Three-Level Optimal Scheduling and Power Allocation Strategy for Power System ContainingWind-Storage Combined Unit

To mitigate the impact of wind power volatility on power system scheduling,this paper adopts the wind-storage combined unit to improve the dispatchability of wind energy.And a three-level optimal scheduling and power allocation strategy is proposed for the system containing the wind-storage combined unit.The strategy takes smoothing power output as themain objectives.The first level is the wind-storage joint scheduling,and the second and third levels carry out the unit combination optimization of thermal power and the power allocation of wind power cluster(WPC),respectively,according to the scheduling power of WPC and ESS obtained from the first level.This can ensure the stability,economy and environmental friendliness of the whole power system.Based on the roles of peak shaving-valley filling and fluctuation smoothing of the energy storage system(ESS),this paper decides the charging and discharging intervals of ESS,so that the energy storage and wind power output can be further coordinated.Considering the prediction error and the output uncertainty of wind power,the planned scheduling output of wind farms(WFs)is first optimized on a long timescale,and then the rolling correction optimization of the scheduling output of WFs is carried out on a short timescale.Finally,the effectiveness of the proposed optimal scheduling and power allocation strategy is verified through case analysis.

Unit Commitment under the Environment of Wind Power and Large-Scale Bilateral Transactions

Bilateral electric power contract is settled based on contract output curve. This paper considered the bilateral transactions execution, new energy accommodation, power grid security and generation economy, considering the executive priority of different power components to establish a multi-objective coordination unit commitment model. Through an example to verify the effectiveness of the model in promoting wind power consumption, guaranteeing trade execution, and improving power generation efficiency, and analyzed the interactions to each other among the factors of wind power, trading and blocking. According to the results, when wind power causes reverse power flow in the congestion line, it will promote the implementation of contracts, the influence of wind power accommodation to trade execution should be analyzed combined with the grid block, the results can provide reference for wind power planning.

Discussion on Key Points of Wind Load of Jack-up Unit

The anti-overturning ability and structure safety of jack-up unit in in-place condition are often affected by environment loads, especially wind load. According to the MODU rule, the projected area method is used for calculating the wind load. However, the calculated results are conservative and not good for structure optimization design. In this paper, a 400 ft jack-up is studied as an example. Based on the wind tunnel test and numerical simulation method, some key points of wind load calculation, such as shielding effect, lift effect and shape coefficient of component, are discussed. The study shows that the points mentioned above, which are ignored in the MODU rule calculation, result in the conservative result.

Grid Integration of Wind Generation Considering Remote Wind Farms:Hybrid Markovian and Interval Unit Commitment

Grid integration of wind power is essential to reduce fossil fuel usage but challenging in view of the intermittent nature of wind.Recently,we developed a hybrid Markovian and interval approach for the unit commitment and economic dispatch problem where power generation of conventional units is linked to local wind states to dampen the effects of wind uncertainties.Also,to reduce complexity,extreme and expected states are considered as interval modeling.Although this approach is effective,the fact that major wind farms are often located in remote locations and not accompanied by conventional units leads to conservative results.Furthermore,weights of extreme and expected states in the objective function are difficult to tune,resulting in significant differences between optimization and simulation costs.In this paper,each remote wind farm is paired with a conventional unit to dampen the effects of wind uncertainties without using expensive utility-scaled battery storage,and extra constraints are innovatively established to model pairing.Additionally,proper weights are derived through a novel quadratic fit of cost functions.The problem is solved by using a creative integration of our recent surrogate Lagrangian relaxation and branch-and-cut.Results demonstrate modeling accuracy,computational efficiency,and significant reduction of conservativeness of the previous approach.

Effect of Angle of Attack and Blade Tip Vortex on the Noise Level of Tandem Wind Rotors of an Intelligent Wind Power Unit

The authors have invented a superior wind power unit, which is composed of tandem wind rotors and double rotational armature type generator without the traditional stator. This unit is called ＂intelligent wind power unit＂. At upwind type unit, the large-sized front wind rotor and the small-sized rear wind rotor drive the inner and the outer rotational armatures respectively, in keeping the rotational torque counter-balance between both wind rotors/armatures. This paper discusses the acoustic noise emitted from the tandem wind rotors. As for tandem wind rotors, the tip vortex shedding from the front wind rotor may make a loud acoustic noise if the vortex attacks the rear wind rotor. Intelligent wind power unit, however, has no chance to increase the acoustic noise level by the tip vortex because the diameter of the front wind rotor is reasonably larger than the diameter of the rear wind rotor. The vorticity generated in the boundary layer on the blade can be observed obviously at wake flow and can be evaluated quantitatively at flow conditions measured by a hot-wire anemometer at a wind tunnel. The flow conditions have shown that the radial and axial components of vorticities contribute to emit the acoustic noise.

