Load Frequency Control of Multi-interconnected Renewable Energy Plants Using Multi-Verse Optimizer

A reliable approach based on a multi-verse optimization algorithm (MVO) for designing load frequency control incorporated in multi-interconnected power system comprising wind power and photovoltaic (PV) plants is presented in this paper. It has been applied for optimizing the control parameters of the load frequency controller (LFC) of the multi-source power system (MSPS). The MSPS includes thermal, gas, and hydro power plants for energy generation. Moreover, the MSPS is integrated with renewable energy sources (RES). The MVO algorithm is applied to acquire the ideal parameters of the controller for controlling a single area and a multi-area MSPS integrated with RES. HVDC link is utilized in shunt with AC multi-areas interconnection tie line. The proposed scheme has achieved robust performance against the disturbance in loading conditions, variation of system parameters, and size of step load perturbation (SLP). Meanwhile, the simulation outcomes showed a good dynamic performance of the proposed controller.     

An energy planning approach based on mixed 0–1 Multiple Objective Linear Programming

Multiple Objective Linear Programming (MOLP) models have been widely used in the energy sector for taking into account several conflicting objectives pursued in energy planning. However, continuous variables are not suffcient to accurately represent discrete phenomena encountered in many practical decision situations, such as the power generation expansion problem. This paper presents a new approach based on a mixed 0–1 MOLP model and applied to the Greek electricity generation sector for identifying the number and output of each type of power units needed to satisfy the expected electricity demand in the future. The core of the model is a branch and bound algorithm, which has been properly modified for the multi-objective case and is capable of generating the whole set of effcient solutions. The results provided by this method is the extraction of the effcient combinations of the power generation units, and for each combination the effcient solutions determining electricity production from each unit.     

小功率开关磁阻风力发电系统模拟装置研发

分析开关磁阻电机风力发电工作原理,推导其非线性数学模型,在MATLAB仿真平台上建立基于PWM斩波和APC复合控制的开关磁阻发电系统仿真模型,进行相关仿真实验,为硬件电路设计的参数选择提供帮助。以DSP为控制核心,设计开关磁阻风力发电系统功率主电路与控制电路,实现小功率风力发电。实验和性能测试验证了设计方案的可行性与有效性。     

低速直驱开关磁阻风力发电系统模拟装置研究与实现

分析开关磁阻电机的发电原理及其非线性模型,在MATLAB仿真平台上构建开关磁阻风力发电系统相应的仿真研究模型,设计一套基于DSP的低速直驱开关磁阻风力发电系统,实现低速直驱风力发电。实验和测试结果证明设计方案正确,系统运行可靠。     

电力营销信息化管理策略

随着市场经济的快速发展,我国电力经营体制的转变和电力供需矛盾逐渐缓的形势下,电力部门正逐步推行电力的信息化管理以来适应国家的可持续发展战略。本文通过分析我国电力部门信息化管理的现状,结合影响信息化管理的存在的问题,对电力营销信息化管理提出一些可行的管理建议与策略。     

Genetic Algorithm Based Smart Grid System for Distributed Renewable Energy Sources

This work presents the smart grid system for distributed Renewable Energy Sources (RES) with control methods. The hybrid MicroGrids (MG) are trending in small-scale power systems that involve distributed generations, power storage, and various loads. RES of solar are implemented with boost converter using Maximum Power Point Tracking (MPPT) with perturb and observe technique to track the maximum power. Also, the wind system is designed by permanent magnet synchronous generator that includes boost converter with MPPT technique. The battery is also employed with a Direct Current (DC)-DC bidirectional converter, and has a state of charge. The MATLAB/Simulink Simscape software is used to design the proposed model. The switching element of all converters is metal oxide semiconductor field effect transistor. The hybrid system is controlled by a voltage source controller using Proportional Integral Derivative (PID)-Genetic Algorithm (GA), and inductors-capacitors filter is used to reduce the system’s harmonics. Also, smart meters are used for monitoring purposes in residential loads. This paper analyses the performances of the MG against various scenarios.     

A two-time-scale load balancing framework for minimizing electricity bills of Internet Data Centers

