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.     

An overview of the Portuguese wind power sector

The present situation of electricity production from renewable energy sources (RES) in Portugal is analyzed, giving particular attention to the wind power sector due to its increasing importance. The evolution of the electricity system is presented along with the strategies for the sector, and future prospects for the RES. Although the interest of private companies in the wind sector is high, the administrative and grid barriers represent major obstacles to wind power development. The problem of wind intermittency and uncertainty is also discussed. The improvement of interconnection capacity and the increase of power reserve are identified as key requirements for ensuring the security of supply. A clear understanding of all these aspects is fundamental for integrated, multidimensional wind power planning.     

风洞动力资源系统集成化保障研究

风洞试验任务的有效遂行依赖于水、电、气等动力资源的保障;为提高风洞动力资源系统的管理水平和维修保障效能,以第五代IETM集成思想为基础,研究提出基于IETM/PMA的一体化风洞动力资源综合保障方案,并就系统实现涉及的系统功能架构设计、数据顶层规划、数据模块需求列表快速生成、综合故障诊断实现、3D虚拟手册研发等关键技术问题进行了深入研究;应用表明:该系统在提供传统“交互式数字专家”功能的基础上,初步实现了IETM数据与装备履历、维修信息、库管信息的联通和各项业务的联动,能够有效提高风洞动力资源综合保障能力。     

基于差分进化算法的分布式电源DG规划设计

分布式电源(DG)是一种可以与环境兼容,利用清洁能源发电,可以满足用户对电量的特殊需求的发电装置。因此,将分布式电源接入电网,不仅可以保证电网的运行安全,提高供电可靠性,还可以将多余的电力反馈给电网。分布式发电接入配电网后,不一定能降低配电系统的网损,提高电网的稳定性,还有可能会因为并网的规划方案设计的不够好反而对电网造成不利影响,因此,分布式电源接入配电网的规划尤为重要。在分布式发电的并网规划中,最重要的是选择分布式发电的接入位置和容量。因此,本文选择具有结构简单、执行方便、优化效率高、参数设置简单、鲁棒性好等优点的差分算法,通过建立系统,并用Matlab进行了仿真,选择其最佳位置,计算出最优容量,并得到最优目标函数,来达到最佳的规划设计。     

基于DSP技术的电能质量在线监测仪

随着社会的发展,电能质量问题越来越受到社会的关注,而电能质量问题取决于供电方和用电方,为了切实维护电力部门和用户的合法利益,提高电网的电能质量水平,必须加强电网电能质量的监测和管理。论文介绍了基于TMS320F2812DSP芯片开发的电能质量在线监测仪,重点讨论了各模块电路的工作原理,以及实现方法。     

Uncertain network data envelopment analysis with undesirable outputs to evaluate the efficiency of electricity power production and distribution processes

In this paper, a customized network data envelopment analysis model is developed to evaluate the efficiency of electric power production and distribution processes. In the production phase, power plants consume fuels such as oil and gas to generate the electricity. In the distribution phase, regional electricity companies transmit and distribute the electricity to the customers in houses, industries, and agriculture. Although, the electricity is assumed to be a clean type of energy, several types of emissions and pollutions are produced during electricity generation. The generated emissions are considered as an undesirable output. A customized network data envelopment analysis (NDEA) approach is proposed to evaluate the efficiency of these processes Each decision making unit (DMU) includes two serially connected sub-DMUs, i.e., production and distribution stages. The models are extended using interval data to address the considerable uncertainty in the problem. The efficiency scores of main process, and each sub-process are determined. The final ranking of DMUs and sub-DMUs are achieved using a multi-attribute decision making (MADM) method. The whole approach is applied in a real case study in electrical power production and distribution network with 14 DMUs. The proposed approach has the following innovations in comparison with existing methods: (1) Both production and distribution process are evaluated in a unique model; (2) Undesirable outputs and uncertainty of data are considered in proposed approach; (3) Properties of proposed models are discussed through several theorems; (4) The efficiencies of production and distribution phases are determined distinctively; (5) A full ranking approach is proposed; (6) A real case study of electrical power production and distribution network is surveyed. The results of proposed approach are adequate and interesting. This approach can be customized for application in similar systems such as water production-supply management, Oil and fuel production–distribution systems, and supply chains.     