Optimal Intelligence Planning of Wind Power Plants and Power System Storage Devices in Power Station Unit Commitment Based

Renewable energy sources(RES)such as wind turbines(WT)and solar cells have attracted the attention of power system operators and users alike,thanks to their lack of environmental pollution,independence of fossil fuels,and meager marginal costs.With the introduction of RES,challenges have faced the unit commitment(UC)problem as a traditional power system optimization problem aiming to minimize total costs by optimally determining units’inputs and outputs,and specifying the optimal generation of each unit.The output power of RES such as WT and solar cells depends on natural factors such as wind speed and solar irradiation that are riddled with uncertainty.As a result,the UC problem in the presence of RES faces uncertainties.The grid consumed load is not always equal to and is randomly different from the predicted values,which also contributes to uncertainty in solving the aforementioned problem.The current study proposes a novel two-stage optimization model with load and wind farm power generation uncertainties for the security-constrained UC to overcome this problem.The new model is adopted to solve the wind-generated power uncertainty,and energy storage systems(ESSs)are included in the problem for further management.The problem is written as an uncertain optimization model which are the stochastic nature with security-constrains which included undispatchable power resources and storage units.To solve the UC programming model,a hybrid honey bee mating and bacterial foraging algorithm is employed to reduce problem complexity and achieve optimal results.

2-MW wind power unit successfully manufactured

As of the end of April, by autonomous research anddevelopment on the basis of imported technologies,Beijing Beizhong Steam-Turbo Machinery Company Ltd.had successfully completed trial production of a 2-MWlow-temperature type wind power generating unit; andnow the company has put the new type of wind

Source-Load Coordinated Optimal Scheduling Considering the High Energy Load of Electrofused Magnesium and Wind Power Uncertainty

In fossil energy pollution is serious and the“double carbon”goal is being promoted,as a symbol of fresh energy in the electrical system,solar and wind power have an increasing installed capacity,only conventional units obviously can not solve the new energy as the main body of the scheduling problem.To enhance the systemscheduling ability,based on the participation of thermal power units,incorporate the high energy-carrying load of electro-melting magnesiuminto the regulation object,and consider the effects on the wind unpredictability of the power.Firstly,the operating characteristics of high energy load and wind power are analyzed,and the principle of the participation of electrofusedmagnesiumhigh energy-carrying loads in the elimination of obstructedwind power is studied.Second,a two-layer optimization model is suggested,with the objective function being the largest amount of wind power consumed and the lowest possible cost of system operation.In the upper model,the high energy-carrying load regulates the blocked wind power,and in the lower model,the second-order cone approximation algorithm is used to solve the optimizationmodelwithwind power uncertainty,so that a two-layer optimizationmodel that takes into account the regulation of the high energy-carrying load of the electrofused magnesium and the uncertainty of the wind power is established.Finally,the model is solved using Gurobi,and the results of the simulation demonstrate that the suggested model may successfully lower wind abandonment,lower system operation costs,increase the accuracy of day-ahead scheduling,and lower the final product error of the thermal electricity unit.

Operation of offshore wind farms connected with DRU-HVDC transmission systems with special consideration of faults

The diode rectifier unit(DRU)-based high-voltage DC(DRU-HVDC) system is a promising solution for offshore wind energy transmission thanks to its compact design, high efficiency, and strong reliability. Herein we investigate the feasibility of the DRU-HVDC system considering onshore and offshore AC grid faults, DC cable faults, and internal DRU faults. To ensure safe operation during the faults, the wind turbine(WT) converters are designed to operate in either current-limiting or voltage-limiting mode to limit potential excessive overcurrent or overvoltage. Strategies for providing fault currents using WT converters during offshore AC faults to enable offshore overcurrent and differential fault protection are investigated. The DRU-HVDC system is robust against various faults, and it can automatically restore power transmission after fault isolation. Simulation results confirm the system performance under various fault conditions.

