Active power control design for supporting grid frequency regulation in wind farms

Among renewable energy sources, wind power is expected to contribute a larger and rapidly growing portion of the world's energy portfolio. However, the increased penetration of wind power into the power grid has challenged the reliable and stable operation of the grid. This motivates new opportunities in the design and development of novel control schemes capable of actively maintaining the necessary balance between power generation and load, which in turn regulates the grid frequency when plenty of winds are available. This paper presents two active power control schemes that are developed based on adaptive pole placement control and fuzzy gain-scheduled proportional-integral control approaches. The active power control is conducted collectively across a wind farm to provide rapid power response while maintaining safe structural loading on turbines’ components. The proposed active power control schemes are evaluated and compared by a series of simulations on an advanced wind farm benchmark model in the presence of wind turbulences, measurement noises, and grid load variations. It is further demonstrated that the mentioned schemes are able to tolerate probable occurrence of sudden imbalance between generation and load due to relevant faults/failures in the wind farm or electric grid.     

Minimum energy storage for power system with high wind power penetration using p-efficient point theory

Minimum energy storage （ES） and spinning reserve （SR） for day-ahead power system scheduling with high wind power penetration is significant for system operations. A chance-constrained energy storage optimization model based on unit commitment and considering the stochastic nature of both the wind power and load demand is proposed. To solve this proposed chance-constrained model, it is first converted into a deterministic-constrained model using p-efficient point theory. A single stochastic net load variable is developed to represent the stochastic characteristics of both the wind power and load demand for convenient use with the p-efficient point theory. A probability distribution function for netload forecast error is obtained via the Kernel estimation method. The proposed model is applied to a wind-thermal-storage combined power system. A set of extreme scenarios is chosen to validate the effectiveness of the proposed model and method. The results indicate that the scheduled energy storage can effectively compensate for the net load forecast error, and the increasing wind power penetration does not necessarily require a linear increase in energy storage.     

计及光伏及风电并网的电力系统短期负荷预测

为提升光伏、风电等分布式能源大量接入电网后短期电力负荷的预测精度,促进电网消纳能力提升,本文对光伏出力及短期用电负荷采用小波——径向基函数(RBF)神经网络预测方法;对风力发电首先利用总体平均经验模态分解(EEMD)方法对其功率数据分解,再采用BP神经网络、RBF神经网络、小波神经网络、ELMAN神经网络四种神经网络预测方法进行预测,并用粒子群算法(PSO)和灰色关联度(GRA)修正。最后,利用等效负荷的概念,分析光伏、风力发电并网对于短期电力负荷预测的影响,并将三种模型有效结合,得到了考虑光伏及风力发电并网的电力系统短期负荷预测的等效负荷预测模型。实例分析表明,本文所提方法相较于其他方法在该预测项目上具有相对更高的预测精度。     

考虑电网调峰需求的工业园区主动配电系统调度学习优化

本文针对含光伏(Photovoltaic, PV)、全钒液流电池(Vanadium redox battery, VRB)储能装置与多类型柔性负荷的工业园区主动配电系统, 研究在考虑源荷随机性情况下该系统的动态经济调度问题. 首先, 将PV出力、多类型负荷需求和电网调峰需求的随机动态变化近似描述为连续马尔科夫过程, 并根据系统内VRB的充放电特性对储能系统进行建模; 然后, 以各决策时刻下PV出力、负荷需求、调峰需求以及储能荷电状态(State of charge, SOC)的离散等级为状态, 以储能充放电及多类型柔性负荷调整方案为行动, 在系统功率平衡等相关约束下, 以应对电网调峰需求和提高系统经济运行水平为目标, 将工业园区主动配电网系统动态经济调度优化问题建立成随机动态规划模型; 最后, 引入强化学习方法进行策略求解. 算例仿真结果表明所得策略可有效提高系统经济运行效益, 并在一定程度上满足电网调峰需求.     

