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Flexible feeder interconnections for increased penetration of renewables and improved volt/VAr control in distribution networks

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IET GENERATION TRANSMISSION & DISTRIBUTION 2019年第21期13卷 4861-4869页

作者： Baghban-Novin, Salar Golshannavaz, Sajjad Nazarpour, Daryoush Hamidi, Amir Urmia Univ Elect Engn Dept Orumiyeh Iran

In this study, a daily distribution management system (DMS) is developed, which utilises the potential of soft open points (SOPs) to enhance the renewable share in power provision task. The active and reactive power contributions of SOPs, as a flexible interconnection, amend the voltage security issues due to high penetration of photovoltaics (PVs). A complete model for SOP is developed to address the conduction and switching losses that affect the technical and economic operation indices. The optimal scheduling framework of DMS is linearly modelled within mixed-integer linear programming to lower the computational burden of the problem. Case studies are carried out on IEEE 33-node system to illustrate and verify the effectiveness of the proposed model. The comparative analysis shows a lower operation cost besides the improved voltage profile and the reduced losses of the whole system. The effective collaboration of PVs and dispatchable distributed generations (DDGs) assisted by the SOPs power processes causes higher penetration of PVs and enhanced the exploitation of DDGs results in a 9.8% increment of PV power exploitation and improved power factor of DDGs operation.

关键词： integer programming scheduling distributed power generation photovoltaic power systems reactive power linear programming optimisation reactive power control voltage control power distribution control power system security distribution networks renewable share power provision task active power contributions reactive power contributions SOP flexible interconnection voltage security issues switching losses technical operation indices economic operation indices optimal scheduling framework DMS mixed-integer linear programming computational burden IEEE 33-node system lower operation cost improved voltage profile reduced losses dispatchable distributed generations SOPs power processes higher penetration PV power exploitation power factor DDGs operation flexible feeder interconnections distribution networks daily distribution management system soft open points

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Toward a MILP Modeling Framework for Distribution System Restoration

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IEEE TRANSACTIONS ON POWER SYSTEMS 2019年第3期34卷 1749-1760页

作者： Chen, Bo Ye, Zhigang Chen, Chen Wang, Jianhui Argonne Natl Lab Energy Syst Div 9700 S Cass Ave Argonne IL 60439 USA Xi An Jiao Tong Univ State Key Lab Elect Insulat & Power Equipment Xian 710049 Shaanxi Peoples R China Southern Methodist Univ Dept Elect Engn Dallas TX 75205 USA

Large-scale blackouts and extreme weather events in recent decades raise the concern for improving the resilience of electric power infrastructures. Distribution service restoration (DSR), a fundamental application in outage management systems, provides restoration solutions for system operators when power outages happen. As distribution generators (DGs) and remotely controllable devices are increasingly installed in distribution systems, an advanced DSR framework is needed to perform optimally coordinated restoration that can achieve maximal restoration performance. This paper introduces a DSR modeling framework, which can generate optimal switching sequences and estimated time of restoration in the presence of remotely controllable switches, manually operated switches, and dispatchable DGs. Two mathematical models, a variable time step model and a fixed time step model, are presented and compared. The proposed models are formulated as amixed-integer linear programming model, and their effectiveness is evaluated via the IEEE 123 node test feeder.

关键词： Distribution system distributed generation mixed-integer linear programming service restoration switching sequence management

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A matheuristic algorithm for the multi-depot inventory routing problem

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TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW 2019年 122卷 524-544页

作者： Bertazzi, Luca Coelho, Leandro C. De Maio, Annarita Lagana, Demetrio Univ Brescia Dept Econ & Management Brescia Italy Laval Univ CIRRELT Quebec City PQ Canada Laval Univ Canada Res Chair Integrated Logist Quebec City PQ Canada Univ Calabria Dept Mech Energy & Management Engn DIMEG Commenda Di Rende Italy

In this paper we solve a practical Multi-Depot Inventory Routing Problem (MDIRP). One minimizes routing costs by determining how to serve the customers from different depots, managing their inventory levels to avoid stock-outs. The MDIRP optimizes the trade-off between inventory and routing decisions in an integrated way. We formulate this problem as a mixed-integer linear programming model and design a three-phase matheuristic to solve the problem. The solutions of our matheuristic are compared with those from a branch-and-cut algorithm on classical IRP instances, new instances and a real case study, showing to be very effective.

