Review of demand-side energy sharing and collective self-consumption schemes in future power systems

The widespread use of distributed energy sources provides exciting potential for demand-side energy sharing and collective self-consumption schemes.Demand-side energy sharing and collective self-consumption systems are committed to coordinating the operation of distributed generation,energy storage,and load demand.Recently,with the development of Internet technology,sharing economy is rapidly penetrating various fields.The application of sharing economy in the energy sector enables more and more end-users to participate in energy transactions.However,the deployment of energy sharing technologies poses many challenges.This paper comprehensively reviews recent developments in demand-side energy sharing and collective self-consumption schemes.The definition and classification of sharing economy are presented,with a focus on the applications in the energy sector:virtual power plants,peer-to-peer energy trading,shared energy storage,and microgrid energy sharing cloud.Challenges and future research directions are thoroughly discussed.

我国构建DSM保障体系的对策研究

分析了需求侧管理(Demand Side Management,DSM)保障体系的主要内涵,研究了国外典型国家在DSM保障体系方面的先进经验,并结合我国DSM实施过程中存在的具体问题,探讨了我国构建完善的需求侧管理保障体系的对策,对我国DSM长效机制的建立具有非常重要的现实意义。

HVAC energy cost minimization in smart grids: A cloud-based demand side management approach with game theory optimization and deep learning

In this paper, we present a novel cloud-based demand side management (DSM) optimization approach for the cost reduction of energy usage in heating, ventilation and air conditioning (HVAC) systems in residential homes at the district level. The proposed approach achieves optimization through scheduling of HVAC energy usage within permissible bounds set by house users. House smart home energy management (SHEM) devices are connected to the utility/aggregator via a dedicated communication network that is used to enable DSM. Each house SHEM can predict its own HVAC energy usage for the next 24 h using minimalistic deep learning (DL) prediction models. These predictions are communicated to the aggregator, which will then do day ahead optimizations using the proposed game theory (GT) algorithm. The GT model captures the interaction between aggregator and customers and identifies a solution to the GT problem that translates into HVAC energy peak shifting and peak reduction achieved by rescheduling HVAC energy usage. The found solution is communicated by the aggregator to houses SHEM devices in the form of offers via DSM signals. If customers’ SHEM devices accept the offer, then energy cost reduction will be achieved. To validate the proposed algorithm, we conduct extensive simulations with a custom simulation tool based on GridLab-D tool, which is integrated with DL prediction models and optimization libraries. Results show that HVAC energy cost can be reduced by up to 36% while indirectly also reducing the peak-to-average (PAR) and the aggregated net load by up to 9.97%.

IRP/DSM and Sustainable Development

This paper introduces the energy consumption status in China, elaborate the affects of the unreasonable energy consumption structure on energy environment and sustainable development of economy. Simultaneously, it points out the solution, i.e., to implement integrated resources planning (IRP)/demand side management (DSM), and gives some recommendations on the way of implementing IRP/DSM.

Smart Grids with Intelligent Periphery:An Architecture for the Energy Internet

A future smart grid must fulfill the vision of the Energy Internet in which millions of people produce their own energy from renewables in their homes, offices, and factories and share it with each other. Electric vehicles and local energy storage will be widely deployed. Internet technology will be utilized to transform the power grid into an energysharing inter-grid. To prepare for the future, a smart grid with intelligent periphery, or smart GRIP, is proposed. The building blocks of GRIP architecture are called clusters and include an energy-management system （EMS）-controlled transmission grid in the core and distribution grids, micro-grids, and smart buildings and homes on the periphery; all of which are hierarchically structured. The layered architecture of GRIP allows a seamless transition from the present to the future and plug-and-play interoperability. The basic functions of a cluster consist of （1） dispatch, （2） smoothing, and （3） mitigation. A risk-limiting dispatch methodology is presented; a new device, called the electric spring, is developed for smoothing out fluctuations in periphery clusters; and means to mitigate failures are discussed.