Internet Data Center (IDC) is one of important emerging cyber-physical systems. To guarantee the quality of service for their worldwide users, large Internet service providers usually operate multiple geographically distributed IDCs. The enormous power consumption of these data centers may lead to both huge electricity bills and considerable carbon emissions. To mitigate these problems, on-site renewable energy plants are emerging in recent years. Since the renewable energy is intermittent, greening geographical load balancing (GGLB for short) has been proposed to reduce both the electricity bills and carbon emissions by following the renewables. However, GGLB is not able to well deal with the wildly fluctuating wind power when applied into IDCs with on-site wind energy plants. It may either fail to minimize the total electricity bills or incur the costly frequent on–off switching of servers. In order to minimize the total electricity bills of geographically distributed IDCs with on-site wind energy plants, we formulate the total electricity bills minimization problem and propose a novel two-time-scale load balancing framework TLB to solve it. First, TLB models the runtime cooling efficiency for each IDC. Then it predicts the future fine-grained (e.g., 10-min) on-site wind power output at the beginning of each scheduling period (e.g., an hour). After that, TLB transforms the primal optimization problem into a typical mixed-integer linear programming problem and solves it to finally obtain the optimal scheduling policy including the open server number as well as the request routing policy. It is worth noting that the open server number of each IDC will remain the same during each scheduling period. As an application instance of TLB, we also design a two-time-scale load balancing algorithm TLB-ARMA for our experimental scenario. Evaluation results based on real-life traces show that TLB-ARMA is able to reduce the total electricity bills by as much as 12.58 % compared with the hourly executed GGLB without incurring the costly repeated on–off switching of servers.     

兆瓦级直驱型风力风电变流系统的设计

在综合比较当前适合直驱型风力发电机组的各种变流电路的基础上,提出了一种兆瓦级直驱型风力发电变流系统的设计结构,即采用不控整流+升压斩波+SPWM逆变的变流器将电机发出的电能转换为可接人电网的恒频恒压的交流电;详细介绍了直驱型风力风电系统的组成结构及其变流系统的控制原理,给出了一种在考虑现有开关器件功率水平的情况下符合大功率直驱并网型风力发电机组要求的变流电路拓扑结构,并给出了相应的主要部分的具体应用电路。     

自动抄表系统中电能表的设计

自动抄表系统是电力部门实现自动化的组成部分,电能表又是该系统中重要的终端设备.利用电量计量技术、嵌入式控制技术、电力线载波通信技术和红外通信技术,完成了多功能电能表的设计.该电能表计量准确,具有远程抄表和近距离红外抄表功能,在结构上兼顾多种电力线载波方式,便于选择不同载波方式来实现远程通信,提高了不同通信方式下电能表的...     

张家口供电气象服务系统的设计与应用

按照供电公司需求,结合本单位实际业务,参考其他气象部门对电力公司的服务经验,利用Visual Basic6.0、Access数据库设计开发了供电气象服务系统,最终实现系统化提供有针对性气象信息,以期为电力部门提供预测服务。     

风光柴蓄复合智能供电系统的计算机控制系统

风光柴蓄复合智能供电系统是一种能够充分利用自然风力和太阳能的供电系统。文中介绍了它的供电机理。对其基于牛顿系列远端智能控制模块的计算机控制系统的硬件组成及软件设计方法进行了系统的阐述，论述了其计算机控制系统的特点。     

风光气储联合发电最优容量配比问题研究

开发和利用农村的风能、光能、沼气是解决偏远农村地区用电量快速增加和偏远山区供电问题的有效途径,该文针对3种可再生能源和储能的联合发电问题,通过研究它们之间的协调互补性,提出了一种新型的"风光气储"多能源互补的微电网供电系统,在该系统中因地制宜地采用沼气和蓄电池作为备用电源,通过改进的鲸鱼算法对"风光气储"联合运行问题进行了优化,仿真实验结果表明在成本最低和弃风弃光率最低这2个目标下都能稳定的运行,对已经有的粒子群算法、遗传算法和鲸鱼算法进行了对比,实验结果表明改进的鲸鱼算法在解决"风光气储"最优容量配比问题上得到了很大的提升。     

A new wind power prediction method based on ridgelet transforms,hybrid feature selection and closed-loop forecasting

To reduce network integration and boost energy trading, wind power forecasting can play an important role in power systems. Furthermore, the uncertain and nonconvex behavior of wind signals make its prediction complex. For this purpose, accurate prediction tools are needed. In this paper, a ridgelet transform is applied to a wind signal to decompose it into sub-signals. The output of ridgelet transform is considered as input of new feature selection to identify the best candidates to be used as the forecast engine input. Finally, a new hybrid closed loop forecast engine is proposed based on a neural network and an intelligent algorithm to predict the wind signal. The effectiveness of the proposed forecast model is extensively evaluated on a real-world electricity market through a comparison with well-known forecasting methods. The obtained numerical results demonstrate the validity of proposed method.     