关键词： Multi-depot inventory routing problem mixed-integer linear programming Matheuristic Clustering

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Optimizing ground station networks for free space optical communications: Maximizing the data transfer

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NETWORKS 2019年第2期73卷 234-253页

作者： Capelle, Mikael Huguet, Marie-Jose Jozefowiez, Nicolas Olive, Xavier Thales Alenia Space France Toulouse France Univ Toulouse CNRS INSA LAASCNRS 7 Ave Colonel Roche Toulouse France Univ Lorraine LCOMS Metz France

Free space optical communications are becoming a mature technology to cope with the needs of high data rate payloads for future low-earth orbiting observation satellites. However, they are strongly impacted by clouds. In this paper, we aim to find a network of optical ground stations maximizing the percentage of data acquired by a low-earth orbiting satellite that can be transferred to the Earth, taking into consideration cloud information. This problem can be separated in two parts and solved hierarchically: the selection of a network of optical ground stations and the assignment of downloads to visibility windows of the stations. We present theoretical and practical results regarding the complexity of the latter subproblem and propose a dynamic programming algorithm to solve it. We combine this algorithm with two methods for the enumeration of the stations, and compare them with a mixed integer linear program (MILP). Results show that even if the MILP can solve scenarios over small horizons, the hierarchical approaches outperform it in term of computation time while still achieving optimality for larger instances.

关键词： cloud uncertainties combinatorial optimization dynamic programming free space optical communications mixed-integer linear programming network design

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Optimal Operation of Unbalanced Three-Phase Islanded Droop-Based Microgrids

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IEEE TRANSACTIONS ON SMART GRID 2019年第1期10卷 928-940页

作者： Vergara, Pedro P. Lopez, Juan C. Rider, Marcos J. da Silva, Luiz C. P. Univ Estadual Campinas Dept Syst & Energy BR-13083852 Campinas SP Brazil

This paper presents a new mixed-integer nonlinear programming (MINLP) model for the optimal operation of unbalanced three-phase droop-based microgrids. The proposed MINLP model can be seen as an extension of an optimal power flow for microgrids operating in islanded mode, that aims to minimize the total amount of unsupplied demand and the total distributed generator (DG) generation cost. Since the slack bus concept is not longer valid, the proposed model considers the frequency and voltage magnitude reference as variables. In this case, DCs units operate with droop control to balance the system and provide a frequency and voltage magnitude reference. Additionally, a set of efficient linearizations are introduced in order to approximate the original MINLP problem into a mixed-integer linear programming (MILP) model that can be solved using commercial solvers. The proposed model has been tested in a 25-bus unbalanced three-phase microgrid and a large 124-node grid, considering different operational and time-coupling constraints for the DGs and the battery systems (BSs). Load curtailment and different modes of operation for the wind turbines have also been tested. Finally, an error assessment between the original MINLP and the approximated MILP model has been conducted.

关键词： Droop control islanded microgrid mixed-integer linear programming three-phase optimal power flow

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Second-order extensions to nearly orthogonal-and-balanced (NOAB) mixed-factor experimental designs

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JOURNAL OF SIMULATION 2019年第3期13卷 226-237页

作者： Little, Zachary C. Weir, Jeffery D. Hill, Raymond R. Stone, Brian B. Freels, Jason K. Perduco Grp 3610 Pentagon Blvd 110 Beavercreek OH 45431 USA Air Force Inst Technol Dept Operat Sci Wright Patterson AFB OH USA Air Force Inst Technol Dept Syst Engn & Management Wright Patterson AFB OH USA

