Optimal Configuration Method for the Installed Capacity of the Solar-Thermal Power Stations

Because of the randomness of wind power and photovoltaic(PV)output of new energy bases,the problem of peak regulation capability and voltage stability of ultra-high voltage direct current(UHVDC)transmission lines,we proposed an optimum allocation method of installed capacity of the solar-thermal power station based on chance constrained programming in this work.Firstly,we established the uncertainty model of wind power and PV based on the chance constrained planning theory.Then we used the K-medoids clusteringmethod to cluster the scenarios considering the actual operation scenarios throughout the year.Secondly,we established the optimal configuration model based on the objective function of the strongest transient voltage stability and the lowest overall cost of operation.Finally,by quantitative analysis of actual wind power and photovoltaic new energy base,this work verified the feasibility of the proposed method.As a result of the simulations,we found that using the optimal configuration method of solar-thermal power stations could ensure an accurate allocation of installed capacity.When the installed capacity of the solar-thermal power station is 1×106 kW,the transient voltage recovery index(TVRI)is 0.359,which has a strong voltage support capacity for the system.Based on the results of this work,the optimal configuration of the installed capacity of the solar-thermal power plant can improve peak shaving performance,transient voltage support capability,and new energy consumption while satisfying the Direct Current(DC)outgoing transmission premise.

Multi-objective coordination optimal model for new power intelligence center based on hybrid algorithm

In order to resolve the coordination and optimization of the power network planning effectively, on the basis of introducing the concept of power intelligence center (PIC), the key factor power flow, line investment and load that impact generation sector, transmission sector and dispatching center in PIC were analyzed and a multi-objective coordination optimal model for new power intelligence center (NPIC) was established. To ensure the reliability and coordination of power grid and reduce investment cost, two aspects were optimized. The evolutionary algorithm was introduced to solve optimal power flow problem and the fitness function was improved to ensure the minimum cost of power generation. The gray particle swarm optimization (GPSO) algorithm was used to forecast load accurately, which can ensure the network with high reliability. On this basis, the multi-objective coordination optimal model which was more practical and in line with the need of the electricity market was proposed, then the coordination model was effectively solved through the improved particle swarm optimization algorithm, and the corresponding algorithm was obtained. The optimization of IEEE30 node system shows that the evolutionary algorithm can effectively solve the problem of optimal power flow. The average load forecasting of GPSO is 26.97 MW, which has an error of 0.34 MW compared with the actual load. The algorithm has higher forecasting accuracy. The multi-objective coordination optimal model for NPIC can effectively process the coordination and optimization problem of power network.

Research on Grid Planning of Dual Power Distribution Network Based on Parallel Ant Colony Optimization Algorithm

A distribution network plays an extremely important role in the safe and efficient operation of a power grid.As the core part of a power grid’s operation,a distribution network will have a significant impact on the safety and reliability of residential electricity consumption.it is necessary to actively plan and modify the distribution network’s structure in the power grid,improve the quality of the distribution network,and optimize the planning of the distribution network,so that the network can be fully utilized to meet the needs of electricity consumption.In this paper,a distribution network grid planning algorithm based on the reliability of electricity consumption was completed using ant colony algorithm.For the distribution network structure planning of dual power sources,the parallel ant colony algorithm was used to prove that the premise of parallelism is the interactive process of ant colonies,and the dual power distribution network structure model is established based on the principle of the lowest cost.The artificial ants in the algorithm were compared with real ants in nature,and the basic steps and working principle of the ant colony optimization algorithm was studied with the help of the travelling salesman problem(TSP).Then,the limitations of the ant colony algorithm were analyzed,and an improvement strategy was proposed by using python for digital simulation.The results demonstrated the reliability of model-building and algorithm improvement.

