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Research on enhancing RDGs accommodation and prolonging cable life via a combination of DTR, network reconfiguration and active controls

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ELECTRIC POWER SYSTEMS RESEARCH 2025年 239卷

作者： Pan, Chen Chen, Weijiang Zhou, Chengke Zhou, Wenjun Li, Gen Wuhan Univ Sch Elect Engn & Automat Wuhan 430072 Peoples R China State Grid Corp China Beijing Peoples R China

Dynamic thermal rating (DTR) is an effective strategy that can enlarge transfer capacity of cables and enhance renewable distributed generators (RDGs) accommodation in favorable meteorological conditions. However, with higher penetration of RDGs, distribution networks face voltage rise challenge, which in turn could hinder further implementation of DTR. At the same time, higher carrying-currents aggravate losses of life (LOL) of cables. To deal with such issues, an optimal model is proposed, which aims to minimize the operation cost by comprehensively taking advantages of DTR, network reconfiguration and active controls such as energy storage and reactive power compensation devices, so as to effectively enhance RDGs accommodation as well as keep the LOL of cables at a relative low level. Accordingly, a model transformation method based on second-order cone relaxation, linearization of variables product and piecewise linearization is designed, the original non-convex nonlinear model is then transformed into a mixed integer second-order cone programming (MISOCP) model by convex processing of non-convex sources, thus reducing the computational complexity. Numerical results demonstrate that the proposed model can effectively enhance RDGs accommodation as well as reduce the LOL of cables.

关键词： Dynamic thermal rating Renewable distributed generators accommodation Active controls Network reconfiguration mixed integer second-order cone programming Loss of life of cables

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Profit maximization in congested hub location problems: Demand models and service level constraints

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TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW 2025年 195卷

作者： Marand, Ata Jalili Hoseinpour, Pooya Aarhus Univ Dept Econ & Business Econ Aarhus Denmark Amirkabir Univ Technol Tehran Polytech Dept Ind Engn & Management Syst Tehran Iran

This study investigates a congested hub location problem with the aim of optimizing a service provider's profit by determining hub locations, capacities, and prices for serving commodities. The study incorporates a price-dependent demand function with a general functional form and models hub operations as M/G/1 queueing systems to address congestion effects. The problem is initially formulated as a mixed-integer nonlinear program, which is subsequently transformed into a mixed-integer second-order cone program, demonstrating solvability with standard off- the-shelf solvers. Through numerical analysis, the study evaluates the influence of different demand functional forms and service time constraints on the optimal network configuration and the service provider's profitability.

关键词： Hub location problem Congestion Pricing Queuing mixed integer second-order cone programming

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Exploiting demand-side heterogeneous flexible resources in risk management of power system frequency

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Science China(Technological Sciences) 2024年第5期67卷 1612-1627页

作者： YAO Yu SONG YongHua YE ChengJin DING Yi ZHAO YuMing College of Electrical Engineering Zhejiang UniversityHangzhou310027China State Key Laboratory of Internet of Things for Smart City University of MacaoMacao SAR519000China Shenzhen Power Supply Bureau Co. Ltd.Shenzhen518051China

More demand-side flexible resources(DFRs)are participating in the frequency regulation of renewable power systems,whose heterogeneous characteristics have a significant impact on the system frequency ***,selecting suitable DFRs poses a formidable challenge for independent system operators(ISO).In this paper,a reserve allocation methodology for heterogeneous DFRs is proposed to manage the risk of power system ***,a performance curve is developed to describe the cost,capacity,and response speed of ***,a clustering method for multiple distributed DFRs is conducted to calculate the aggregated performance curves and uncertainty ***,the frequency security criterion considering DFRs’performance is constructed,whose linearity makes it can be easily coupled into the system scheduling model and ***,a risk management model for DFRs considering frequency-chance-constraint is proposed to make a trade-off between cost and frequency ***,the model is transformed into mixed integer second-order cone programming(MISOCP)and solved by the commercial *** proposed model is validated by the IEEE 30 and IEEE 118 bus systems.

关键词： demand-side heterogenous flexible resources risk management of power system frequency performance curve aggregation method mixed integer second-order cone programming

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Coordinated Planning of Converter-Based DG Units and Soft Open Points Incorporating Active Management in Unbalanced Distribution Networks

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IEEE TRANSACTIONS ON SUSTAINABLE ENERGY 2020年第3期11卷 2015-2027页

作者： Wang, Jian Zhou, Niancheng Chung, C. Y. Wang, Qianggang Chongqing Univ State Key Lab Power Transmiss Equipment & Syst Se Chongqing 400044 Peoples R China Univ Saskatchewan Dept Elect & Comp Engn Saskatoon SK S7N 5A9 Canada

Soft open points (SOPs) can transfer active power between feeders and compensate reactive power. These features help increase the integration capacity of distributed generation (DG), but the installation location and capacity of SOPs will affect DG planning. In addition, the distribution networks are usually unbalanced due to asymmetric line parameters, unbalanced loads, and DG. Converter-based DG units and SOPs have individual phase active and reactive power regulating ability and provide unbalance compensation. The objective of this paper is to develop a coordinated planning model of converter-based DG units and SOPs in an unbalanced distribution network (UDN) to incorporate their individual phase power control abilities. The individual phase power control characteristics of DG converters and SOPs are first analyzed. A bi-level optimization model of converter-based DG units and SOP planning is then established, in which the upper-level problem minimizes the total cost of the UDN and the lower-level problem minimizes the power loss and voltage unbalance. The bi-level model is transformed into a single-level mixed integer second-order cone programming problem that can be efficiently solved by widely used commercial solvers. Finally, the proposed model is verified on IEEE 33-node and Taiwan Power Company systems.