考虑源荷随机性的跨区互联电网直流联络线调度学习优化

在跨区互联电网中,充分利用直流联络线调度能力可以有效地平衡电力资源的配置,促进新能源的消纳.本文针对源荷不确定性的跨区互联电网直流联络线调度问题,首先用连续马尔科夫过程模型描述互联电网中风电出力与负荷需求随机动态特性;然后在功率平衡及联络线日交易电量约束等实际运行要求前提下,将直流联络线调度优化问题建立成离散马尔科夫决策过程模型.在该模型下,调度机构根据互联电网系统各时段源荷的功率情况,动态调整联络线输电计划和配套的柔性负荷调节方案,以达到提升系统运行效益的优化目标;最后引入强化学习方法对调度策略进行优化求解.通过学习优化,系统平均日运行代价显著下降且最终收敛.实验结果表明考虑源荷随机性的直流联络线动态调整方法可有效地提高互联电网发输电系统的运行效益.     

多时空尺度的风力发电预测方法综述

风能是目前世界上装机量较大的可再生能源之一，风力发电预测的精度直接影响电网的调度与安全运营.由于电网的调度策略存在多个时间点，并与涉及的地域范围有关，本文从多种时间和空间尺度的角度，综述风力发电预测方法.风力发电预测一般针对特定的空间范围和时间尺度，并在有限信息资源的条件下完成，故本文从上述三个方面综述已有研究成果.本文首先根据风力发电空间范围，从单台风力发电机、单一风电场以及风电场群三个空间尺度对研究成果进行梳理.其次在每个空间尺度上，根据风电预测是否使用气象信息将研究成果分类，并根据预测时间尺度将研究成果再次分类.最后在每个时间尺度上，根据风电预测存在的挑战，将已有的研究成果归类.通过上述梳理，本文希望可以帮助研究人员找到适合不同风电预测任务场景的方法.     

山西电网消纳风电能力的计算分析

山西电网风电并网规模不断增大,电力系统的调峰能力已成为消纳风电的主要因素。结合山西省水电贫乏、火电供热机组增多等特点,并考虑负荷特性、电源特性,分析了山西电网的调峰能力和风电对电网调峰能力的影响,提出了山西电网消纳风电能力的计算方法。在收集各种实际运行数据的基础上,通过计算分析,得到了山西电网消纳风电能力容量范围,并据此提出了电网运行控制措施。通过实践运行,证明此计算分析方法基本正确,达到了提高电网消纳能力的目的。     

面向高比例新能源电网的重大耗能企业需求响应调度

随着国家“双碳”重大战略的提出,高比例新能源并网将成为我国电力能源转型的重要态势.针对火电机组、配电网和需求侧关联的系列运行约束制约了电网对高比例新能源的有效消纳这一问题,本文提出重大耗能企业这一主要电力负荷参与网需求响应(Demand response, DR)的研究思路,通过重大耗能企业与电网协调调度促进新能源消纳,并获得经济补偿以减少运行成本.研究首先基于混合需求侧响应机制,提出以重大耗能企业、新能源、火电机组为核心的协调调度方法,并根据新能源预测值-预测误差的信息依存顺序提出了两步调度策略.在此基础上,进行生产过程行为建模以实现重大耗能企业需求侧响应决策描述,并建立高比例新能源并网的重大耗能企业需求响应与电网协调调度优化模型.最后,基于烟台电网实际系统进行算例分析,验证了重大耗能企业通过需求响应参与电网协调调度以及两步调度策略的有效性.     

