An analysis for the need of a battery energy storage system in tracking wind power schedule output

电池储能系统(battery energy storage system,BESS)在风储联合应用中具有多种功能,利用电池储能系统提高风电并网调度运行能力是当前研究的热点之一.文章基于我国北方某风电场历史运行数据与预测数据,依据预测误差评价指标和风电场预报考核指标的综合评价方法对风电场预测数据进行分析研究,归纳了预测误差的概率分布特征;提出利用电池储能系统提高风电跟踪计划出力能力,统计并量化出电池储能系统用于跟踪计划出力场合的作用范围;通过仿真验证电池储能系统在风储联合系统中提高风电跟踪计划出力控制策略的有效性和可行性.     

Minimization and control of battery energy storage for wind power smoothing: Aggregated,distributed and semi-distributed storage

A battery energy storage system (BESS) is usually integrated with a wind farm to smooth out its intermittent power in order to make it more dispatchable. This paper focuses on the development of a scheme to minimize the capacity of BESS in a distributed configuration using model predictive control theory and wind power prediction. The purpose to minimize the BESS capacity is to reduce the overall cost of the system as the capacity of BESS is the main cost driver. A new semi-distributed BESS scheme is proposed and the strategy is analyzed as a way of improving the suppression of the fluctuations in the wind farm power output. The scheme is tested for similar and dissimilar wind power profiles, where the turbines are geographically located closer and further from each other, respectively. These two power profiles are assessed under a variety of hard system constraints for both the proposed and conventional BESS configurations. Based on the simulation results validated with real-world wind farm data, it has been observed that the proposed semi-distributed BESS scheme results in the improved performance as compared with conventional configurations such as aggregated and distributed storage.     

Control Strategies for Battery Energy Storage for Wind Farm Dispatching

Integrating a battery energy storage system (BESS) with a large wind farm can smooth out the intermittent power from the wind farm. This paper focuses on development of a control strategy for optimal use of the BESS for this purpose. The paper considers a conventional feedback-based control scheme with revisions to incorporate the operating constraints of the BESS, such as state of charge limits, charge/discharge rate, and lifetime. The goal of the control is to have the BESS provide as much smoothing as possible so that the wind farm can be dispatched on an hourly basis based on the forecasted wind conditions. The effectiveness of this control strategy has been tested by using an actual wind farm data. Finally, it is shown that the control strategy is very important in determining the proper BESS size needed for this application.      

A Statistical Approach to the Design of a Dispatchable Wind Power-Battery Energy Storage System

A scheme that allows the dispatch of steady and controllable level of power from a wind power generating station is proposed in this paper. The scheme utilizes two battery energy storage systems (BESSs) in which the generated wind power is used to charge one BESS, while the second BESS is used to discharge constant power into grid. The role of the two BESS interchanges when the discharging BESS reaches specified operating limit. With this scheme in mind and based on given wind speed statistics, charging characteristics of the BESS are studied, and a method to determine the expected charging time of the BESS to reach stipulated battery state of charge is developed. The expected BESS charging time, in turn, dictates the constant power level that can be dispatched to the grid through the discharging BESS. The corresponding discharge time is also determined using the developed method, the accuracy of which is validated experimentally. The proposed design procedure is then used to determine the minimum BESS capacity based on the expected wind power. Statistical likelihood of dispatchable power delivery achievable from the scheme is also obtained.      

电力市场环境下风-水电联合优化运行策略研究

为了促进风电场在电力市场环境下的发展,提出了一种风-水电站联合参与电力市场优化运行的策略。该策略综合考虑了从日前能量市场及调节备用容量市场中取得的收益,以期望收益最大化为目标,加入了水电站运行的限制,建立了含全天24个时段的混合整数规划模型,通过求解模型得出了各市场中的最优能量及容量申报,并基于实际的水电站与风电场参数进行了算例仿真。测试结果表明,水电站与风电场联合运行可降低风电出力的随机性对收益的负面影响,经济效益明显;风电出力的波动、能量不平衡的惩罚系数等因素都会对结果造成影响。     

A new self-scheduling strategy for integrated operation of wind and pumped-storage power plants in power markets