关键词： Reactive power Mathematical model Planning Power conversion Power control Optimization Unbalanced distribution networks coordinated planning distributed generation soft open points mixed integer second-order cone programming

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A New Mathematical Model for the Restoration Problem in Balanced Radial Distribution Systems

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IEEE TRANSACTIONS ON POWER SYSTEMS 2016年第2期31卷 1259-1268页

作者： Romero, Ruben Franco, John F. Leao, Fabio B. Rider, Marcos J. de Souza, Eliane S. UNESP Univ Estadual Paulista Fac Engn Ilha Solteira Dept Elect Engn Ilha Solteira SP Brazil

This paper presents a comprehensive mathematical model to solve the restoration problem in balanced radial distribution systems. The restoration problem, originally modeled as mixed integer nonlinear programming, is transformed into a mixed integer second-order cone programming problem, which can be solved efficiently using several commercial solvers based on the efficient optimization technique family branch and bound. The proposed mathematical model considers several objectives in a single objective function, using parameters to preserve the hierarchy of the different objectives: 1) maximizing the satisfaction of the demand, 2) minimizing the number of switch operations, 3) prioritizing the automatic switch operation rather than a manual one, and 4) prioritizing especial loads. General and specialized tests were carried out on a 53-node test system, and the results were compared with other previously proposed algorithms. Results show that the mathematical model is robust, efficient, flexible, and presents excellent performance in finding optimal solutions.

关键词： Distribution system optimization mixed integer second-order cone programming restoration problem

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Robust Optimization Dispatch Method for Distribution Network Considering Four-Quadrant Power Output of Energy Storage Devices

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JOURNAL OF ELECTRICAL ENGINEERING & TECHNOLOGY 2024年第2期19卷 919-930页

作者： Li, Yue Xiao, Xiao-Bing He, Xiao-Meng Huang, Bo-Yang Fang, Yang He, Xin-Yi Guizhou Power Grid Co Ltd Power Sci Res Inst Guiyang Guizhou Peoples R China China Southern Power Grid Res Inst LLC Co Guangzhou Peoples R China

This paper describes a technique for improving distribution network dispatch by using the four-quadrant power output of distributed energy storage systems to address voltage deviation and grid loss problems resulting from the large integration of distributed generation into the distribution network. The approach creates an optimization dispatch model for an active distribution network. The objective function aims to minimize power purchase costs, network loss costs, and voltage deviation penalties. In addition, the method employs an interval robust optimization technique to handle uncertainties related to solar turbine output and load demand. To solve the optimal power flow problem for AC in the distribution network, this paper implements the second-order cone relaxation technique to convert it into a solvable second-order cone programming problem. Moreover, the Big-M method is used to handle the nonlinear terms in the objective function. Finally, simulation experiments are conducted on the IEEE33 node system to verify the effectiveness and superiority of the proposed method. The simulation results indicate that the system's operating cost can be significantly reduced. Additionally, it has a positive impact on reducing voltage deviation and system loss, ultimately improving the operation of the distribution network system.

关键词： Active distribution network Distributed energy storage Power four-quadrant output mixed integer second-order cone programming Robust optimization

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Delay-aware downlink beamforming with discrete rate adaptation for green cloud radio access network

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The Journal of China Universities of Posts and Telecommunications 2017年第1期24卷 26-34页

作者： Yu Zhi Wang Ke Ji Hong School of Telecommunication Engineering Beijing University of Posts and Telecommunications Beijing 100876 China

With the popularity of variety delay-sensitive services, how to guarantee the delay requirements for mobile users （MUs） is a great challenge for downlink beamformer design in green cloud radio access networks （C-RANs）. In this paper, we consider the problem of the delay-aware downlink beamforming with discrete rate adaptation to minimize the power consumption of C-RANs. We address the problem via a mixed integer nonlinear program （MINLP）, and then reformulate the MINLP problem as a mixed integer second-order cone program （MI-SOCP）, which is a convex program when the integer variables are relaxed as continuous ones. Based on this formulation, a deflation algorithm, whose computational complexity is polynomial, is proposed to derive the suboptimal solution. The simulation results are presented to validate the effectiveness of our proposed algorithm.