LMP Congestion Management Using Enhanced STF-LODF in Deregulated Power System

Nowadays electricity market industry is become a major impact on power system for privatization and deregulation of power in global wise. As per the limitation of the transmission system, the complexity arises and the supply fact will be with demand at the time of balancing. The congestion of the power system is occurring based on the transmission limits of the power desire and amount for operating the system. In order to avoid transmission line congestion, enhanced STF-LODF method is proposed. It shows the regulated line transmission flow with generating units by implementing renewable energy resources (RER) based on enhanced STF-LODF in power systems. It avoids the congestion of transmission line frequently in the power system and manages price based on pricing and sensitivity approach, and also manages optimal location of congestion transmission and instability issues of voltage. The congestion management of Locational Marginal Pricing (LMP) is performed with minimum line loss, less cost, line flow, better sensitivity and better performances in optimal power flow and control flow. The efficiency of the proposed power system is analyzed and verified by the simulation results of tested IEEE 14 bus system.

Model development and parameter investigation of a column-type electric power steering system

In this paper, the performance of a column-type electric power steering （EPS） system and vehicle has been studied and a detailed mathematical model for the system has been established. Based on the mathematic model of the optimization design for steering feel, the parameters of the EPS system and vehicle on steering performance have been investigated. Moreover, the effects of the parameters on system stability have been analyzed and compared by the method of absolute sensitivity and the results are given in the end.

Optimal Feeder Routing in Urban Distribution Networks Planning with Layout Constraints and Losses

We address the problem of optimally re-routing the feeders of urban distribution network in Milano,Italy,which presents some peculiarities and significant design challenges.Milano has two separate medium-voltage(MV)distribution networks,previously operated by two different utilities,which grew up independently and incoordinately.This results in a system layout which is inefficient,redundant,and difficult to manage due to different operating procedures.The current utility UNARETI,which is in charge of the overall distribution system,aims at optimally integrating the two MV distribution networks and moving to a new specific layout that offers advantages from the perspectives of reliability and flexibility.We present a mixed-integer programming(MIP)approach for the design of a new network configuration satisfying the so-called 2-step ladder layout required by the planner.The model accounts for the main electrical constraints such as power flow equations,thermal limits of high-voltage(HV)/MV substation transformers,line thermal limits,and the maximum number of customers per feeder.Real power losses are taken into account via a quadratic formulation and a piecewise linear approximation.Computational tests on a small-scale system and on a part of the Milano distribution network are reported.

Important Issues and Results When Considering the Stochastic Representation of Wind Power Plants in a Generation Optimization Model: An Application to the Large Brazilian Interconnected Power System

Wind power has an increasing share of the Brazilian energy market and may represent 11.6% of total capacity by 2024. For large hydro-thermal systems having high-storage capacity, a complementarity between hydro and wind production could have important effects. The current optimization models are applied to dispatch power plants to meet the market demand and optimize the generation dispatches considering only hydroelectric and thermal power plants. The remaining sources, including wind power, small-hydroelectric plants and biomass plants, are excluded from the optimization model and are included deterministically. This work introduces a general methodology to represent the stochastic behavior of wind production aimed at the planning and operation of large interconnected power systems. In fact, considering the generation of the wind power source stochastically could show the complementarity between the hydro and wind power production, reducing the energy price in the spot market with the reduction of thermal power dispatches. In addition to that, with a reduction in wind power and a simultaneous dry-season occurrence, this model, is able to show the need of thermal power plants dispatches as well as the reduction of the risk of energy shortages.

Radio Network Planning and Optimization for 5G Telecommunication System Based on Physical Constraints

The paper mainly focuses on the network planning and optimization problem in the 5G telecommunication system based on the numerical investigation.There have been two portions of this work,such as network planning for efficient network models and optimization of power allocation in the 5G network.The radio network planning process has been completed based on a specific area.The data rate requirement can be solved by allowing the densification of the system by deploying small cells.The radio network planning scheme is the indispensable platform in arranging a wireless network that encounters convinced coverage method,capacity,and Quality of Service necessities.In this study,the eighty micro base stations and two-hundred mobile stations are deployed in the-15km×15km wide selected area in the Yangon downtown area.The optimization processes were also analyzed based on the source and destination nodes in the 5G network.The base stations’location is minimized and optimized in a selected geographical area with the linear programming technique and analyzed in this study.

