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Distributionally robust optimization of home energy management system based on receding horizon optimization

Jidong WANG, Boyu CHEN, Peng LI, Yanbo CHE

《能源前沿（英文）》 2020年第14卷第2期页码 254-266 doi: 10.1007/s11708-020-0665-4

摘要： This paper investigates the scheduling strategy of schedulable load in home energy management system (HEMS) under uncertain environment by proposing a distributionally robust optimization (DRO) method based on receding horizon optimization (RHO-DRO). First, the optimization model of HEMS, which contains uncertain variable outdoor temperature and hot water demand, is established and the scheduling problem is developed into a mixed integer linear programming (MILP) by using the DRO method based on the ambiguity sets of the probability distribution of uncertain variables. Combined with RHO, the MILP is solved in a rolling fashion using the latest update data related to uncertain variables. The simulation results demonstrate that the scheduling results are robust under uncertain environment while satisfying all operating constraints with little violation of user thermal comfort. Furthermore, compared with the robust optimization (RO) method, the RHO-DRO method proposed in this paper has a lower conservation and can save more electricity for users.

关键词： distributionally robust optimization (DRO) home energy management system (HEMS) receding horizon optimization (RHO) uncertainties

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基于解耦价值和策略强化学习的家庭能源管理方法

熊珞琳,唐漾,刘臣胜,毛帅,孟科,董朝阳,钱锋

《信息与电子工程前沿（英文）》 2023年第24卷第9期页码 1261-1272 doi: 10.1631/FITEE.2200667

摘要：由于电动汽车的普及性和家用电器的灵活性，在动态电价下对家庭能源系统进行能源调度优化电力成本和保障居民舒适度是可行的。本文提出一种基于数据驱动的深度强化学习家庭能源管理方法。首先，为揭示影响电动汽车充电行为的多种不确定因素，引入一种结合驾驶员经验、突发事件和交通状况的改进数学模型描述电动汽车在家庭能源系统中的动态能量需求。其次，提出一种解耦优势演员-评论家（DA2C）算法，通过缓解策略和价值共享网络导致的过拟合问题提升能源优化性能。此外，策略函数和价值函数的解耦网络确保了所提方法在不可见场景中的泛化性。最后，将所提方法与现有方法进行综合实验比较。结果表明，该方法能在不同场景下优化用电成本并兼顾居住舒适度。

关键词：家庭能源系统电动汽车强化学习泛化性

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Energy efficiency of small buildings with smart cooling system in the summer

Yazdan DANESHVAR, Majid SABZEHPARVAR, Seyed Amir Hossein HASHEMI

《能源前沿（英文）》 2022年第16卷第4期页码 651-660 doi: 10.1007/s11708-020-0699-7

摘要： In this paper, a novel cooling control strategy as part of the smart energy system that can balance thermal comfort against building energy consumption by using the sensing and machine programming technology was investigated. For this goal, a general form of a building was coupled by the smart cooling system (SCS) and the consumption of energy with thermal comfort cooling of persons simulated by using the EnergyPlus software and compared with similar buildings without SCS. At the beginning of the research, using the data from a survey in a randomly selected group of hundreds and by analyzing and verifying the results of the specific relationship between the different groups of people in the statistical society, the body mass index (BMI) and their thermal comfort temperature were obtained, and the sample building was modeled using the EnergyPlus software. The result show that if an intelligent ventilation system that can calculate the thermal comfort temperature was used in accordance with the BMI of persons, it can save up to 35% of the cooling load of the building yearly.

关键词： smart home heating and cooling systems saving energy optimal consumption of energy

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Energy storage resources management: Planning, operation, and business model

《工程管理前沿（英文）》页码 373-391 doi: 10.1007/s42524-022-0194-4

摘要： With the acceleration of supply-side renewable energy penetration rate and the increasingly diversified and complex demand-side loads, how to maintain the stable, reliable, and efficient operation of the power system has become a challenging issue requiring investigation. One of the feasible solutions is deploying the energy storage system (ESS) to integrate with the energy system to stabilize it. However, considering the costs and the input/output characteristics of ESS, both the initial configuration process and the actual operation process require efficient management. This study presents a comprehensive review of managing ESS from the perspectives of planning, operation, and business model. First of all, in terms of planning and configuration, it is investigated from capacity planning, location planning, as well as capacity and location combined planning. This process is generally the first step in deploying ESS. Then, it explores operation management of ESS from the perspectives of state assessment and operation optimization. The so-called state assessment refers to the assessment of three aspects: The state of charge (SOC), the state of health (SOH), and the remaining useful life (RUL). The operation optimization includes ESS operation strategy optimization and joint operation optimization. Finally, it discusses the business models of ESS. Traditional business models involve ancillary services and load transfer, while emerging business models include electric vehicle (EV) as energy storage and shared energy storage.