Feasibility of replacing the 3-coach with a 1.5-coach grouping trainmodel in wind tunnel experiment at different yaw angles

The effects of different yaw angles on the aerodynamic performance of city electric multiple units(EMUs)were investigated in a wind tunnel using a 1:16.8 scaled model.Pressure scanning valve and six-component box-type aerodynamic balance were used to test the pressure distribution and aerodynamic force of the head car respectively from the 1.5-and 3-coach grouping city EMU models.Meanwhile,the effects of the yaw angles on the pressure distribution of the streamlined head as well as the aerodynamic forces of the train were analyzed.The experimental results showed that the pressure coefficient was the smallest at the maximum slope of the main shape-line.The side force coefficient and pressure coefficient along the head car cross-section were most affected by crosswind when the yaw angle was 55°,and replacing a 3-coach grouping with a 1.5-coach grouping had obvious advantages for wind tunnel testing when the yaw angle was within 24.2°.In addition,the relative errors of lift coefficient C_(L),roll moment coefficient C_(Mx),side force coefficient C_(S),and drag coefficient C_(D) between the 1.5-and 3-coach cases were below 5.95%,which all met the requirements of the experimental accuracy.

Optimization of Minimum Power Output for Combined Heat and Power Units Considering Peak Load Regulation Ability

Northern China has rich wind power and photovoltaic renewable resources. Combined Heat and Power (CHP) Units to meet the load demand and limit its peaking capacity in winter, to a certain extent, it results in structural problems of wind-solar power and thermoelectric. To solve these problems, this paper proposes a plurality of units together to ensure supply of heat load on the premise, by building a thermoelectric power peaking considering thermal load unit group dynamic scheduling model, to achieve the potential of different thermoelectric properties peaking units of the excavation. Simulation examples show, if the unit group exists obvious relationship thermoelectric individual differences, the thermal load dynamic scheduling can be more significantly improved overall performance peaking unit group, effectively increase clean energy consumptive.

Big-M based MILP method for SCUC considering allowable wind power output interval and its adjustable conservativeness

In contrast to most existing works on robust unit commitment(UC),this study proposes a novel big-M-based mixed-integer linear programming(MILP)method to solve security-constrained UC problems considering the allowable wind power output interval and its adjustable conservativeness.The wind power accommodation capability is usually limited by spinning reserve requirements and transmission line capacity in power systems with large-scale wind power integration.Therefore,by employing the big-M method and adding auxiliary 0-1 binary variables to describe the allowable wind power output interval,a bilinear programming problem meeting the security constraints of system operation is presented.Furthermore,an adjustable confidence level was introduced into the proposed robust optimization model to decrease the level of conservatism of the robust solutions.This can establish a trade-off between economy and security.To develop an MILP problem that can be solved by commercial solvers such as CPLEX,the big-M method is utilized again to represent the bilinear formulation as a series of linear inequality constraints and approximately address the nonlinear formulation caused by the adjustable conservativeness.Simulation studies on a modified IEEE 26-generator reliability test system connected to wind farms were performed to confirm the effectiveness and advantages of the proposed method.

ELMAN Neural Network with Modified Grey Wolf Optimizer for Enhanced Wind Speed Forecasting