关键词： C-RAN delay-aware downlink beamfoming discrete rate adaptation green communication mixed integer second-order cone programming

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Bi-Level programming-Based Optimal Strategy to LSEs with Demand Response Bids

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ELECTRIC POWER COMPONENTS AND SYSTEMS 2018年第18期46卷 1926-1937页

作者： Ding, Tao Yang, Qingrun Jiang, Jiangfeng Yang, Yongheng Blaabjerg, Frede Li, Yaohong Ju, Yuntao Xi An Jiao Tong Univ Sch Elect Engn State Key Lab Elect Insulat & Power Equipment Xian 710049 Shaanxi Peoples R China Aalborg Univ Dept Energy Technol Aalborg Denmark State Grid Jiangsu Elect Power Co Nanjing Jiangsu Peoples R China China Agr Univ Dept Elect Engn Beijing Peoples R China

As a profit-seeking market participant, load serving entities (LSEs) have been trying to apply demand response (DR) programs to induce the demand elasticity to further their profit. However, due to the different preference of DRs, it is difficult for LSEs to generate the optimal strategic bidding strategy in the ISO/RTO's market. Therefore, this paper proposed a bi-level optimization model considering DR bidding to maximize the total profit of LSEs: conceptually, the consumers participate DR through setting their bidding prices to LSEs with respect to their own preference and LSEs should determine the optimal reward value of DR as well as the amount of demanded electricity;technically, an original method has been implemented to solve the bi-level optimization model. The closed form of shadow price function with respect to the total load demand is derived to reduce the complexity. Hence, the proposed model is converted to a mixed integer second order cone programming and able to achieve the global optimality. It needs to be note that the closed form of shadow price introduced in this paper can also be applied to other bi-level programming models. Moreover, case studies have been performed to demonstrate the validity of the proposed method.

关键词： demand response mixed integer second-order cone programming optimal strategy bi-level programming load serving entities (LSEs)

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Voltage Restoration After Unforeseen Disturbances in Weakly Observable Distribution Systems

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IEEE TRANSACTIONS ON POWER SYSTEMS 2022年第4期37卷 3063-3076页

作者： Nouri, Alireza Jafarian, Mohammad Keane, Andrew Univ Coll Dublin Energy Inst Dublin 04 Ireland Univ Coll Dublin Sch Elect & Elect Engn Dublin 04 Ireland

Following an unforeseen disturbance in a power system, the system state should be known to extract the emergency voltage restoration strategy. Such a condition does not usually hold in distribution systems due to the lack of enough measurements. Here, the joint probability density function (pdf) of uncertain parameters is extracted from historical data. This pdf is updated to comply with the measurements. A set of samples is then generated that best models the updated pdf. These data reconciliation and sampling techniques enable the functioning of the emergency voltage control (evc) with measurement scarcity. They are designed to be fast enough to meet the quasi-real-time requirements of the intended application. The evc problem is cast as a stochastic programming problem. The resultant problem is a mixed-integer non-convex (and hence, NP-hard) optimization problem. It is solved using five distinct sms based on relaxation/approximation of the non-convex constraints. The results show that a novel combination of relaxation and approximation aimed at respectively mitigating the emergency under- and over-voltages outperforms the others. The propounded stochastic evc is validated through numerical studies.

关键词： Voltage control Probability density function Voltage measurement programming Reactive power Velocity measurement Stochastic processes mixed integer second-order cone programming observability voltage control voltage restoration

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Fulfillment Center Location and Network Design in Dual-Channel Retailing

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NETWORKS & SPATIAL ECONOMICS 2024年 1-35页

作者： Malik, Aditya Vidyarthi, Navneet Concordia Univ John Molson Sch Business Montreal PQ H3G 1M8 Canada Interuniv Res Ctr Enterprise Networks Logist & Tra Montreal PQ H3G 1M8 Canada

With the emergence of e-commerce and the growing trend for online shopping, many retailers are adding online sales channel to their traditional brick-and-mortar stores. In this paper, we study the problem of fulfillment center location and network design for a retailer that seeks to integrate online sales channel into its traditional brick-and-mortar retail channel. The proposed analytical model seeks to locate fulfillment centers, select stores for online demand fulfillment, assign stores to fulfillment centers, and allocate safety stocks at fulfillment centers and stores to deal with variability in demand and lead time at minimum total cost. The problem is modelled as a mixed-integer nonlinear program, which is then reformulated as a mixed-integer second-order conic program. We present an exact branch-and-cut algorithm for the reformulated problem, in which extended polymatroid inequalities are separated to improve the convergence of the algorithm. Extensive computations under different cost scenarios and parameter settings confirm the efficiency of our exact algorithm. Through computational experiments, we showed that our algorithm reduces computation time, provides lower optimality gap, and outperforms the state-of-the art commercial solver on large instances. We conduct sensitivity analyses to understand the impact of variation in cost and model parameters and present managerial insights. The model also determines if the safety stock inventory should be pooled at the distribution centers (i.e. centralized inventory) and/or held at the stores (i.e. decentralized inventory). Using the model, we show the benefits of integrating fulfillment centers in the dual-channel network to serve in-store demand as well as online demand and its impact on facility location and network design decisions.

关键词： Facility location Fulfillment network design Dual-channel retailing Safety stock mixed integer second-order cone programming Branch-and-cut

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