A reactive scheduling and control framework for integration of renewable energy sources with a reformer-based fuel cell system and an energy storage device

The main technological barrier in relying solely on renewable energy resources is that the sources such as wind and solar are highly intermittent in availability and result in uncertainty in demand satisfaction. This paper focuses on the integration of these uncertain renewable energy sources along with relatively deterministic energy sources such as reformer based fuel cell and battery. The power mix scenario between these multiple renewable energy sources along with the reformer based fuel cell system, coupled with an energy storage option is envisaged in this paper to ensure undisrupted power supply, to combat the possible intermittent nature of these renewable sources. An appropriate scheduling layer which provides a detailed plan of the optimum contribution of the various available power sources is considered over one week (7 days) duration. A model predictive control (MPC) scheme is deployed at the lower level control layer that receives a measurement of the possible fluctuations or uncertainties in the renewable power sources and maintains a smooth operation of the power generation system through appropriate decisions on generation via the reformer based fuel cell or by exploiting the battery storage, to ensure a delay-free delivery of power to the external load. During real-time operation of the plant, due to the uncertainties in the contribution from solar and wind sources, the power demanded from the fuel cell and the battery is varied accordingly by the MPC layer to meet the overall power demand. The performance of the designed MPC to maintain a smooth delivery of power in both the absence and presence of uncertainties in the renewable energy sources, with and without a reactive feedback between the scheduling and control layers, is illustrated using case studies.     

A second-order sliding mode and fuzzy logic control to optimal energy management in wind turbine with battery storage

The optimal control of large-scale wind turbine has become a critical issue for the development of renewable energy systems and their integration into the power grid to provide reliable, secure and efficient electricity, despite any possible constraints such as sudden changes in wind speed. This paper deals with the modeling and control of a hybrid system integrating a permanent magnet synchronous generator (PMSG) in variable speed wind turbine (VSWT) and batteries as energy storage system (BESS). Moreover a new supervisory control system for the optimal management and robust operation of a VSWT and a BESS is described and evaluated by simulation under wind speed variation and grid demand changes. In this way, the proposed coordinated controller has three subsystems (generator side, BESS side and grid side converters). The main function of the first one is to extract the maximum wind power through controlling the rotational speed of the PMSG, for this a maximum power point tracking algorithm based on fuzzy logic control and a second-order sliding mode control (SOSMC) theory is designed. The task of the second one is to maintain the required direct current (DC) link voltage level of the PMSG through a bidirectional DC/DC converter, whereas in the last, a (SOSMC) is investigated to achieve smooth regulation of grid active and reactive powers quantities, which provides better results in terms of attenuation of the harmonics present in the grid courant compared with the conventional first-order sliding controller. Extensive simulation studies under different conditions are carried out in MATLAB/Simulink, and the results confirm the effectiveness of the new supervisory control system.

     

Smart energy pricing for demand‐side management in renewable energy smart grids

Smart grids are expected to provide various benefits to society by integrating advances in power engineering with recent developments in the field of information and communications technology. One of the advantages is the support to efficient demand‐side management (DSM), for example, changes in consumer demands for energy based on using incentives. Indeed, DSM is expected to help grid operators balance time‐varying generation by wind and solar units, and the optimization of their usage. This paper focuses on DSM considering renewable energy generation and proposes an auction, in which consumers submit bids to renewable energy usage plans. An additional model is introduced to allow consumers to compute their bid for a given usage plan. Both models have been extended to include energy storage devices. The proposed model is compared to a system with time‐varying pricing for energy, where it is shown to allow consumers to use more appliances, to lead to a larger profit, and to reduce the peak‐to‐average ratio of energy consumption. Finally, the impact of the use of energy storage in households and in the energy provider is also considered.     