Application of Interval Algorithm in Rural Power Network Planning

Rural power network planning is a complicated nonlinear optimized combination problem which based on load forecasting results, and its actual load is affected by many uncertain factors, which influenced optimization results of rural power network planning. To solve the problems, the interval algorithm was used to modify the initial search method of uncertainty load mathematics model in rural network planning. Meanwhile, the genetic/tabu search combination algorithm was adopted to optimize the initialized network. The sample analysis results showed that compared with the certainty planning, the improved method was suitable for urban medium-voltage distribution network planning with consideration of uncertainty load and the planning results conformed to the reality.

A New Model for Transmission Network Expansion and Reactive Power Planning in a Deregulated Environment

Transmission network expansion planning (TNEP) is a challenging issue especially in new restructured electricity mar-kets environment. TNEP can be incorporated with reactive power planning in which the operating conditions will be satisfied. In this paper a combinatorial mathematical model has been presented to solve transmission expansion and reactive power planning problem (TEPRPP) simultaneously. The proposed model is a non-convex problem having a mixed integer nonlinear nature where the number of candidate solutions to be evaluated increases exponentially according to the system size. The objective function of TEPRPP comprises the new circuits’ investment and production costs as well as load curtailment penalty payments. A real genetic algorithm (RGA) aimed to obtaining a significant quality solution to handle such a complicated problem has been employed. An interior point method (IPM) is applied to solve the proposed concurrent optimization problem in the solution steps of TEPRPP model. This paper proposes a new methodology for the best location as well as the capacity of VAr sources;it is tested on two well-known systems;the Garver and IEEE 24-bus systems. The obtained results show the capability and the viability of the proposed TEPRPP model incorporating operating conditions.

风电—光伏—光热发电系统联合优化运行研究

“风光热储”是近几年多种新能源互补发电的新模式,以有效解决用电高峰期和低谷期存在的电力输出不平衡问题,并提高能源利用率,实现清洁发展。为此研究了光热电站的运行机理和工作模式。建立了风电—光伏—光热发电系统联合优化运行模型,以高优先级优化匹配调度曲线的程度,以低优先级优化联合系统的可再生能源消纳能力。为提高风力发电、光伏发电并网的可靠性,采用预测误差描述二者出力存在的不确定性,并采用样本均值近似法对其进行了确定化处理。然后对优化模型中的非线性因素进行了线性化处理,最后调用Cplex求解器得出联合系统最佳调度方案。结果表明,光热电站可以调节联合发电系统的上网功率,使其尽可能满足调度曲线的需求;另外,采用样本均值近似法处理不确定变量,并且将优化模型线性化后,可以更加快速地求出最优解。

“人-车-桩-路-网”深度耦合下的配电网协同规划与运行优化

电动汽车(EV)作为连接交通电气化和电网清洁化的纽带和桥梁,可实现电力-交通-信息之间的深度耦合,形成电力-交通一体化的规划及运行架构。配电-交通融合系统(DTIS)中,EV充放电行为多时空动态交织、电能流-交通流-信息流深度融合、多利益主体动态博弈等大量不确定性因素使配电网的规划及运行优化的边界都将发生重大转变,但同时也给挖掘利用EV的移动储能特性和提升配电网灵活性带来了契机。为此,在分析“人-车-桩-路-网”深度耦合下配电网的形态演化特征基础上,剖析了新形态下配电网协同规划与运行优化所面临的新挑战,进而针对“人-车-桩-路-网”耦合下的EV灵活性建模、灵活域高效构建及预测、协同规划、运行优化4个方面关键技术展开讨论,并对相关技术问题的研究方向进行了展望。