Evolving practice of demand-side management

The concept of demand-side management(DSM)was invented in the late 1970s along with the development of many of the frameworks in use to plan and implement it in the years immediately following. It was originally referred to as demand-side load management. It is generally defined as the planning and implementation of those activities designed to influence consumer use of electricity in ways that will result in changes in the utility’s load shape—i.e., changes in the time pattern and magnitude of a utility’s load. This paper describes the evolution it has undergone since its invention and some likely changes ahead. DSM largely originated in the U.S., but is practiced in various forms through the world today. This paper uses U.S. data as examples.

DSM演进历史的评析

DSM是一种广泛推行的能效管理技术和节能运作机制,自20世纪70年代开始至今,经历了20多年的实践在日趋完善,它主要应用在终端节电领域。DSM作为在市场经济体制基础上培植起来的一种能效管理和节能运作机制,要随市场经济体制的不断演进做相应的调整。DSM能够在政府法规和政策支持下,采取有效的激励和诱导措施,通过社会各方共同协力,达到节约能源和保护环境、实现能源与经济和环境协调发展的目的。从总体上看,我国的DSM还处于起步阶段,为把它纳入管理和运作轨道,还需要在借鉴国际经验的基础上探索适合自己的有效途径。

需求侧管理(DSM)在炼化企业节能管理中的应用

需求侧管理是国际上广泛应用的一种先进管理技术,可以激发各用能单位主动采用各种有效节能方法,实现减少投资与节约能源的双重目的。镇海炼化通过各级用能单位主动提出多项节能措施,合计停运机泵、空压机11台,节电988×104kW.h/a;优化蒸汽约14 t/h,节约燃料约1 000 t/a。能源需求侧管理是一种先进的用能管理方法,具有广泛的推广与应用价值。

Smart residential energy management system for demand response in buildings with energy storage devices

In the present scenario,the utilities are focusing on smart grid technologies to achieve reliable and profitable grid operation.Demand side management(DSM)is one of such smart grid technologies which motivate end users to actively participate in the electricity market by providing incentives.Consumers are expected to respond(demand response(DR))in various ways to attain these benefits.Nowadays,residential consumers are interested in energy storage devices such as battery to reduce power consumption from the utility during peak intervals.In this paper,the use of a smart residential energy management system(SREMS)is demonstrated at the consumer premises to reduce the total electricity bill by optimally time scheduling the operation of household appliances.Further,the SREMS effectively utilizes the battery by scheduling the mode of operation of the battery(charging/floating/discharging)and the amount of power exchange from the battery while considering the variations in consumer demand and utility parameters such as electricity price and consumer consumption limit(CCL).The SREMS framework is implemented in Matlab and the case study results show significant yields for the end user.

Game-theoretic energy management with storage capacity optimization in smart grids

With the development of smart grids, a renewable energy generation system has been introduced into a smart house. The generation system usually supplies a storage system with the capability to store the produced energy for satisfying a user's future demand. In this paper,the main objective is to determine the best strategies of energy consumption and optimal storage capacities for residential users, which are both closely related to the energy cost of the users. Energy management with storage capacity optimization is studied by considering the cost of renewable energy generation, depreciation cost of storage and bidirectional energy trading. To minimize the cost to residential users, the non-cooperative game-theoretic method is employed to formulate the model that combines energy consumption and storage capacity optimization.The distributed algorithm is presented to understand the Nash equilibrium which can guarantee Pareto optimality in terms of minimizing the energy cost. Simulation results show that the proposed game approach can significantly benefit residential users. Furthermore, it also contributes toreducing the peak-to-average ratio(PAR) of overall energy demand.

新型电力需求侧管理终端的研制

根据国家电网公司对电力能源的节约化和精益化管理要求,实现配变台区的自动采集。研制了一种集电能计量、负荷管理、公变监测、无功补偿为一体的新型电力需求侧管理终端,介绍了其总体设计思想、模块化的硬件设计、分层面向对象的软件设计,最后给出了典型应用方案。

提高我国电力产业能效的系统规划方法研究

电力产业作为国民经济的基础产业和社会公用事业,其不仅生产能源同时也在耗费着大量一次能源。由于电力生产耗费一次能源的比重最高,提高电力能效自然成为节约能源的重要手段。本文从系统规划的角度出发,研究了提高电力能效的各种方法,包括电源结构优化、电力与经济协调规划、电源与电网协调规划、电价规划、电力节能规划等。

