Harmony search optimization of renewable energy charging with energy storage system

We propose an efficient harmony search algorithm for charge scheduling of an energy storage system (ESS) with renewable power generators under time-of-use pricing and demand charge policy. We show the superiority of the proposed method by simulating experiments with load and generation profiles of typical residential customers. ESS scheduled by the proposed harmony search algorithm showed improved result over the system optimized using genetic algorithm.     

Multi-objective optimal charging of plug-in electric vehicles in unbalanced distribution networks

Plug-in electric vehicles (PEVs) as new generations of transportation systems have recently become a promising solution to mitigate emissions of greenhouse gases produced by petroleum-based vehicles. Existing power systems may face serious reliability and power quality problems in supplying emerging PEV charging loads unless the charging task is coordinated. In addition, in real world applications, most PEVs are single-phase loads supposed to be charged from residential or commercial outlets. In this paper, a multi-objective optimization framework is proposed to optimally coordinate the charging of single-phase PEVs with dynamic behavior in unbalanced three-phase distribution systems employing smart grid facilities. Objective functions include total cost of purchasing energy in a multi-tariff pricing environment as well as grid total energy losses over charging span. The objective functions are optimized subject to network security, power quality, and PEV constraints. Fuzzy memberships are used to transform differently-scaled objective functions into a same range in order to ensure the Pareto optimality of the multi-objective solution. The proposed method is tested on an unbalanced three-phase distribution system and obtained results, which are discussed in detail, confirm its efficiency in getting a solution satisfying both objective functions as well as in the speed.     

Peer-to-peer (P2P) electricity trading in distribution systems of the future

Recent years distribution systems have been witnessed a rapid interconnection of distributed energy resources (DER), solar energy generation and electric vehicles (EV) in particular. To this end, residential and commercial electricity customers equipped with DERs are transforming their roles from pure electricity consumers to prosumers that can switch between electricity consumers and producers. Indeed, if properly managed, DERs of prosumers could bring significant benefits to distribution system operations. Peer-to-peer (P2P) electricity trading in distribution systems has been recently explored, in order to properly manage existing prosumers and to continually promote a deeper penetration of prosumers. This article discusses two types of P2P mechanisms, namely auction-based and bilateral contract-based P2P electricity trading mechanisms, and analyze their effectiveness in properly managing electricity trading among prosumers in distribution systems of the future.     

考虑阶梯式碳交易机制与电制氢的综合能源系统热电优化

"双碳"背景下,为提高能源利用率,优化设备的运行灵活性,进一步降低综合能源系统(IES)的碳排放水平,提出一种IES低碳经济运行策略.首先考虑IES参与到碳交易市场,引入阶梯式碳交易机制引导IES控制碳排放;接着细化电转气(P2G)的两阶段运行过程,引入电解槽、甲烷反应器、氢燃料电池(HFC)替换传统的P2G,研究氢能...     

含碳-绿色证书联合交易机制的综合能源系统日前优化调度

随着能源互联和低碳电力的持续推进,综合能源系统(IES)将成为节能减排的重要载体.结合碳排放权交易(CET)和绿色证书交易(GCT)机制,提出含碳-绿色证书联合交易机制的IES优化运行模型.在分析CET和GCT机制的基础上,搭建碳-绿色证书联合交易市场框架,打破传统碳和绿色证书市场交易的壁垒;综合考虑IES的购电成本、...     

Data-driven next-generation smart grid towards sustainable energy evolution: techniques and technology review

Meteorological changes urge engineering communities to look for sustainable and clean energy technologies to keep the environment safe by reducing CO2 emissions. The structure of these technologies relies on the deep integration of advanced data-driven techniques which can ensure efcient energy generation, transmission, and distribution. After conducting thorough research for more than a decade, the concept of the smart grid (SG) has emerged, and its practice around the world paves the ways for efcient use of reliable energy technology. However, many developing features evoke keen interest and their improvements can be regarded as the next-generation smart grid (NGSG). Also, to deal with the non-linearity and uncertainty, the emergence of data-driven NGSG technology can become a great initiative to reduce the diverse impact of non-linearity. This paper exhibits the conceptual framework of NGSG by enabling some intelligent technical features to ensure its reliable operation, including intelligent control, agent-based energy conversion, edge computing for energy management, internet of things (IoT) enabled inverter, agent-oriented demand side management, etc. Also, a study on the development of data-driven NGSG is discussed to facilitate the use of emerging data-driven techniques (DDTs) for the sustainable operation of the SG. The prospects of DDTs in the NGSG and their adaptation challenges in real-time are also explored in this paper from various points of view including engineering, technology, et al. Finally, the trends of DDTs towards securing sustainable and clean energy evolution from the NGSG technology in order to keep the environment safe is also studied, while some major future issues are highlighted. This paper can ofer extended support for engineers and researchers in the context of data-driven technology and the SG.     