When simulation studies involve many quantitative (i.e., discrete and continuous) and qualitative (i.e., categorical) input factors with different numbers of levels for each, meta-models of simulation responses can benefit from the use of mixed-factor space-filling designs. The first-order nearly orthogonal-and-balanced (NOAB) design is a popular approach in these situations. This research develops second-order extensions for an existing construction method of NOAB designs, estimating the pairwise correlations between possible first-order and second-order terms. These extensions permit additional linear constraints in the mixed-integer linear programming (MILP) formulations previously developed for first-order NOAB designs. A case study is presented for NOAB designs of different sizes and construction approaches. The second-order MILP extensions show improvements in design performance measures for parameter estimation and prediction variance for an assumed second-order model as well as for model misspecification with respect to second-order terms for an assumed first-order model.

关键词： Design of experiments mixed-integer linear programming pairwise correlation model misspecification meta-model

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Toward a Synthetic Model for Distribution System Restoration and Crew Dispatch

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IEEE TRANSACTIONS ON POWER SYSTEMS 2019年第3期34卷 2228-2239页

作者： Chen, Bo Ye, Zhigang Chen, Chen Wang, Jianhui Ding, Tao Bie, Zhaohong Argonne Natl Lab Energy Syst Div Argonne IL 60439 USA Xi An Jiao Tong Univ State Key Lab Elect Insulat & Power Equipment Xian 710049 Peoples R China Southern Methodist Univ Dept Elect Engn Dallas TX 75205 USA Xi An Jiao Tong Univ Xian 710049 Shaanxi Peoples R China

Distribution service restoration (DSR) is critical for improving the resilience and reliability of modern distribution systems by strategically and sequentially energizing the system components and customer loads. Restoring electricity service to affected customers also requires multiple crews with different skill sets to perform multiple tasks that are procedurally interdependent with safety guaranteed. However, in existing DSR practices, switch operations and crew dispatch are scheduled separately, and their interdependence is not fully considered. As advanced technologies are enabling remote communication, control, and dispatch, utilities now desire an integrated DSR framework to achieve seamless coordination among multiple DSR tasks such as switch operation, crew dispatch, and component repair. In this paper, we introduce a synthetic model that integrates the service restoration model and the crew dispatch model based on a universal routing model. The proposed model can provide the estimated time of restoration for each load, the switching sequence for safely operating remotely/manually operated switches, and dispatch solutions for crews with different skill sets. The proposed synthetic model is formulated as a mixed-integer linear programming model, and its effectiveness is evaluated via the IEEE 123 bus test feeder and several large-scale test feeders (EPRI Ckt5, Ckt7, Ckt24, and IEEE 8500 node test feeder.

关键词： Distribution service restoration crew dispatch mixed-integer linear programming repair switching sequence management

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Efficient train re-routing and rescheduling: Valid inequalities and reformulation of RECIFE-MILP

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TRANSPORTATION RESEARCH PART B-METHODOLOGICAL 2019年 120卷 33-48页

作者： Pellegrini, Paola Pesenti, Raffaele Rodriguez, Joaquin Univ Lille Nord France IFSTTAR COSYS LEOST 20 Rue Elisee ReclusBP 70317 F-59666 Villeneuve Dascq France Univ Ca Foscari Venezia Dept Management Cannaregio 873 I-30121 Venice Italy Univ Lille Nord France IFSTTAR COSYS ESTAS 20 Rue Elisee ReclusBP 70317 F-59666 Villeneuve Dascq France

The real-time Railway Traffic Management problem consists in finding suitable train routes and schedules to minimize delay propagation due to traffic perturbations. RECIFE-MILP is a mixed integer linear programming based heuristic for this problem which has proven to be effective in various contexts. However, when instances are very large or difficult, the performance of the algorithm may worsen. In this paper, we propose valid inequalities to boost the performance of RECIFE-MILP. These valid inequalities link the routing and scheduling binary variables. We also provide an instance in which they are able to represent all the facets of the projection of the convex hull of the problem in the sub-space of the binary variables. Moreover, they allow reformulating the model based on a reduced number of scheduling binary variables. In an experimental analysis based on realistic instances representing traffic in four French infrastructures, we observe that the merit of addition of valid inequalities depends on the specific case-study at hand, and that the reduction of the number of binary variables in general boosts the performance of RECIFE-MILP significantly. (C) 2019 Elsevier Ltd. All rights reserved.