智能电网——未来电网的发展态势

智能电网已成为近年来国内外有关未来电网发展趋势的热门话题。文章简述和分析了智能电网研究开发背景情况,智能电网的概念、特性和发展智能电网的驱动力,智能电网包含的主要技术,我国智能电网技术研究取得的部分进展以及目前国外智能电网技术研究的新动向。对于如何发展我国智能电网,作者提出了自己的看法。

基于分时电价的住宅能量管理算法

随着混合式电动汽车(PHEV)的出现,关于PHEV向电网方向供电(V2G)技术的研究也逐渐增加。针对包含PHEV的家居微型电网,提出一种改进的能量管理算法。该算法基于分时电价对家用电器及PHEV的运行方式和时间进行调度,结合PHEV及用户参数,利用V2G技术有效实现了移峰填谷并降低家庭用电费用。同时还提出一种最优算法,以衡量改进算法的性能。仿真结果表明,改进算法可使用户的用电费用及峰均比分别降低约22%和70%,性能接近最优算法,并且可以实时处理用电请求,具有较强的实用性。

基于能耗实时监测的电力需求侧管理

近年来我国能耗监测管理得到了不同程度的改善,但在管理理念、制度安排、技术创新、资金支持等方面还存在着较多问题。利用信息技术,建立能耗在线实时监测管理体系,将成为未来能耗监测的发展目标。我国需要在计量设备基础管理、监测机构设置和人员培训、利益相关者关系协调等方面进行不断创新,才能适应能耗监测发展目标。

大企业用电的管理

连续高温天气 ,致使用电负荷连创历史新高。如何有效地使用电力 ,提升电能的效率才是让企事业单位电力产生功效的唯一准则 。

云浮地区建材行业配电变压器节能和经济运行

配电变压器的节能与经济运行是电力需求侧管理中的一项重要内容。根据云浮市基本用电情况,对配电变压器的技术经济评价、经济容量选择和经济运行等方面进行了分析和研究。配电变压器的节能和经济运行对节能减排、改善电网电能质量具有重要意义。

EMS数据流管理系统的框架设计

针对现有关系型数据库系统在能量管理系统(EMS)实时应用中存在的缺陷,设计了一个新型EMS数据流管理系统的框架,并建立了相对应的数据流模型。该框架能够根据流速不同对采集数据进行分类处理,通过数据流查询窗口对相量测量单元(PMU)高速数据进行分割、降速、筛选,实现了对PMU数据和原有监控与数据采集(SCADA)系统测量值的并行实时处理,并且能够在实现稳态计算功能的同时对系统进行动态监测。文中描述了系统的基本结构、各组成部分的功能和关键技术,并在数据流处理方面提出了一些提高效率的改进措施。

智能建筑电力需求侧能源管理

介绍了电力需求侧管理技术。在智能建筑基础上引入需求响应机制,建立了一个基于建筑侧需求响应的能源管理平台。该平台可使用户就地或远程地对分布于智能建筑内的不同功能的智能化子系统进行能耗跟踪及节能控制,以提高建筑能源利用效率,实现供需资源的协同、优化、整合。

Long-term forecasting of annual peak load considering effects of demand-side programs

The main purpose of this research paper is to investigate the long-term effects of the proposed demandside program,and its impact on annual peak load forecasting important for strategic network planning.The program comprises a particular set of demand-side measures aimed at reducing the annual peak load.The paper also presents the program simulations for the case study of the Electricity Distribution Company of Belgrade(EDB).According to the methodology used,the first step is to determine the available controllable load of the distribution utility/area under consideration.The controllable load is presumed constant over the analyzed time horizon,and the smart grid(SG)infrastructure available.The saturation of positive effects during intense program application is also taken into account.Technical and economic input data are taken from the real projects.The conducted calculations indicate that demand-side programs can bring about the same results as the energy storage in the grids with a strong impact of distributed generation from variable renewable sources(V-RES).In conclusion,the proposed demand-side program is a good alternative to building new power facilities,which can postpone investment costs for a considerable period of time.