A Multiple Objective Linear Programming Approach to Power Generation Planning with Demand-Side Management (DSM)

The optimization of an economic indicator has traditionally been the sole objective function of mathematical programming models for power generation expansion planning. Recently, however, other evaluation aspects, such as environmental concerns, were also given an explicit role as objective functions in mathematical models. Models become thus more realistic so that decision makers are able to grasp the inherent conflicts and trade-offs among the distinct objectives in selecting a best compromise plan. A significant change in the planning processes has also occurred concerning new planning methodologies integrating demand-side management (DSM) techniques, in an attempt to change the levels and forms of electricity use by the consumers. This paper presents a multiple objective linear programming model for power generation expansion planning incorporating DSM. The objective functions are the total expansion cost, the environmental impact associated with the installed power capacity and the environmental impact associated with the energy output. DSM is included by modelling it as a new generating group along with the generating alternatives from the supply side. Five categories of constraints are considered related to the reliability of the supply system, the availability of the generating units, the capacity of the DSM-equivalent generating group, the total capacity installed throughout the planning period, the pollutant emissions. Some results are presented derived by using an interactive method, aimed at assisting decision makers in a progressive and selective search of good compromise solutions.     

移动应急电源变流器技术及其仿真研究

针对传统移动应急电源(EPS)大都依靠车载柴油发电机组提供电能,存在噪声大、效率低等局限性,提出了一种基于PWM变换技术的新型应急移动电源.在传统三相全控桥式变流器拓扑结构的基础上,增加电容、电感和接触器等简单器件,构成一种多功能变流器,使风能、太阳能等新能源能够应用于移动应急电源系统.Matlab仿真结果表明,系统输出电能质量较高,较传统EPS有更广泛的应用范围及更优越的性能,为新一代移动应急电源的开发提供了新的思路.     

基于电力大数据的用户用电感知研究

在基于电力大数据对用户提供多元化服务的研究中,发现电网在不同时刻停电,不同用户的停电感受不一样以及在调度计划制定时,由于不同线路所带用户不同需进行差异化服务。为此,提出基于电力大数据的用户用电感知研究。首先通过电网内部系统及外部系统进行数据采集,然后基于大数据从多维度进行数据处理和分析,建立了用电需求模型和用户用电感知模型并进行了深入应用;通过该模型可以实现有限投资供电可靠性提升最快,最大限度满足用户需求;可最大限度实现不同行业、类别的用户用电互补,提高设备利用率;可实现用电感知最低时段停电,停电涉及用户更精准。该模型的引用实现了电网规划、用户接入、调度运行的智能决策,使电网规划投资更精准,固定投资提升可靠性最快,提高设备利用效率和用户满意度。     

Optimization and control of a stand-alone hybrid solid oxide fuel cells/gas turbine system coupled with dry reforming of methane

This paper presents the hybrid solid oxide fuel cells (SOFC)/gas turbine (GT) system coupled with dry reforming of methane (DRM). The DRM is a syngas producer by consuming greenhouse gas. The stand-alone (off-the-grid) power system is developed by using a combination of a post-burner, recuperators and pressurized recycles in place of external energy supplies. To address the stand-alone operation and meet the complete combustion condition for the burner, the optimal operating conditions are initially determined by solving a constrained optimization algorithm for maximizing the hybrid power efficiency, and the dynamic control loops are implemented in a plantwide environment. In the proposed plantwide control strategy, the inventory control framework is added to regulate the plant component inventory, an air/fuel cross-limiting combustion control is added to ensure complete combustion and reduce heat loss, and the power and CO₂ emission control configuration is added to achieve the quality control performance. Finally, the simulation shows that the IMC-based multi-loop control scheme can efficiently regulate the total system power and control CO₂ emissions per kWh of electricity as well.     

System Dynamics Forecasting on Taiwan Power Supply Chain

This research aims to study the sustainability of Taiwan power supply chain based on system dynamics forecasting. The paper tries to investigate electricity shortage effects not only on the industrial side, but also from the standpoint of society. In our model, different forecasting methods such as linear regression, time series analysis, and gray forecasting are also considered to predict the parameters. Further tests such as the structure, dimension, historical fit, and sensitivity of the model are also conducted in this paper. Through analysis forecasting result, we believe that the demand for electricity in Taiwan will continue to increase to a certain level for a period of time in the future. This phenomenon is closely related to Taiwan’s economic development, especially industrial development. We also point out that electricity prices in Taiwan do not match with high industrial demand, and that prices are still slightly low. Finally, the future growth trend of Taiwan’s electricity demand has not changed, and ensuring adequate supply to meet electricity demand to prevent potential power shortages will pose some difficulty.     

电力市场环境下电源规划研究的软件设计与实现

本文主要是对电力市场条件下电源规划进行程序设计实现,以验证这种电源规划研究的科学性与正确性。该程序使用了分解协调措施,采用VC++6.0进行编写,经试验研究证明,该程序可用于验证电力市场环境下电网的电源规划研究的正确性与适用性,同时也能够为电力规划人员提供相对有效的依据。     

Expert or assistant: Supporting power engineers in the management of electricity distribution

A case study is presented of the development of computer-based support tools for power engineers in the electricity supply industry. The objective was to develop an expert system to support witching schedule production. A user-centred approach was followed which led the user community to conclude that a switching schedule production assistant (SSPA) was required which would leave control with the power engineer. Prototype systems were developed and evaluated in user trials which revealed that a significant and more general purpose tool would be a computer generated electricity network display that the engineers could manipulate. The paper concludes that the process of enabling users to evaluate alternative forms of technology can facilitate the development systems that are useful, acceptable and usable.     

