电力物联网是保障电力系统安全可靠、经济高效运行的重要基础，也是支撑城市能源互联网的基础平台。为此，文章对面向城市能源互联网的电力物联网内涵、架构和关键技术进行了深入探讨和分析。首先，梳理和分析了城市能源互联网和电力物联网的区别，并指出了面向城市能源互联网的电力物联网内涵；其次，分别提出了面向城市能源互联网的电力物联网的体系架构、物理架构和系统架构；最后，结合现有的“云大物移”、电力光纤入户、“四网融合”和“三表集抄”等技术，从信息化和通信化2个角度阐述了面向城市能源互联网的电力物联网关键技术内容及其现存的不足，以期为未来城市能源互联网的发展和研究提供一定的借鉴。

The power internet of things （IOT） is the important foundation to ensure the safe， reliable， economical and efficient operation of the power system， and also a basic platform to support the urban energy internet. In this paper it makes a deep discussion and analysis on the content， frameworks and key technologies of the power internet of things for urban energy internet. Firstly， the differences between the urban energy internet and the power internet of things are sorted out and analyzed， and the content of the power internet of things oriented to the urban energy internet is proposed and the framework， physical framework and system framework of power internet of things for urban energy internet are proposed. Finally， combined with cloud computing technology， big data， internet of things， mobile internet， power fiber to the home， four-network convergence of telecommunication network， internet， broadcast network and power grid， and three-meter collection of water， electricity and gas， this paper elaborates the content and existing shortcomings of the key technologies of the power IOT for urban energy internet from the perspectives of information and communication， wishing to provide some reference for the future development and research of urban energy internet.

 摘  要：以往对于冷/热/电联供(combined cooling heating and power, CCHP)系统的研究主要集中在其运行优化上，较少对系统中分布式电源(distributed generation, DG)的选址定容问题进行研究，更少有文献将基于价格与基于激励的需求响应(demand response, DR)综合考虑在系统中。该文利用CCHP系统的多能源互补特性，综合考虑基于价格与基于激励的需求响应，以分布式电源接入节点与接入容量为变量，提出了计及需求响应的分布式电源选址定容模型。首先，建立了CCHP系统热电耦合运行模型。其次，综合考虑负荷削减量、中断持续时间与中断时间因子等因素，提出了可中断负荷的单位电量补偿定价的方法。通过在目标函数中分析需求响应成本，使规划目标更为全面，从而节约投资。另外，综合基于激励与基于价格的需求响应作用，考虑用户对于电价、燃气价格、可中断负荷单位电量补偿定价的响应，定义了改进的价格弹性系数，并利用此系数对负荷预测进行修正。最后，通过基于邻域再搜索的改进粒子群算法(neighborhood re-dispatch particle swarm optimization，NR-PSO)对规划模型进行求解，并通过对某13节点综合园区系统的仿真分析，验证了所提模型及方法的有效性。 

&nbsp;ABSTRACT： The traditional combined cooling heating and power &nbsp;(CCHP) system researches mainly focus on its operation optimization, and lesson the siting and sizing of distributed generation (DG) in the system. The demand response (DR) based on price and incentive is not taken into account in the process. Based on the multi-energy complementary characteristics of CCHP system, this paper puts forward the siting and sizing model of distributed power with considering price and incentive based DR, which takes distributed power access nodes and access capacity as variables. Firstly, we establish the thermo-electric coupling operation model for CCHP system. Secondly, we propose the pricing method of unit power compensation with interruptible load, comprehensively considering load reduction, interruption duration and interrupt time factor. Then, by analyzing the DR cost in the objective function, the planning goal is more comprehensive and the investment is saved. In addition, based on the consideration of incentive and price-based DR, an improved price elasticity coefficient is defined with considering the influence of electric price, gas price and the compensating price of unit power with interruptible load, which is used to correct the load forecast. At last, the planning model is solved by the neighborhood re-dispatch particle swarm optimization algorithm (NR-PSO). And through the simulation analysis of a 13-node integrated park system, the validity of the proposed model and method is verified.<div>&nbsp;</div>

近年来随着天然气发电比重的不断增加和电转气（power to gas，P2G）技术的逐步成熟，电力系统和天然气系统的耦合程度随之加深，只针对电力系统的规划方法已经不能满足电-气混联综合能源系统的规划和运行需求。在此背景下，考虑热电联产（combined heat and power，CHP）机组和电转气装置，对电-气混联综合能源系统的协同规划问题做了些初步研究。首先，引入能源中心概念，其中能源载体可从某种形式转换成其他形式，如热电联产机组，并对能源中心进行建模。在此基础上，构建了包含能源中心和电转气装置等的综合能源系统的非线性模型并进行线性化处理。之后，以电-气混联综合能源系统的投资成本、运行成本以及表征可靠性的能量短缺成本之和最小为规划目标，采用基于通用代数建模系统（general algebraic modeling system，GAMS）平台的CPLEX求解器对常规发电机组、热电联产机组、电转气厂站、燃气锅炉、输电线路和天然气管道的选址定容问题进行优化，并对规划方案的可靠性以及电转气厂站消纳间歇性可再生能源的效益进行评估。最后，用综合能源模拟系统对所提出的方法做了说明。