Competitive structure of power markets causes various challenges for wind resources to participate in these markets. Indeed, production uncertainty is the main cause of their low income. Thus, they are usually supported by system operators, which is in contrast with the competitive paradigm of power markets. In this paper, a new strategy for increasing the profits of wind resources is proposed. In the suggested strategy, a Generation Company (GenCo), who owns both wind and pumped-storage plants, self-schedules the integrated operation of them regarding the uncertainty of wind power generation. For presenting an integrated self-schedule and obtaining a real added value of the strategy, participation of the GenCo in energy and ancillary service markets is modeled. The self-scheduling strategy is based on stochastic programming techniques. Outputs of the problem include generation offers in day-ahead energy market and ancillary service markets, including spinning and regulation reserve markets. A Neural Network (NN) based technique is used for modeling the uncertainty of wind power production. The proposed strategy is tested on a real wind farm in mainland, Spain. Moreover, added value of the strategy is presented in different conditions of the market.     

Predictive control and sizing of energy storage to mitigate wind power intermittency

This paper studies how the control algorithm impacts the required capacity of battery energy storage system (BESS) to mitigate wind intermittency. We study a futuristic scenario in which wind generation is traded in the energy market on an hourly basis, and the wind power producer has to procure reserves to handle wind fluctuations. The wind power producer can avoid paying for conventional reserves by charging/discharging BESS to compensate for wind surplus and deficit. We develop control algorithms using the model predictive control (MPC) methodology, which incorporates wind forecasts for the next few hours when determining wind scheduling. The MPC algorithm is developed by solving a non‐linear optimization problem to minimize operation costs to the wind power producer. In addition to operation costs, the MPC algorithm considers two practical aspects: the efficiency loss of BESS and the smoothness in wind power scheduling. BESS sizing is studied by parametric analyses. Simulations show that BESS is more effective in reducing operation costs and reducing wind curtailment than conventional reserves. In addition, MPC is a horizon‐based control algorithm and can preview future information in its control action. Simulations also show that MPC consistently outperforms an instantaneous heuristic algorithm that does not use future information. Therefore, we confirm that MPC can reduce the BESS capacity required to cover wind uncertainties. Copyright © 2015 John Wiley & Sons, Ltd.     

A distributed optimization strategy for an island microgrid with price incentives

本文提出了一种基于多代理系统（multi-agent system,MAS）的孤岛微电网（microgrid,MG）实时经济调度分布式优化策略,其中孤岛微电网由发电供应商、电力用户和储能运营商等多运营主体组成。该策略考虑了电力用户参与电价制定的权利,经过系统内部多运营主体共同议价决策出电能交易的出清电价和交易电能量,实现了微电网内供需功率平衡。为保护交易过程中各运营主体的内部隐私权,模型采用了异步交替方向乘子法对联盟效益最大化模型进行求解。仿真结果验证了该策略的有效性。     

考虑负荷响应的冷电联供双层调度策略

为了提高清洁能源消纳率,解决负荷侧能源调度不足的问题,提出负荷层和冷电联供双层调度策略.首先负荷层对不同形式的负荷进行分类建模,然后通过源荷协调模型调整负荷转移或削减,匹配风电出力时序增加清洁能源消纳;其次调度层依据市场电价优化系统运行经济性,协调出力设备功率曲线.最后采用禁忌-细胞膜混合算法对双层调度模型求解.通过算...     

Minimizing the energy cost for microgrids integrated with renewable energy resources and conventional generation using controlled battery energy storage

This paper presents a methodology to minimize the total cost of buying power from different energy producers including renewable energy generations particularly within the context of a microgrid. The proposed idea is primarily based on the controlled operation of a battery energy storage system (BESS) in the presence of practical system constraints coupled with our proposed cost optimization algorithm. The complex optimization problem with constraints has been solved using the well-known concept of dynamic programming. The methodology has been assessed using actual power and price data from six different power generation sites and cost reduction has been calculated for a number of BESSs by varying their energy and power capacities. Twofold benefits of the proposed methodology lie in minimizing the total cost along with the constraint-based efficient operation of the BESS. Simulation results depict that the given power demand at a particular region can be fulfilled properly at all times using a BESS and multiple power generation.     