基于并行分类算法的电力客户欠费预警

针对供电企业"先消费后付款"的经营模式可能造成用电客户因失信引发的欠费风险,需要在用电客户欠费行为发生之前实时快速地分析海量的用电用户的数据,给出潜在的欠费客户名单的问题,提出一种基于并行分类算法的电力客户欠费预警方法。首先,该方法使用基于Spark的随机森林(RF)分类算法对欠费用户进行建模;其次,根据用户以往历史用电行为和缴费记录使用时间序列进行预测得到其未来用电和缴费行为特征;最后,使用之前得到的模型对用户进行分类得到未来潜在高危险欠费用户。将该方法与并行化后的支持向量机(SVM)算法和在线序列极限学习机(OSELM)算法进行对比分析,实验结果表明,所提方法相对于对比算法在准确率上有较大提高,便于电费回收管理人员进行提前催缴,确保电费回收的及时性,有利于电力企业进行客户欠费风险管理。     

移动式无线数字水位监测站的设计与应用

采用检索式数字水位传感器专利技术,设计开发了一种移动式、数字化、智能型并太阳能供电、无线数据收发的水位监测站系统的技术方案。系统携带运输方便、即装即用,可广泛用于水库大坝、河道、水资源管理、汛情汛期快速布站设测点等水位监测场合。现场应用表明:系统运行可靠,功耗低,特别适用于偏远与无可靠供电条件地区的水位监测。     

Differential Mathematical Models to Investigate the Computer Network Architecture of an All-Mode System of Control over a Distance of Railways

The evolutionary development of railway power-supply systems and computer networks and technologies that control these systems are analyzed. It is shown that the optimization of electricity consumption is based on the intellectualization of electricity supply procedures. A graph is constructed whose topology adequately represents the typical architecture of a computer network of control at the layer of a distance of power supply of railways with a view to investigating the mutual integration of a power supply infrastructure and a computer network architecture of all-mode control. This article proposes a differential mathematical model for investigating the computer network architecture of an all-mode system of control over a distance of power supply and methods (in analytical form) for determining values of probabilities of states of system nodes, their capacities, and the number of failures of requests as the basis for the intellectualization of power supply procedures.     

基于高频整流模式新型EPS及工作原理分析

EPS作为一种可靠的绿色应急供电电源,在电梯、消防、应急照明等场合发挥重要作用.根据PWM整流器能量双向传输的特点,发展新型EPS应急电源在消防电源中的应用,其充电、放电都由PWM整流器完成.新型EPS应急电源优化传统EPS电源的结构和控制策略,提高消防电源的效率和管理信息化程度.对新型EPS应急电源的工作原理进行深入的分析,针对直接电流双环PID控制策略在MATLAB环境下进行仿真研究,并对仿真结果进行扼要的分析.     

Smart consumer load balancing: state of the art and an empirical evaluation in the Spanish electricity market

The basis of an efficient functioning of a power grid is an accurate balancing of the electricity demand of all the consumers at any instant with supply. Nowadays, this task involves only the grid operator and retail electricity providers. One of the facets of the Smart Grid vision is that consumers may have a more active role in the problem of balancing demand with supply. With the deployment of intelligent information and communication technologies in domestic environments, homes are becoming smarter and able to play a more active role in the management of energy. We use the term Smart Consumer Load Balancing to refer to algorithms that are run by energy management systems of homes in order to optimise the electricity consumption, to minimise costs and/or meet supply constraints. In this work, we analyse different approaches to Smart Consumer Load Balancing based on (distributed) artificial intelligence. We also put forward a new model of Smart Consumer Load Balancing, where consumers actively participate in the balancing of demand with supply by forming groups that agree on a joint demand profile to be contracted in the market with the mediation of an aggregator. We specify the business model as well as the optimisation model for load balancing, showing the economic benefits for the consumers in a realistic scenario based on the Spanish electricity market.     

Improving Electricity Planning – Use of a Multicriteria Decision Making Model

Electricity supply planners are now expected to consider a wide range of supply and demand options to meet future power needs. The evaluation is also expected to consider multiple objectives in such diverse areas as quality of supply, cost, environmental and social impacts. Further, there are a range of views on the appropriated weightings for those various considerations. Traditional methods for determining choices are no longer adequate. This paper outlines the development of a powerful tool to facilitate a multiobjective-driven electricity planning process. The multicriteria decision making model allows the evaluation of options against a wide range of criteria, grouped in a hierarchical structure. A formalism for comparing options is explored, showing that the model allows a planner to compare the range of alternatives against both a desired level of performance and a minimum acceptable level. The architecture of a computer-based decision support system is briefly described.