考虑风电消纳的居民小区电动汽车有序充电控制方法

随着电动汽车的保有量不断提升,其充电过程对电网的影响也不断加大。为降低电动汽车无序充电对电网的冲击,提升清洁风电的消纳,提出一种居民小区电动汽车有序充电控制方法。方法使用居民小区的电力预测信息与当地风电产生预测信息,计算获取理想风电消纳的小区电动汽车充电负荷参考曲线。在参考曲线的基础上,使用差分进化算法优化可以得到电动汽车充电功率预分配曲线。在实际应用的实时分配问题上,给出了合适的功率分配策略。最后通过算例仿真实验,验证了算法的有效性。仿真实验表明,提出的电动汽车有序充电控制方法具有较好的有效性和实用性。     

煤矿安全监控系统嵌入式在线检测装置软件架构设计

嵌入式在线检测装置是煤矿安全监控系统嵌入式在线检测系统的主要组成部分,用于在线检测煤矿井下甲烷浓度超限声光报警功能和断电/复电控制功能、甲烷风电闭锁功能、系统控制响应时间和实际巡检周期、系统传感器实际配置数量、甲烷传感器稳定性等。文章详细介绍了嵌入式在线检测装置的软件架构设计及各组成部分的工作流程及功能。该架构设计使得软件的每一个功能由多个子程序模块组合实现,各个子程序模块可并行执行,提高了程序的运行速度。     

基于RBF神经网络的短期负荷预测

短期电力负荷预测是电力系统运行调度中一项重要的内容,传统的电力负荷预测方法都是建立在线性假设基础之上,由于预测精度低,难以满足现在电力部门的要求。人工神经网络己被应用在电力负荷预测中,并取得了较为理想的结果。主要基于神经网络的负荷预测模型,通过MATLAB仿真实验平台,构建RBF神经网络模型,并用历史电力负荷数据进行训练,成功的进行了电力系统的短期负荷预测,预测结果误差较小,取得了令人满意的结果。     

基于电力交易的大工业板块指数的设计及模拟仿真

随着2015年(中发〔2015〕9号)文的发布，我国新一轮电力体制改革拉开了序幕，贵州成为全国首批电力体制改革综合试点省区。贵州在电力体制改革方面先行先试，完成了“全国首个多股东有限公司制省级电力交易机构的组建、全国首创1+4电力交易指数体系等”多个全国首创。本文在全国首创的1+4电力交易指数体系基础上，用大数据手段深入挖掘电力交易过程中蕴藏的工业生产和社会经济发展信息，设计了基于电力交易大工业的板块指数。该指数结合贵州大工业类别，建立了板块指数模型，并通过近年来的大工业生产数据对模型进行分析与评价。行业板块指数是全国首创1+4电力交易指数体系的进一步补充与深化，对全省大工业企业的运行决策有一定的借鉴与参考作用。     

永磁直驱风力发电系统变流器的设计与仿真

由两相旋转坐标系下的数学模型,推导了得出了并网逆变器双闭环控制方法,并且对电流环的设计做了详细的介绍.根据控制原理在MATLAB环境下搭建了永磁直驱风力发电系统的仿真模型,进行了仿真实验.仿真结果表明,在风速变化的情况下,并网逆变器可以向电网输出稳定可靠的电能,系统稳态、暂态性能良好.     

时分割脉冲调宽技术在电动汽车充电设施仪表校验中的应用

电动汽车作为一种以车载电源为源动力驱动的新型汽车,是一种具有着良好发展空间的环保交通工具.作为这种绿色交通工具发展的前提基础,充电设施的完善、电力部门和电力企业对充电计量的规范标准化就显得尤为重要.而做好充电计量仪表的校准工作更是让充电能够规范标准化的关键.利用时分割脉冲调宽技术可以提高高精度基准电压的精度确保校准仪器时稳定度以及准确度.     

A bottom-up optimization model for the long-term energy planning of the Greek power supply sector integrating mainland and insular electric systems

The energy planning of power sector constitutes a multifaceted challenge for policy makers, incorporating a variety of economic, technological, environmental, political and social aspects in order to ensure the unhindered equilibrium between electricity demand and electricity supply. This paper presents a deterministic bottom-up Mixed Integer Linear Programming model for the long-term energy planning of national power supply systems, having special focus and modeling effort on the peculiar case of Greece. It is a least cost optimization based model being expanded and enhanced with the integration of electric interconnections and the evident participation of environmental dimension. Its superstructure consists of multiple mathematical expressions representing power demand patterns, technical constraints, operation rules, penetration potential of energy sources, economic aspects, technological availability, environmental obligations and other sectoral targets and commitments applying in the electricity supply field. Its main contribution lies on the holistic methodological approach adopted, concerning the discrete electric systems of mainland and insular areas in Greece by proposing a novel way of simulating the potentiality of their submarine interconnection. The present model is applied on a real case study concerning the Greek electricity planning problem for the period 2014–2024, through the elaboration of two alternative evolution scenarios. The underlying objective is multifarious: (a) to deliver the portfolio of new capacity investments, the fuel mix trend, the penetration of renewable energy sources and the progress of achieving country׳s commitments and targets, and (b) to investigate and highlight the potential economic, energy and environmental benefits arising from the electrical interconnection of Greek islands to the main continental power system.