The increasing penetration of natural gas power generation and ever-developing power to gas （P2G） technology in recent years have promoted the coupling between the power system and the natural gas system than ever before. This coupling has introduced new challenges to the planning of integrated electricity and natural gas energy systems, as the existing power system planning models normally overlook the impacts of natural gas or other energy systems. Given this background, this paper studies the collaborative planning of integrated energy systems with combined heat and power （CHP） plants and P2G stations. First, the energy center concept is introduced and modeled, and in an energy center various kinds of energy conversion such as CHP can be carried out. A nonlinear model for an integrated energy system with multiple interconnected energy centers and P2G stations is next presented and linearized. Then, this paper takes the minimum overall cost as planning objectives including investment cost, operation cost and energy shortage cost characterizing the reliability of integrated energy systems, optimizes the location sizing problems of traditional generating units, CHP plants, P2G stations, gas-fired boilers, transmission lines and natural gas pipelines with using general algebraic modeling system（GAMS） -based CPLEX solver, and evaluates the reliability of the planning scheme and the benefit generated by P2G stations in promoting the capability of accommodating intermittent renewable energy. Finally, the effectiveness of the proposed collaborative planning model is demonstrated by a sample integrated energy system.

面向越来越开放的能源交易市场,为充分调动用户侧资源,提出了一种考虑需求响应(demand response, DR)的电/热/气云储能(cloud energy storage,CES)优化配置策略。建立含电/热/气云储能能源集线器(energy hub, EH)结构,从参与云储能商业模式的用户侧与云储能提供商出发,构建两主体双层优化模型。底层基于长短期记忆和贝叶斯神经网络的概率预测方法,刻画新能源出力的不确定性,建立考虑需求响应的用户侧云储能充放能模型,以用户总成本最小为目标优化决策用户侧充放能行为,并将决策信息传递到云储能提供商。顶层以云储能提供商的总成本最小为目标,集中优化决策实体储能功率和容量的配置问题。通过大M法对目标以及约束中的非线性部分进行松弛线性化,将其转化为混合整数线性规划模型。最后,建立4个典型应用场景,通过Matlab中的YALMIP工具箱调用CPLEX优化求解器对不同场景下的模型进行求解,联合对比在4种不同场景下的整体成本与收益,验证该策略在资源共享、节约系统整体成本等方面的优越性。

In order to fully mobilize user-side resources in an increasingly open energy trading market, this paper proposes an optimal allocation strategy for electricity-heat-gas cloud energy storage (CES) considering demand response (DR). The proposed optimized configuration establishes an energy hub (EH) structure with electricity-heat-gas cloud energy storage, and a two-subject two-layer optimized model from the view of users and providers participating in the CES business model is established. The lower layer describes the uncertainty of new energy output according to the probability prediction method based on long-term and short-term memory and Bayesian neural network; a user-side CES charging and discharging model considering demand response, which is optimized aiming to minimize the user’s total cost, is established; and the decision information will be informed to the CES provider. The upper layer, aimed to minimize the investment and construction cost of CES providers, concentrates on optimizing the allocation of energy storage power and capacity of decision-making entities. The big M method is adopted to relax and linearize the nonlinear part of the objective and constraints, and then it is transformed into a mixed-integer linear optimization problem. Finally, four typical application scenarios are established. As to the verification of the superiority of the strategy, the CPLEX optimization solver is called through the YALMIP toolbox in Matlab to solve the models in different scenarios, and the overall costs and benefits are jointly compared.

As a key application of smart grid technologies, the smart distribution network (SDN) is expected to have a high diversity of equipment and complexity of operation patterns. Situational awareness (SA), which aims to provide a critical visibility of the SDN, will enable a significant assurance for stable SDN operations. However, the lack of systematic evaluation through the three stages of perception, comprehensive, and prediction may prevent the SA technique from effectively achieving the performance necessary to monitor and respond to events in SDN. To analyze the feasibility and effectiveness of the SA technique for the SDN, a comprehensive evaluation framework with specific performance indicators and systematic weighting methods is proposed in this paper. Besides, to implement the indicator framework while addressing the key issues of human expert scoring ambiguity and the lack of data in specific SDN areas, an improved interval-based analytic hierarchy process-based subjective weighting and a multi-objective programming method-based objective weighting are developed to evaluate the SDN SA performance. In addition, a case study in a real distribution network of Tianjin, China is conducted whose outcomes verify the practicality and effectiveness of the proposed SA technique for SDN operating security.