考虑风光出力不确定性及相关性的配电网规划方法

新能源在电力系统中的渗透率日益提高,大大增加了电网中的不确定因素,对配电网的规划运行和控制提出了更高的要求。配电网规划是电力系统安全稳定运行的重要基石,传统配电网规划中各参数都已确定,缺乏对不确定因素的适应性。因此,提出一种基于概率潮流的配电网规划方法,首先对配电网中的不确定因素定量建模,建立源荷出力模型,其次将风速、太阳辐射与用电负荷之间的相关性用秩相关系数矩阵表征,建立计及相关性的半不变量概率潮流计算方法,最后构建以规划成本最小为目标函数,以潮流平衡、馈线容量、节点电压、网架辐射型结构为约束条件的配电网规划模型,并通过改进惯性参数与引入变异操作对粒子群算法进行改进,利用改进后的算法求解规划模型。以33节点系统为例进行仿真,结果验证了该方法能够有效降低网损,减少网络规划费用。

海上油气平台不稳定电源与储能联合配置优化策略

针对海上油气平台集群接入不稳定电源与储能的联合配置问题,结合海上风电、光伏特点及已有的拓扑结构,提出了三阶段风机/光伏/储能阶段式联合配置策略,介绍嵌入潮流计算的阶段式粒子群算法。第一阶段通过LightGBM网络预测模型得到风机光伏的时序预测发电功率,再以投资建设经济性和潮流稳定性为目标优化每个节点的风机/光伏容量;第二阶段针对不稳定电源配置后的配电网,提出了基于电压和损耗灵敏度为指标的集群划分方法,将配电网集群划分为若干个子集群;第三阶段根据划分后的子集群,以储能容量、配电网损耗和节点电压波动为目标为每个子集群内配置储能。以渤海油田某10 kV实际油气平台配电网为例,设立燃气机出力功率自定义和经济性自定义两种方案来验证联合配置优化决策的合理性。结果表明,两种配置策略都可以有效地提升海上油气平台配电网的潮流稳定性,提高新能源的渗透率。本文研究验证了海上分散式风机/光伏发电工程的可行性,有利于实现未来海上油气平台的“零碳”建设。

考虑电压-无功调节的台区互联装置规划方法

伴随分布式能源广泛接入低压配电网,其对配电网运行灵活性和消纳能力的要求不断提高。利用低压柔性互联装置将独立运行的低压配电台区分区互联,避免传统电压调节和无功补偿装置频繁动作。考虑到柔性互联装置造价昂贵,协同传统电压-无功调节装置,文中提出低压柔性互联装置的选址定容规划方法。首先,分析低压柔性互联装置拓扑和运行方式,建立其潮流模型。其次,建立低压柔性互联装置优化配置的双层规划模型,上层规划以年综合费用最小为目标,下层规划考虑电压-无功协调控制时间序列模型,以运行成本和电压偏差最小为目标,基于粒子群优化算法和混合整数二阶锥规划算法交替求解,得出配电系统最优柔性互联方案和最优运行方式。最后,在IEEE 33节点系统上进行实例分析,验证该双层规划算法的有效性。结果表明,所提方法能有效减少柔性互联装置的过度布置,同时减少由分布式能源频繁波动造成的运行成本。将模型凸化并线性化的方法明显提高了求解效率。

基于降维粒子群的大电网断面功率极限计算方法

随着电力系统的发展,系统运行方式日益复杂。为了提高电力系统运行安全水平,提出一种基于降维粒子群的大电网断面功率极限计算方法。首先综合考虑大电网静态安全稳定约束和暂态稳定约束,建立断面功率极限计算模型;然后,提出了基于功率灵敏度的降维粒子群算法,根据功率灵敏度和聚合系数对可调节发电机组进行分群处理,利用降维粒子群算法计算得到了极限功率、发电机组功率调节量以及极限功率制约因素,实现了大电网断面功率极限的快速寻优。最后在我国某地区2128节点电网和我国某跨区12643节点联网中验证了该方法的有效性和正确性。