The scope of this paper is to forecast wind speed. Wind speed, temperature, wind direction, relative humidity, precipitation of water content and air pressure are the main factors make the wind speed forecasting as a complex problem and neural network performance is mainly influenced by proper hidden layer neuron units. This paper proposes new criteria for appropriate hidden layer neuron unit’s determination and attempts a novel hybrid method in order to achieve enhanced wind speed forecasting. This paper proposes the following two main innovative contributions 1) both either over fitting or under fitting issues are avoided by means of the proposed new criteria based hidden layer neuron unit’s estimation. 2) ELMAN neural network is optimized through Modified Grey Wolf Optimizer (MGWO). The proposed hybrid method (ELMAN-MGWO) performance, effectiveness is confirmed by means of the comparison between Grey Wolf Optimizer (GWO), Adaptive Gbest-guided Gravitational Search Algorithm (GGSA), Artificial Bee Colony (ABC), Ant Colony Optimization (ACO), Cuckoo Search (CS), Particle Swarm Optimization (PSO), Evolution Strategy (ES), Genetic Algorithm (GA) algorithms, meanwhile proposed new criteria effectiveness and precise are verified comparison with other existing selection criteria. Three real-time wind data sets are utilized in order to analysis the performance of the proposed approach. Simulation results demonstrate that the proposed hybrid method (ELMAN-MGWO) achieve the mean square error AVG ± STD of 4.1379e-11 ± 1.0567e-15, 6.3073e-11 ± 3.5708e-15 and 7.5840e-11 ± 1.1613e-14 respectively for evaluation on three real-time data sets. Hence, the proposed hybrid method is superior, precise, enhance wind speed forecasting than that of other existing methods and robust.

Houshiheisan compound prescription protects neurovascular units after cerebral ischemia

Houshiheisan is composed of wind-dispelling （chrysanthemun fower, divaricate saposhnikovia root, Manchurian wild ginger, cassia twig, Szechwan lovage rhizome, and platycodon root） and deficiency-nourishing （ginseng, Chinese angelica, large-head atractylodes rhizome, Indian bread, and zingiber） drugs. In this study, we assumed these drugs have protective effects against cerebral ischemia, on neurovascular units. Houshiheisan was intragastrically administered in a rat model of focal cerebral ischemia. Hematoxylin-eosin staining, transmission electron microscopy, immu- nofluorescence staining, and western blot assays showed that Houshiheisan reduced pathological injury to the ischemic penumbra, protected neurovascular units, visibly up-regtflated neuronal nuclear antigen expression, and down-regulated amyloid precursor protein and amyloid-[3 42 expression. Wind-dispelling and deficiency-nourishing drugs maintained NeuN expression to varying degrees, but did not affect amyloid precursor protein or amyloid-~ 42 expression in the ischemic penumbra. Our results suggest that the compound prescription Houshiheisan effectively suppresses abnormal amyloid precursor protein accumulation, reduces amyloid substance depo- sition, maintains stabilization of the internal environment of neurovascular units, and minimizes injury to neurovascular units in the ischemic penumbra.

基于特征选择及ISSA-CNN-BiGRU的短期风功率预测

针对风电功率随机性大、平稳性低,以及直接输入预测模型往往难以取得较高精度等问题,提出了一种基于特征选择及改进麻雀搜索算法(ISSA)优化卷积神经网络-双向门控循环单元(CNN-BiGRU)的短期风电功率预测方法。首先,利用变分模态分解(VMD)将原始功率分解为一组包含不同信息的子分量,以降低原始功率序列的非平稳性,提升可预测性,同时通过观察中心频率方式确定模态分解数。其次,对每一分量采用随机森林(RF)特征重要度的方法进行特征选择,从风速、风向、温度、空气密度等气象特征因素中,选取对各个分量预测贡献度较高的影响因素组成输入特征向量。然后,建立各分量的CNN-BiGRU预测模型,针对神经网络算法参数难调、手动配置参数随机性大的问题,利用ISSA对模型超参数寻优,自适应搜寻最优参数组合。最后,叠加各分量的预测值,得到最终的预测结果。以中国内蒙古某风电场实际数据进行仿真实验,与多种单一及组合预测方法进行对比,结果表明,本文所提方法相比于其他方法具有更高的预测精度,其平均绝对百分比误差值达到2.644 0%;在其他4个数据集上进行的模型准确性及泛化性验证结果显示,模型平均绝对百分比误差值分别为4.385 3%、3.174 9%、1.576 1%和1.358 8%,均保持在5.000 0%以内,证明本文所提方法具有较好的预测精度及泛化能力。