考虑预测误差分析的混合储能补偿优化策略

为提高风电场预测功率精度,对于风电场和混合储能构成的风储混合系统,提出基于预测信息搭建的混合储能补偿方案。首先,依据风电预测误差进行概率统计分析,提出风电功率预测误差的分层补偿策略,制定针对补偿预测误差的允许误差域及置信区间补偿域。其次,利用储能对不同误差层的预测误差给出相应的储能补偿方案,基于小波包分解将超出区域外待补偿预测误差分解,通过不平衡功率DFT分频法确定临界点作为功率型储能和能量型储能的目标分配值,对于荷电状态越限问题通过自适应模糊控制进行二次修正。最后,以新疆某风电场为例进行仿真分析,结果表明所提策略可有效减少风电功率预测误差。     

Lifetime and economic analyses of lithium‐ion batteries for balancing wind power forecast error

Wind power plant operators are often faced with extra charges when their power production does not match the forecasted power. Because the accuracy of wind power forecasts is limited, the use of energy storage systems is an attractive alternative even when large‐scale aggregation of wind power is considered. In this paper, the economic feasibility of lithium‐ion batteries for balancing the wind power forecast error is analysed. In order to perform a reliable assessment, an ageing model of lithium‐ion battery was developed considering both cycling and calendar life. The economic analysis considers two different energy management strategies for the storage systems and it is performed for the Danish market. Analyses have shown that the price of the Li‐ion BESS needs to decrease by 6.7 times in order to obtain a positive net present value considering the present prices on the Danish energy market. Moreover, it was found that for total elimination of the wind power forecast error, it is required to have a 25‐MWh Li‐ion battery energy storage system for the considered 2 MW WT. Copyright © 2015 John Wiley & Sons, Ltd.     

Impact of wind generation control strategies, penetration level and installation location on electricity market prices

Integration of wind facilities into power system grids have several impact on power system related issues including; transmission congestion, optimum power flow, system stability, power quality, system economics and load dispatch. Consequently, wind farm control strategy, location across the distribution network and its penetration level could have an impact on electricity market prices. This paper addresses these issues, by developing a single auction market model. An optimal power flow problem was formulated for determining the close to real time electricity market-clearing price and the total cost of generation. Simulation results, considering different operational cases, are presented to highlight the impact.     

Fatigue distribution optimization for offshore wind farms using intelligent agent control

A novel control approach is proposed to optimize the fatigue distribution of wind turbines in a large‐scale offshore wind farm on the basis of an intelligent agent theory. In this approach, each wind turbine is considered to be an intelligent agent. The turbine at the farm boundary communicates with its neighbouring downwind turbines and organizes them adaptively into a wind delivery group along the wind direction. The agent attributes and the event structure are designed on the basis of the intelligent agent theory by using the unified modelling language. The control strategy of the intelligent agent is studied using topology models. The reference power of an individual wind turbine from the wind farm controller is re‐dispatched to balance the turbine fatigue in the power dispatch intervals. In the fatigue optimization, the goal function is to minimize the standard deviation of the fatigue coefficient for every wind turbine. The optimization is constrained such that the average fatigue for every turbine is smaller than what would be achieved by conventional dispatch and such that the total power loss of the wind farm is restricted to a few percent of the total power. This intelligent agent control approach is verified through the simulation of wind data from the Horns Rev offshore wind farm. The results illustrate that intelligent agent control is a feasible way to optimize fatigue distribution in wind farms, which may reduce the maintenance frequency and extend the service life of large‐scale wind farms. Copyright © 2012 John Wiley & Sons, Ltd.     

Determination of Battery Storage Capacity in Energy Buffer for Wind Farm

Design of a battery energy storage system (BESS) in a buffer scheme is examined for the purpose of attenuating the effects of unsteady input power from wind farms. The design problem is formulated as maximization of an objective function that measures the economic benefit obtainable from the dispatched power from the wind farm against the cost of the BESS. Solution to the problem results in the determination of the capacity of the BESS to ensure constant dispatched power to the connected grid, while the voltage level across the dc-link of the buffer is kept within preset limits. A computational procedure to determine the BESS capacity and the evaluation of the dc voltage is shown. Illustrative examples using the proposed design method are included.      