关键词： energy storage system energy storage resources management planning configuration operational management business model

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

S. L. ARUN, M. P. SELVAN

《能源前沿（英文）》 2019年第13卷第4期页码 715-730 doi: 10.1007/s11708-018-0538-2

摘要： 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 premise 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.

关键词： smart grid demand side management (DSM) demand response (DR) smart building smart appliances energy storage

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Energy transition management towards a low-carbon world

《工程管理前沿（英文）》 2022年第9卷第3期页码 499-503 doi: 10.1007/s42524-022-0201-9

关键词： energy transition low-carbon technology system modeling transition path emission reduction

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IoT sensor-based BIM system for smart safety barriers of hazardous energy in petrochemical construction

《工程管理前沿（英文）》 2022年第9卷第1期页码 1-15 doi: 10.1007/s42524-021-0160-6

摘要： The accidental release of hazardous energy is one of the causes of construction site accidents. This risk is considerably increased during petrochemical plant construction because the project itself is complex in terms of process, equipment, and environment. In addition, a general construction safety barrier hardly isolates and controls site hazardous energy effectively. Thus, this study proposes an Internet of Things (IoT) sensor-based building information modeling (BIM) system, which can be regarded as a new smart barrier design method for hazardous energy in petrochemical construction. In this system, BIM is used to support the identification of on-site hazardous energy, whereas IoT is used to collect the location of on-site personnel in real time. A hazardous energy isolation rule is defined to enable the system to generate a smart barrier on the web terminal window, thereby ensuring the safety of on-site person. This system has been applied to a large-scale construction project in Sinopec for one year and accumulated substantial practical data, which supported the idea about the application of sensor and BIM technology in construction. The related effects of the system on hazardous energy management are also presented in this work.

关键词： IoT BIM smart safety barrier hazardous energy management petrochemical construction

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Heterogeneous length-of-stay modeling of post-acute care residents in the nursing home with competing

《工程管理前沿（英文）》页码 577-591 doi: 10.1007/s42524-022-0203-7

摘要： Post-acute care (PAC) residents in nursing homes (NHs) are recently hospitalized patients with medically complex diagnoses, ranging from severe orthopedic injuries to cardiovascular diseases. A major role of NHs is to maximize restoration of PAC residents during their NH stays with desirable discharge outcomes, such as higher community discharge likelihood and lower re/hospitalization risk. Accurate prediction of the PAC residents’ length-of-stay (LOS) with multiple discharge dispositions (e.g., community discharge and re/hospitalization) will allow NH management groups to stratify NH residents based on their individualized risk in realizing personalized and resident-centered NH care delivery. Due to the highly heterogeneous health conditions of PAC residents and their multiple types of correlated discharge dispositions, developing an accurate prediction model becomes challenging. Existing predictive analytics methods, such as distribution-/regression-based methods and machine learning methods, either fail to incorporate varied individual characteristics comprehensively or ignore multiple discharge dispositions. In this work, a data-driven predictive analytics approach is considered to jointly predict the individualized re/hospitalization risk and community discharge likelihood over time in the presence of varied residents’ characteristics. A sampling algorithm is further developed to generate accurate predictive samples for a heterogeneous population of PAC residents in an NH and facilitate facility-level performance evaluation. A real case study using large-scale NH data is provided to demonstrate the superior prediction performance of the proposed work at individual and facility levels through comprehensive comparison with a large number of existing prediction methods as benchmarks. The developed analytics tools will allow NH management groups to identify the most at-risk residents by providing them with more proactive and focused care to improve resident outcomes.

关键词： nursing home predictive analytics individualized prediction competing risks health outcomes

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Distributed energy management for networked microgrids in a three-phase unbalanced distribution network

《能源前沿（英文）》 2023年第17卷第3期页码 446-446 doi: 10.1007/s11708-022-0851-7

摘要： Owing to increased penetration of three-phase and single-phase microgrids, distributed energy resources (DERs), and responsive loads, the maintenance of a three-phase balance by distribution networks is a significant challenge. Existing literature on distributed energy management for networked microgrids generally neglects the distribution network or employs a simplified phase balanced distribution network; thus, these evaluations are not applicable. Further, the underlying mutual coupling between the different phases of distribution feeders results in a more challenging situation. To solve this issue, this study sought to propose distributed energy management based on a three-phase unbalanced distribution network. Various three-phase or single-phase microgrids, utility-owned DERs, and responsive loads were coordinated through iteratively adjusted price signals. Based on the price signals received, the microgrid controllers (MCs) and distribution management system (DMS) updated the schedules of the DERs and responsive loads under their jurisdiction separately. The price signals were then updated according to the generation-load mismatch at each node and distributed to the corresponding MCs and DMS for the next iteration. The iteration continued until a sufficiently small generation-load mismatch was achieved at all nodes, that is, a balanced generation and load at all nodes under the agreed price signals. Considering a three-phase unbalanced distribution network, the price signals were determined per phase per node. Overall, the proposed distributed energy management coordinates microgrids, utility-owned DERs, responsive loads with guaranteed network constraints, and preserves the privacy of microgrid customers. This distributed energy management method was further demonstrated through various case studies on a three-phase networked microgrid test system.