基于ADWOA算法的风光水互补系统优化调度研究

为了有效应对大规模风能和光伏并网带来的波动问题,保障电网的安全稳定运行,本研究通过深入分析风力发电、光伏发电、水利发电以及抽水蓄能之间的互补特性,构建了一个综合的互补发电系统。在此基础上,针对系统中存在的多种功率约束,本文提出了两种优化调度模型：一种旨在最小化互补系统的波动,另一种则是最小化火电机组等效负荷波动。为求解这两个优化模型,采用了改进的自适应权重优化算法（Adaptive Weight Optimization Algorithm, ADWOA）。通过仿真实验验证了该算法在两种模型中的有效性,结果表明这两种最优调度模型均能有效追踪优化目标,并显著减小由于风力和光伏发电并网引起的影响,从而增强电网的运行稳定性。     

含电动汽车充电站的多端直流微电网研究

为未来大规模能源互联网的形成以及多种新能源的接入提供技术支撑,设计直流微电网的拓扑结构,提出了一种四端口环网的直流电网拓扑结构,实现交流电网、储能单元、直流负荷、风力发电和光伏发电与直流电网的互联。首先研究了交流电网与直流电网的接口方式和相关技术参数,提出了光伏发电、风力发电和储能单元等接口的技术配置。其次,研究了整个直流微电网的启停时序,设计了直流电网的接线方式、电压等级和容量,最后基于MATLAB Simulink平台搭建了直流园区系统仿真模型,然后对典型工况进行了仿真分析：（1）储能单元由放电到能量为零;（2）储能单元由充电到能量充满;（3）VSC1变换器功率反转;（4）负荷跳变;（5）储能单元由放电到充电。这些工况基本包涵了直流微电网可能出现的运行状态,对直流微电网的运行管理有较高的参考价值。     

多虚拟电厂接入的主动配电系统优化经济调度

在市场环境下,为促进含随机性可再生能源的消纳同时协调各经济主体矛盾并挖掘各主体价值和经济效益,本文提出一种基于分析目标级联理论的主动配网调度优化模型,以配网与虚拟电厂存在电能交互为建模背景。考虑虚拟电厂组成的多样性,设置风储型虚拟电厂以及含冷热电系统型虚拟电厂,各虚拟电厂可以分别与配网进行电能交互,各经济主体根据自身组成优化内部变量以及交互功率,通过分析目标级联法与其他主体协调交互功率实现分布式求解。最后通过IEEE33节点配电系统的算例仿真表明,调度结果能较好的反应主体经济性,得出风储型虚拟电厂有利于提高风电的消纳量,冷热电联供型虚拟电厂可以实现综合能源经济管理,分析目标级联法用于本文所提的模型背景是有效的。     

Optimal reactive power dispatch with uncertainties in load demand and renewable energy sources adopting scenario-based approach

Optimizing reactive power flow in electrical network is an important aspect of system study as the reactive power supports network voltage which needs to be maintained within desirable limits for system reliability. A network consisting of only conventional thermal generators has been extensively studied for optimal active and reactive power dispatch. However, increasing penetration of renewable sources into the grid necessitates power flow studies incorporating these sources. This paper presents a formulation and solution procedure for stochastic optimal reactive power dispatch (ORPD) problem with uncertainties in load demand, wind and solar power. Appropriate probability density functions (PDFs) are considered to model the stochastic load demand and the power generated from the renewable energy sources. Numerous scenarios are created running Monte-Carlo simulation and scenario reduction technique is implemented to deal with reduced number of scenarios. Real power loss and steady state voltage deviation of load buses in the network are set as the objectives of optimization. Success history based adaptive differential evolution (SHADE) is adopted as the basic search algorithm. SHADE has been successfully integrated with a constraint handling technique, called epsilon constraint (EC) handling, to handle constraints in ORPD problem. The effectiveness of a proper constraint handling technique is substantiated with case studies for deterministic ORPD on base configurations of IEEE 30-bus and 57-bus systems using SHADE-EC algorithm. The single-objective and multi-objective stochastic ORPD cases are also solved using the SHADE-EC algorithm. The results are discussed, compared and critically analyzed in this study.     