Trading wind energy on the basis of probabilistic forecasts both of wind generation and of market quantities

Wind power is not easily predictable and non‐dispatchable. Nevertheless, wind power producers are increasingly urged to participate in electricity market auctions in the same manner as conventional power producers. The aim of this paper is to propose an operational strategy for trading wind energy in liberalized electricity markets and to assess its performance. At first, the so‐called optimal quantile strategy is revisited. It is proved that without market power, i.e. under the price‐taker assumption, this strategy maximizes expected market revenues. Forecasts of wind power production, of day‐ahead and real‐time market prices and of the system imbalance are inputs to this strategy. Subsequently, constraining of the bid that maximizes the expected revenues is proposed as a way to overcome the strategy's disregard of practical limitations and, at the same time, of risk. Two constraining techniques are introduced: constraining in the decision space and in the probability space. Finally, the trade of a wind power producer is simulated in a test case for the Eastern Danish (DK‐2) price area of the Nordic Power Exchange (Nord Pool) during a 10 month period in 2008. The results of the test case show the financial benefits of the aforementioned strategy as well as the consequent interaction with the electricity market. This study will support a demonstration in the framework of the EU project ANEMOS.plus. Copyright © 2012 John Wiley & Sons, Ltd.     

Application of energy capacitor system to wind power generation

In this paper, it is reported that energy capacitor system (ECS), which combines power electronic devices and electric double‐layer capacitor, can significantly decrease voltage and power fluctuations of grid‐connected fixed‐speed wind generator. The proper selection of wind farm output power reference is still a problem for smoothing the wind farm output power. This paper proposes exponential moving average to generate the reference output power of a grid‐connected wind farm. The objective of the control system is to follow the line power reference by absorbing or providing real power to or from the ECS. Moreover, the necessary reactive power can also be supplied to keep the wind farm terminal voltage at the desired reference level. Real wind speed data were used in the simulation analyses, which validate the effectiveness of the proposed control strategy. Simulation results clearly show that our proposed ECS can be suitable for wind power application. Copyright © 2007 John Wiley & Sons, Ltd.     

An input‐output linearization–based control strategy for wind energy conversion system to enhance stability

This paper proposes a novel control strategy for doubly fed induction generator (DFIG)‐based wind energy conversion system to investigate the potential of enhancing the stability of wind energy transmission system, a synchronous generator weakly integrated to a power system with a DFIG‐based wind farm. The proposed approach uses state feedback to exactly linearize the nonlinear wind energy transmission system from control actions (active power and reactive power control order of DFIG) to selected outputs (power angle and voltage behind transient resistance of synchronous generator) at first. Then, on account of the linearized subsystem, the stability enhancement controller is designed based on linear quadratic regulator algorithm to contribute adequate damping characteristics to oscillations of the synchronous generator system under various operation points. The proposed control strategy successfully deals with the nonlinear behaviors exist from the inputs to outputs and improve the robustness with respect to the variation of system operation points. Furthermore, not only the rotor angle stability but also the voltage stability is enhanced by using the proposed control strategy. The simulation results carried on the studied system verify the effectiveness of the proposed control strategy of wind energy conversion system for system stability enhancement and the robustness against various system operation points.     

Inhibition of wind power fluctuations of battery energy storage system adaptive control strategy design

为了增加电池储能系统针对大规模风电并网对电网系统的友好性,降低风电功率波动对电网的不利影响,本文提出以电池荷电状态和风电功率为反馈量,改变平抑时间常数和电池储能系统充放电目标功率为目标的平抑风电功率波动的自适应控制策略。经仿真验证,上述策略能有效避免电池的荷电状态大幅波动,延长电池使用寿命,从而减小电池储能系统的安装容量,最大限度地发挥电池储能系统的作用。     

Risk constrained self-scheduling of hydro/wind units for short term electricity markets considering intermittency and uncertainty

In view of the intermittency and uncertainty associated with both the electricity production sector of restructured power system and their competitive markets, it is necessary to develop an appropriate risk managing scheme. So that it is desirable to trade-off between optimum utilization of intermittent generation resources (i.e. renewable energy resources), uncertain market prices and related risks in order to maximize participants' benefits and minimize the corresponding risks in the multi-product market environment. The main goal of this paper is to investigate risk management by introducing a novel multi-risk index to quantify expected downside risk (EDR) which is caused by both the wind power and market price uncertainties. Value-at-Risk (VaR) method is used to assess the mentioned risk issue by the proposed weighted EDR, so that an optimal trade-off between the profit and risk is made for the system operations. Also, the roulette wheel mechanism is employed for random market price scenario generation wherein the stochastic procedure is converted into its respective deterministic equivalents. Moreover, the autoregressive integrated moving average (ARIMA) model is employed to characterize the stochastic wind farm (WF) generation by predetermined mean level and standard deviation of wind behavior as well as temporal correlation. The problem is formulated as a mixed-integer stochastic framework for a hydro-wind power system scheduling and tested on a generation company (GENCO).