关键词： distributed optimization energy management networked microgrids three-phase distribution network distributed energy resources

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具有智能外围的智能电网——能源互联网架构 Artical

Felix F. Wu,Pravin P. Varaiya,Ron S. Y. Hui

《工程（英文）》 2015年第1卷第4期页码 436-446 doi: 10.15302/J-ENG-2015111

摘要：

未来的智能电网应能够实现能源互联网的愿景：数百万用户利用可再生能源，在家庭、办公室和工厂生产所需的能源，并实现共享；广泛使用电动车辆和本地储能系统；利用互联网技术将当前电网升级为实现能源共享的互联网络。为实现这个愿景，本文提出了具有智能外围的智能电网的架构和概念，或称为智能GRIP。GRIP架构的构建模块被称为集群，配置能量管理系统(EMS) 的输电网是一个在电网核心的集群，外围的配电网，微电网和智能楼宇及住宅均为(外围的) 集群。这些集群全部采用分层结构。GRIP的分层架构可让电网实现从当前电网功能到未来即插即用型电网的无缝过渡。所有的集群都包括三个基本功能，即调度、消除波动和故障缓解。为实现上述功能，本文提出了风险约束的调度方法；开发了一种名为“电力弹簧”的新型装置，用于消除外围集群的电力波动；另外还讨论了故障的缓解措施。

关键词：智能电网未来电网能源互联网能量管理系统可再生能源接入电力系统运行电力系统控制配电自动化系统需求侧管理

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电动汽车关键技术发展综述

王丹,续丹,曹秉刚

《中国工程科学》 2013年第15卷第1期页码 68-72

摘要：

介绍了电动汽车关键技术发展状况，分别从电动汽车用驱动电机、动力电池及电池管理系统、电机控制及能量回收系统等方面进行了概述，并对电动汽车技术发展趋势进行了展望。在政府的支持下，随着电机、电池及电控等电动汽车关键技术逐步完善，电动汽车必将成为“零污染”的清洁交通工具。

关键词：电动汽车电机电池能源管理系统能量回收系统

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Special issue: Transition management of energy systems towards carbon neutrality

《工程管理前沿（英文）》 2022年第9卷第3期页码 355-357 doi: 10.1007/s42524-022-0219-z

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Machine learning in building energy management: A critical review and future directions

《工程管理前沿（英文）》 2022年第9卷第2期页码 239-256 doi: 10.1007/s42524-021-0181-1

摘要： Over the past two decades, machine learning (ML) has elicited increasing attention in building energy management (BEM) research. However, the boundary of the ML-BEM research has not been clearly defined, and no thorough review of ML applications in BEM during the whole building life-cycle has been published. This study aims to address this gap by reviewing the ML-BEM papers to ascertain the status of this research area and identify future research directions. An integrated framework of ML-BEM, composed of four layers and a series of driving factors, is proposed. Then, based on the hype cycle model, this paper analyzes the current development status of ML-BEM and tries to predict its future development trend. Finally, five research directions are discussed: (1) the behavioral impact on BEM, (2) the integration management of renewable energy, (3) security concerns of ML-BEM, (4) extension to other building life-cycle phases, and (5) the focus on fault detection and diagnosis. The findings of this study are believed to provide useful references for future research on ML-BEM.

关键词： building energy management machine learning integrated framework knowledge evolution

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Synergetic Management Theory for Coal-Based Energy Engineering and the Engineering Practice of Shenhua

Wen Ling

《工程管理前沿（英文）》 2016年第3卷第1期页码 1-8 doi: 10.15302/J-FEM-2016005

摘要： To deal with problems in synergetic development of coal-based energy engineering, this paper, guided by the philosophy of engineering, proposes the synergetic management philosophy of “factors coordination, systems synergy, dynamic optimization and three-dimension planning.” The paper also establishes the synergetic management system characterized by systems factor synergy, resource-environment synergy and systems boundary extension and supported by the “two-wheel driven” management innovation and technological innovation. In addition, the paper presents a multi-objective dynamic optimization model for energy engineering, designed based on Shenhua’s own engineering practice, to analyze Pareto optimal solution in three scenarios: best resource allocation, minimal environmental impact and maximal value creation. This provides important reference to synergetic development strategies and decision-making in engineering management.

关键词： coal-based energy engineering synergetic management two-wheel driven innovation Shenhua engineering