基于CEEMD-SE的CNN&LSTM-GRU短期风电功率预测

为进一步提升短期风电功率的预测精度,提出了一种基于互补集合经验模态分解-样本熵(complementary ensemble empirical mode decomposition-sample entropy,CEEMD-SE)的卷积神经网络(convolutional neural network,CNN)和长短期记忆-门控循环单元(longshorttermmemory-gatedrecurrentunit,LSTM-GRU)的短期风电功率预测模型。首先,利用互补集合经验模态分解将原始风电功率序列分解为若干本征模态函数(intrinsic mode function,IMF)分量和一个残差(residual,RES)分量,利用样本熵算法将相近的分量进行重构;其次,搭建卷积神经网络和长短期记忆网络的并行网络结构,提取数据的局部特征和时序特征,并将特征融合后输入门控循环单元网络中进行学习预测;最后,通过算例进行验证,结果表明采用该模型后预测精度得到了有效提升,其均方根误差降低了15.06%、平均绝对误差降低了15.22%、决定系数提高了1.91%。

计及风电不确定性的多场景多时段安全约束机组组合解耦求解方法

为了加速求解计及风电不确定性的安全约束机组组合问题,提出计及风电不确定性的多场景多时段安全约束机组组合解耦求解方法。将原问题解耦为多个场景的安全约束机组组合问题;通过将各场景的调度时段分为多个子时段对各场景安全约束机组组合问题进行解耦,形成多个并行的子问题;为了确保多场景解耦和多时段解耦解的可行性,利用一致性约束耦合不同的子问题,并在目标函数中添加惩罚项。通过算例分析验证了所提方法的有效性。结果表明,在可接受的精度下,所提方法比传统集中式方法显著缩短了多场景安全约束机组组合问题的求解时间。

考虑负荷侧惯量不确定性的机组组合

针对新能源高占比电力系统的频率安全问题和频率安全评价指标中只考虑电源侧惯量的问题,提出一种考虑电源侧惯量和负荷侧惯量并计及预测误差随机性的安全约束机组组合优化模型。首先,推导包含系统整体惯量的频率变化率和频率最低点公式。然后,深入研究电网调度运行的不确定因素,利用蒙特卡洛对风电功率预测误差概率分布模型抽样生成典型场景,利用随机规划理论对负荷侧惯量预测误差建模,在机会约束规划的基础上将其纳入频率约束中,建立随机机会约束的频率安全机组组合优化模型。最后,通过改进的10机算例,验证所提模型的经济性和频率安全性。

考虑太阳能辅助碳捕集技术的综合能源生产单元随机低碳调度策略

为解决综合能源生产单元(integrated energy production unit,IEPU)中燃煤机组碳捕集过程的高能耗问题,同时应对新能源不确定性对运行调度带来的挑战,该文提出一种考虑太阳能辅助碳捕集技术的IEPU随机低碳调度策略,旨在实现IEPU的多能协同与低碳运行。首先,对含太阳能辅助碳捕集热电联产单元(combined heat and power based on solar-assisted carbon capture,CHP-SACC)的能量流动与运行机理进行分析,并构建其运行模型;其次,考虑风电不确定性带来的影响,提出一种基于条件最小二乘生成对抗网络(conditional-least squares generative adversarial networks,C-LSGANs)的可再生能源场景生成方法来提高场景的生成质量;然后,考虑异质能流耦合约束、多元设备运行约束以及能量平衡约束等,以最大化系统运行收益期望为目标构建IEPU随机低碳调度模型;最后,在算例仿真中设置不同的运行策略验证所提低碳转型方案的有效性,并分析了能源价格、设备容量等因素对系统运行收益的影响。

具备黑启动和构网能力的远海风电经DRU-MMC送出方案

由于具有成本低、体积重量小和可靠性高等特点,送端采用二极管整流器(DRU)、受端采用模块化多电平换流器(MMC)的送出方案在远海风电送出领域备受关注。鉴于DRU不能构建交流电网且无法倒送有功功率,文中提出一种具备黑启动和构网能力的远海风电经DRU-MMC送出方案。所提方案在DRU-MMC送出技术的基础上增加了常规小容量电压源型辅助换流器、耗能单元和必要的快速开关,通过直流海缆复用和快速开关倒闸重构拓扑,分别构建黑启动电源低压回路和风电传输高压回路,实现黑启动和功率传输2种工况在线切换;提出辅助换流器在不同运行阶段的构网控制策略,解决海上交流电网构建、DRU无功补偿和谐波抑制等问题,消除DRU-MMC送出方案对风电场类型的限制。最后,通过经济性分析和算例仿真,验证了所提方案的优越性和有效性。