面向电能交易的用户级直流微网母线电压分层控制策略研究

传统用户级直流微网运行策略无法满足微网用户分布式电能交易需求,为此提出一种面向分布式电能交易的直流微网母线电压分层控制策略.该策略依据直流母线电压信号,将微网划分为6个运行区域.根据每一层区域的特点,将微网内分布式单元设置为特定的电压主控单元(控制直流母线电压设备对象)和能量单元(提供功率输出设备对象).分布式单元依据...     

面向含氢综合能源系统的电-碳-氢耦合交易市场研究综述

在我国“双碳”目标愿景下,电-碳-氢耦合交易市场正通过市场机制优化能源配置,加速能源转型,但含氢综合能源系统的兴盛给多能耦合交易市场的发展带来了新的挑战。介绍了含氢综合能源系统的基本结构,并在电-碳、电-氢交易市场研究的基础上分析了电-碳-氢耦合交易机制,深入探究了面向含氢综合能源系统的电-碳-氢耦合交易市场机制。分别从市场的交易标的物、交易对象、交易价格角度进行了阐述,并归纳分析了目前实现市场均衡的能源定价策略与市场出清机制。最后总结了电-碳-氢交易市场与含氢综合能源系统发展面临的挑战,并对后续的研究方向进行了展望。     

计及氢能多元利用和绿证-碳联合交易的综合能源系统优化运行

为充分利用综合能源系统的多能耦合特性和高比例新能源的特点,提出一种计及氢能精细化多元利用和绿证-碳联合交易的综合能源系统低碳经济优化调度策略。针对氢能的低碳清洁特性,建立含电解制氢、氢转电热、氢制甲烷以及热电掺氢的氢能多元利用模型,并考虑氢能利用过程中产生的余热,在氢能多元利用模型中引入热回收装置,提出氢能精细化多元利用结构;为提升新能源消纳能力以及降低系统碳排放量,分别建立碳交易机制和绿证交易机制,并针对两者之间的关联性提出绿证-碳联合交易机制;兼顾综合能源系统的经济性和环保性,建立以绿证交易成本、购能成本、碳交易成本、运行维护成本和弃风成本之和最低为目标的综合能源系统低碳经济调度模型。算例结果表明,所提模型能够提高新能源消纳能力,显著降低碳排放量,实现了能源的高效利用和综合能源系统的低碳经济运行。     

Machine learning for power system protection and control

Since the power system is undergoing a transition into a more flexible and complex system, it urges improvements in fault diagnosis techniques for the power system protection to avoid cascading damages at the occurrence of faults. Facing with challenges of massive data, several machine-learning based methods for identifying faults were proposed over the past years. In this paper, an overview of conventional and trending machine learning applications for the fault diagnosis are summarized.     

应用机器学习对超晶格信号随机性的研究和评估

本研究由对超晶格随机数发生器的信号随机性检测为出发点展开。通过使用人工智能方法对发生器产生的随机信号进行检测和评估。针对这种新随机信号采用了几种常见的机器学习方法,来预处理一部分信号并试图训练聚类或网络模型,然后对随机数其他部分进行测试并判断随机性优劣。将此方法运用于比较正态分布随机数与超晶格发生器随机数,结论为超晶格随机数具有更好更明显的随机性,且各类机器学习方法在随机数性能检验中有价值,可以展望使用机器学习方法研究随机数及其相关的密码安全性的可能前景。     

Multiobjective electric distribution system expansion planning using hybrid energy hub concept

This paper presents a novel approach for optimal electric distribution system expansion planning (OEDSEP) using a hybrid energy hub concept. The proposed method uses an energy hub model to explore the impacts of energy carrier systems on OEDSEP procedure. This algorithm decomposes the OEDSEP problem into three subproblems to achieve an optimal expansion planning of a system in which the investment and operational costs are minimized, while the reliability of the system is maximized. The algorithm was successfully tested in the present research for an urban distribution system.     

智能电网框架下电动汽车智能充电系统设计研究

近年来,电动汽车和插电式电动汽车（Plug-in electric vehicles, PEVs）的销量稳步增长,充电桩数量急剧增加,这一现象可能会给电网和当地配电电路和变压器造成负担,而且可能会导致电力公司的成本增加。文中介绍了智能电网系统的设计和实现逻辑,使电动汽车、PEV与电网之间能够实现动态交互。这种智能和动态的交互能够减轻电网负荷,从而最大限度地减少成本,避免负载过大造成的损害。本文以开发算法为重点,提出了完整的系统设计,该系统充电速度快、效率高,可以成功地用于减轻电网的负担。     

Deployment of cybersecurity for managing traffic efficiency and safety in smart cities