Optimal management of wind and solar energy resources

This paper presents a portfolio-based approach to the harvesting of renewable energy (RE) resources. Our examined problem setting considers the possibility of distributing the total available capacity across an array of heterogeneous RE generation technologies (wind and solar power production units) being dispersed over a large geographical area. We formulate the capacity allocation process as a bi-objective optimization problem, in which the decision maker seeks to increase the mean productivity of the entire array while having control on the variability of the aggregate energy supply. Using large-scale optimization techniques, we are able to calculate – to an arbitrary degree of accuracy – the complete set of Pareto-optimal configurations of power plants, which attain the maximum possible energy delivery for a given level of power supply risk. Experimental results from a reference geographical region show that wind and solar resources are largely complementary. We demonstrate how this feature could help energy policy makers to improve the overall reliability of future RE generation in a properly designed risk management framework.     

电力系统一二次调频的反馈微分博弈协同控制

风能等间歇式能源并网将是未来电网发展趋势,其输出功率的波动将加剧一二次调频之间的冲突反调问题.本文将反馈微分博弈应用于电力系统频率控制中,建立起一二次调频的协同控制模型,并考虑调速器死区、控制动作幅值限制、机组爬坡速率约束等工程实际因素,用协同进化算法求得该模型的反馈纳什均衡解.用仿真验证了该方法在满足各种工程因素下有效解决一二次调频的冲突反调问题,充分挖掘了系统蕴藏的调频能力.     

受成本约束的电力信息?物理相依系统鲁棒性优化设计

针对复杂网络视角,考虑到电力网络存在扩建等现实问题,研究受成本约束下如何增设站点从而优化负荷分布、改善系统的鲁棒性。基于华中地区某省电力网的拓扑结构数据,构建了电力网与信息网部分一一对应的相依网络模型,并采用非线性负载?容量模型作为系统的级联失效模型。考虑实际电力网中超前规划新增厂站的现实情况,提出4种可能的增设电力节点及其信息设备对应的节点配置优化策略,并对华中某省电力网及IEEE 118 总线的电力信息?物理系统在4种节点配置策略下的电力负荷优化及系统鲁棒性进行仿真及分析。仿真结果表明:以配置的物理节点连接网络中大电力负荷及小电力负荷节点为基准时,仅需配置较少的节点就能达到既定的优化度。本结论对于电力系统在建设与规划过程中将有限资源进行较优分配具有一定的指导意义。     

Passivity-based control design for a grid-connected hybrid generation system integrated with the energy management strategy

Hybrid generation systems produce electric energy from a wide variety of energy sources, including renewable sources. A hybrid system based on renewable sources usually consists of two or more renewable energy sources with the possibility of including storage units so as to enhance the reliability of the system. The hybrid system requires an energy strategy that determines the operation point of each element of the system depending on multiple variables and subjected to the constraints inherent in this kind of systems. In addition, the system needs controllers to command each of these elements in order to reach the operation point established by the energy strategy. Here, we propose a control design via passivity-based control integrated with an energy management strategy for a hybrid generation system based on solar energy and coupled with the grid. The performance of the control methodology is extensively assessed through computer simulation using a comprehensive nonlinear model of the plant. The results show that the controlled system accomplishes the control tasks with good responses, working under very different atmospheric conditions and required load power.     

Perspectives in modeling for control of power networks

Increasing integration of renewable energy sources in the power grid leads to a complete re-thinking of its operation. This necessitates the consideration of new modeling and analysis approaches, which can serve as natural starting points for robust and scalable control and design strategies.In this ‘vision’ paper we will highlight two topics within the broad area of power networks: the modeling and analysis of the synchronous generator, and the modeling and analysis of power networks using the swing equation as an approximate model for the generator. In both cases we will discuss a port-Hamiltonian formulation, which reflects the underlying physics of power flow and energy storage. Although the port-Hamiltonian model of the synchronous generator reveals a clear structure it still poses fundamental challenges for its non-zero steady state stability analysis. It is shown how the swing equation can be directly deduced from the power balance of the port-Hamiltonian model of the synchronous generator. Under the phasor assumption, this leads to a port-Hamiltonian model of power networks of generators, which enables a straightforward stability analysis and provides a starting point for control.