动力集中动车组动力车前后横向平稳性差异研究

针对动力集中动车组动力车现场运行前、后横向平稳性差异问题,基于动力学仿真分析方法研究其形成机理与影响因素,并提出减缓措施。采用Simpack软件建立某型动力车的动力学模型,对比抗蛇行减振器斜对称与开口向外两种布置方式,分析关键悬挂参数对车体前端和后端横向平稳性影响,并采用模态分析法研究抗蛇行减振器横向安装角对蛇行模态稳定性和车体横移摇头模态相位差的影响;以线性稳定性和车体前、后端横向平稳性指标为优化目标,对抗蛇行减振器阻尼、等效串联刚度以及横向安装角进行多目标优化,并根据计算结果对优化参数进行Sobol全局敏感性分析。结果表明:抗蛇行减振器采用斜对称布置方式时,车体前端与后端的横向平稳性差异受悬挂参数影响较小,横向安装角对动力车横向稳定性不敏感;采用开口向外布置方式时,抗蛇行减振器适当横向安装角度显著降低甚至消除车体前端和后端横向平稳性差异,且车体横向平稳性和线性稳定性对横向安装角均较为敏感,建议优化横向安装角2°~6°。

基于灵敏度因子的随机电网规划方法

针对常规电网规划考虑系统灵活性不足的问题,建立多场景的不确定电网规划模型,该模型以设备投资成本和运行费用综合最小为目标,嵌入安全约束机组组合模型以充分反映系统灵活性的平衡;同时,鉴于常规电网规划模型规模过大,计算效率低下,提出一种基于灵敏度因子的电网规划方法,建立候选线路投建状态变量对输电断面约束的灵敏度模型,消除传统电网规划中的节点相角变量,实现线路和断面潮流的解耦,从而大幅提高电网规划求解效率。IEEE 118节点算例和实际电网算例的结果表明:对新能源消纳率的过高追求可能会导致巨大电网投资成本;同时,在中大型电力系统中,基于灵敏度因子的电网规划计算效率优势明显,从而验证模型和算法的有效性。

Development modes analysis of renewable energy power generation in North Africa

North African countries generally have strategic demands for energy transformation and sustainable development.Renewable energy development is important to achieve this goal.Considering three typical types of renewable energies—wind,photovoltaic(PV),and concentrating solar power(CSP)—an optimal planning model is established to minimize construction costs and power curtailment losses.The levelized cost of electricity is used as an index for assessing economic feasibility.In this study,wind and PV,wind/PV/CSP,and transnational interconnection modes are designed for Morocco,Egypt,and Tunisia.The installed capacities of renewable energy power generation are planned through the time sequence production simulation method for each country.The results show that renewable energy combined with power generation,including the CSP mode,can improve reliability of the power supply and reduce the power curtailment rate.The transnational interconnection mode can help realize mutual benefits of renewable energy power,while the apportionment of electricity prices and trading mechanisms are very important and are related to economic feasibility;thus,this mode is important for the future development of renewable energy in North Africa.

考虑声振耦合的阻尼板声辐射拓扑优化

针对阻尼材料分布对车轮振动引起的声辐射抑制作用问题,以国内现有某直辐板型车轮阻尼板为例,结合声振耦合理论,以阻尼板一阶峰值频率激励下的声辐射功率最小化为目标函数,阻尼材料的体积分数为约束条件,通过直接求导法推导目标函数在一阶峰值频率激励下的灵敏度,采用渐进优化算法获得最优阻尼构型并基于实测频响验证了计算的准确性。研究结果表明:阻尼车轮在整个频域范围,振动频响函数幅值明显低于标准车轮,安装了经阻尼布局优化后的阻尼板车轮在2000、3150、4000 Hz处的声功率级相比全覆盖时分别下降了6、5.5、2.8 dB,声场声压级最大值下降了6.9 dB;相比优化前在(r,5)处的频响从1.76 m/s^(2)下降到0.39 m/s^(2),且高频振动响应均有所减弱。