Boosting the concept of smart cities for implementing an intelligent management of traffic congestion while reducing cybersecurity concerns will not only be more efficient for reducing traffic congestion but also more resilient to cyber incidents. In this paper we proposed a framework that can act as a generalized firewall and work interactively with several critical infrastructures in a smart city to protect the respective operations from a variety of cyber threats. The objective is to develop several steps for a comprehensive traffic management framework in smart cities that facilitates the cooperation among drivers and between drivers and the traffic management authority. The transformative nature of the proposed study supports its applications to a variety of networked critical infrastructures, including electricity, gas, water, rails, and telecommunications, as they intend to respond effectively to a wide range of weather- or human-related disruptions. The contributions of this paper include: Improving the traffic management performance in urban transportation systems, assessing and mitigating the cybersecurity risk in urban traffic management, and facilitating efficient and cyber-secure traffic management in metropolitan areas; Developing and testing an interactive simulation platform for evaluating the traffic management performance under various traffic conditions; Validating and demonstrating the applications in a practical urban transportation system; Disseminating the proposed study results to a wide range of concerned audiences via user-group meetings, detailed education forums, and a close collaboration with the local traffic management authority.     

An innovative approach for solving the restoration problem in distribution networks

An effective heuristic graph-based approach is proposed in this paper for solving the service restoration problem in distribution networks. Minimisation of the de-energised consumers’ load and reduction of the number of switching operations were considered in this service restoration application. A suitable assignment of the weighting coefficient to all branches in a de-energised area was used to decrease the number of switching operations. Prim's algorithm for finding of the minimum spanning tree logic was used to realise this approach. Other applications necessary for the optimal performance of the service restoration application were also developed and tested in this study (e.g., load flow, load reallocation of overloaded network elements, generation of the sequence of switch actions, etc.).     

分布式电能管理系统在电厂中的应用

湛江发电厂为了提高厂用电系统电气控制的安全性和可靠性．应用高可靠性的微机处理装置和通信技术代替人工监测,为3号机组加装了电能管理系统(IMPACC)．实现了对厂用电母线和重要电动机运行情况的实时监测。IMPACC系统采用分层分布式结构．由集中控制单元和现场控制单元两部分组成,采用该系统可减少不必要的停机维护时间,有效地提高工作效率。该系统于2003年5月投入使用后,运行正常,维护方便,基本实现了设计的功能。     

A review of machine learning applications in IoT-integrated modern power systems

This paper aims to provide a systematic and comprehensive survey of state-of-the-art machine learning techniques and their potential applications in IoT-integrated power systems.     

基于云计算的异构能源系统能源管理方法

本文提出了一种基于云计算的能源管理方法,促进异构能源系统中可再生能源的整合。首先将能源供应商与能源产消者组成虚拟能源提供商,直接参与异构能源系统交易。其次建立云计算模型,用于系统内能源交易。然后考虑最小化客户能源使用成本和最大化能源供应商收益建立线性规划模型,促进可再生能源整合。在不同用户数量、可再生能源比例、储能结构的场景中对所提出的方法进行了测试,并与传统管理方法进行了比较。仿真结果表明,与MT方法相比,所提的方法可降低30%以上的系统成本,并且计算时间可满足实时能源管理服务。     

Distributed power flow loss minimization control for future grid

In this paper, a novel decentralized algorithm is proposed to minimize power flow loss in a large‐scale future grid connecting with many real‐time‐distributed generation systems by which power flows bi‐directionally. The DC‐power loss at each link is defined as the product of resistance and the square of current that can be considered as a quadratic flow cost. We employ the notion of tie‐sets that reduces the complexity of the power flow loss problem by dividing a power network into a set of loops that forms a linear vector space on which the power loss problem can be formulated as a convex optimization problem. As finding a solution in each tie‐set enables global optimization, we realize parallel computing within a system of independent tie‐sets by integrating autonomous agents. Simulation results demonstrate the minimization of the power loss on every link by iteratively optimized power flows and show the superiority against the traditional centralized optimization scheme. Copyright © 2014 John Wiley & Sons, Ltd.     

局域能源市场多产消者P2P交易框架设计

随着局域能源市场中分布式能源的大量接入和电力系统运行方式的逐渐转变,具有电能生产/消费行为的产消者得到了广泛关注与研究。在此背景下,为提高小规模能源在局域能源市场中的就地消纳能力,设计了一种面向局域能源市场中多产消者的点对点(P2P)日前市场交易框架。在局域能源市场建立了P2P市场交易平台,并对产消者的基本特征进行了归纳分析,提出了典型的产消者组合类型;在产消者层面,采用供给函数均衡模型对产消者竞价行为进行建模,确立了含多产消者的P2P交易平台参与局域能源市场交易;采用连续双边拍卖机制对产消者之间进行P2P匹配,并确定交易过程中的拍卖价格和交易价格。最后,通过算例验证了所提P2P交易框架的有效性。