关键词： Transportation Real-time railway traffic management problem Train re-routing and rescheduling mixed-integer linear programming Valid inequalities

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Robust Control of a Microgrid Energy Storage System Using Various Approaches

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IEEE TRANSACTIONS ON SMART GRID 2019年第3期10卷 2702-2712页

作者： Choi, Jongwoo Shin, Youngmee Choi, Moonok Park, Wan-Ki Lee, Il-Woo Seoul Natl Univ Dept Mech & Aerosp Engn Seoul 08826 South Korea Elect & Telecommun Res Inst IoT Res Div Daejeon 34129 South Korea

This paper presents a robust optimal control strategy for an energy storage system (ESS) of a grid-connected microgrid. The robust optimal control guarantees the highest possible economic benefit of the control schedule even under the worst case net demand prediction error conditions. Several robust optimization approaches are proposed to formulate a fast optimal control problem. The global optimum of a concise control problem can be found within a short computation time using mixed-integer linear programming. The rolling horizon controller of the energy management system periodically updates the control schedule by solving the control problem. The state of charge of an ESS is precisely calculated by the piecewise linearization technique using nonlinear efficiency maps. External working conditions such as peak control and demand response can be dynamically applied during the optimization process. The proposed strategy provides control robustness in terms of cost reduction, precise control, and external effect. Future study will focus on the development of a robust control strategy that considers both the worst and best cases of cost reduction.

关键词： Demand response efficiency map energy management system energy storage system microgrid mixed-integer linear programming peak control robust optimization

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Utilising demand response for distribution service restoration to achieve grid resiliency against natural disasters

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IET GENERATION TRANSMISSION & DISTRIBUTION 2019年第14期13卷 2942-2950页

作者： Hafiz, Faeza Chen, Bo Chen, Chen de Queiroz, Anderson Rodrigo Husain, Iqbal North Carolina State Univ Dept Elect & Comp Engn Raleigh NC 27695 USA Argonne Natl Lab Div Energy Syst 9700 S Cass Ave Argonne IL 60439 USA North Carolina Cent Univ Sch Business Dept Decis Sci Durham NC USA North Carolina State Univ Civil Construct & Environm Engn Dept Raleigh NC USA

The increased frequency of power outages due to natural disasters in recent years has highlighted the urgency of enhancing distribution grid resilience. The effective distribution service restoration (DSR) is an important measure for a resilient distribution grid. In this work, the authors demonstrate that DSR can be significantly improved by leveraging the flexibility provided by the inclusion of demand response (DR). The authors propose a framework for this by considering integrated control of household-level flexible appliances to vary the load demand at the distribution-grid level to improve DSR. The overall framework of the proposed system is modelled as a three-step method considering three optimization problems to (i) calculate feasible controllable aggregated load range for each bus, (ii) determine candidate buses to perform DR and their target load demand, and (iii) maintain the load level in each house through home energy management during the DSR, considering uncertainties in load and solar generation sequentially. The optimization problems are formulated as linear programming, mixed-integer linear programming, and multistage stochastic programming (solved using the stochastic dual dynamic programming) models. Case studies performed in the IEEE 123-node test feeder show improvements in resilience in terms of energy restored compared to the restoration process without DR.

关键词： optimisation power grids energy management systems power distribution control power system restoration demand side management domestic appliances demand response grid resiliency power outages distribution grid resilience resilient distribution grid integrated control household-level flexible appliances distribution-grid level optimisation problems aggregated load target load demand mixed-integer linear programming distribution service restoration IEEE 123-node test feeder system stochastic dual dynamic programming multistage stochastic programming solar generation home energy management

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