the power handling capabilities of the power system. Our best-case scenario includes UPFC with hub height augmentation, demonstrating that it is technically, fiscally, and environmentally viable. Over the course of its lifespan, the planned system has the potential to save 1,011,957 tCO2, resulting in a greener environment. When the energy generated annually by a current wake-affected system is compared to our best-recommended scenario, a recovered shortfall of 4.851% is seen, with improved system stability. This modest investment in repowering boosts energy production due to wake effects, resulting in increased NPV, revenue, and fewer CO2 footprints.