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

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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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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Heuristic solution of a joint electric control reserve and wholesale market model

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International Journal of Modeling, Simulation, and Scientific Computing 2019年第2期10卷 1-20页

作者： Timo Breithaupt Thomas Leveringhaus Lutz Hofmann Institute of Electric Power Systems Leibniz Universit¨at Hannover Welfengarten 1 30167 HanoverGermany

A mixed integer linear programming(MILP)approach for the joint simulation of electric control reserve and electricity wholesale markets is *** generation dispatch model extends an existing integrated grid and electricity market(IGEM)model covering the Continental European electric power *** explicitly incorporating the markets for primary and secondary control reserves(PCR and SCR),the model can reproduce the decisions of generating unit operators on which markets get ***,the introduction of the integrality conditions allows considering start-up costs and the calculus of generating units to pass through the economically unattractive periods with low or even negative prices in order to avoid another *** this model is too large to be solved with common MILP solvers for the intended simulation time of one year,temporal and geographical interdependencies are used to solve it *** heuristic therefore splits the model into various sub-problems so that on the one hand,the number of variables,especially of integer variables,per sub-problem is reduced significantly and on the other hand,the relevant interdependencies remain *** heuristic is evaluated in terms of accuracy and computation time by means of two case *** case studies show satisfactory accuracy and significant advantages in computation time.

关键词： mixed-integer linear programming unit commitment rolling horizon heuristic

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A decomposition-based heuristic for large employee scheduling problems with inter-department transfers

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EURO JOURNAL ON COMPUTATIONAL OPTIMIZATION 2019年第4期7卷 325-357页

作者： Attia, Dalia Burgy, Reinhard Desaulniers, Guy Soumis, Francois Polytech Montreal Dept Math & Genie Ind Montreal PQ Canada Gerad Montreal PQ Canada Univ Fribourg Dept Informat Fribourg Switzerland

We consider a personalized employee scheduling problem with characteristics present in retail stores consisting of multiple departments. In the setting under study, each department generally covers its demand in employees over the planning horizon of a week by assigning shifts to its own staff. However, the employees can also be transferred to other departments under certain conditions for executing entire shifts or parts of shifts there. The transfer feature enables to improve the overall schedule quality considerably when compared to the nontransfer case. Given the complexity of the problem, we propose a three-phase decomposition-based heuristic. In the first phase, we consider each department separately and solve a simplified version of the mono-department scheduling problems. From the obtained solutions, we deduce inter-department shifts that could potentially reduce the overall cost. This is examined in the second phase by resolving the scheduling problem of the first phase where the deduced inter-department shifts are included. In this phase, however, we decompose the scheduling problem by time, looking at each day separately. From the obtained schedules, we then devise inter-department demand curves, which specify the number of transfers between departments over time. In the third phase, we decompose the initial scheduling problem into mono-department problems using these inter-department demand curves. Consequently, our approach makes it possible to solve mono-department optimization problems to get an overall schedule while still benefiting from the employee transfer feature. In all three phases, the scheduling problems are formulated as mixed-integer linear programs. We show through extensive computational experiments on instances with up to 25 departments and 1000 employees that the method provides high-quality solutions within reasonable computation times.

关键词： Employees scheduling Shift scheduling Multi-department Retail industry Heterogeneous workforce mixed-integer linear programming Decomposition

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FORM FOLLOWS AVAILABILITY - DESIGNING STRUCTURES THROUGH REUSE

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JOURNAL OF THE INTERNATIONAL ASSOCIATION FOR SHELL AND SPATIAL STRUCTURES 2019年第4期60卷 257-265页

作者： Bruetting, Jan Senatore, Gennaro Fivet, Corentin Swiss Fed Inst Technol Lausanne EPFL Struct Xplorat Lab Lausanne Switzerland Swiss Fed Inst Technol Lausanne EPFL Appl Comp & Mech Lab Lausanne Switzerland

This work proposes a new direction in structural design: the synthesis of structures through the reuse of elements. Reusing structural elements reduces the environmental impacts of building structures because it avoids sourcing new material, it reduces waste and it requires little energy. Designing structures from reused elements is unlike conventional structural design because stock element availability is a design input. In other words, structures must be designed subject to availability of given element characteristics such as length and cross-section type, which have a major influence on the optimal structure layout and form. In this new paradigm structural form follows availability. In this work new computational methods for the synthesis of reticular structures through reuse are formulated to address two scenarios: a) reuse of reclaimed elements from a given stock, and b) design of an element stock which is used as a kit of parts to build diverse structures. Case studies are presented to demonstrate the potential of the proposed methods. It is shown that structures produced by these methods have a significantly lower environmental impact than minimum weight structures made of new elements.

关键词： Structural design discrete optimization geometry optimization mixed-integer linear programming reuse Life Cycle Assessment environmental impact

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An optimal scheduling model of an energy storage system with a photovoltaic system in residential buildings considering the economic and environmental aspects

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ENERGY AND BUILDINGS 2020年 209卷

作者： Jung, Seunghoon Kang, Hyuna Lee, Minhyun Hong, Taehoon Yonsei Univ Dept Architecture & Architectural Engn Seoul 03722 South Korea

In terms of sustainable development, the Energy Storage System (ESS) with a photovoltaic (PV) is an efficient technology for residential distributed generation to raise its economic and environmental benefits, which are differentiated by charge and discharge scheduling of ESS. Accordingly, it is essential to optimize the scheduling of ESS with PV to maximize economic and environmental benefits for residential buildings. Therefore, this study developed an optimal scheduling model of ESS with PV in residential buildings considering the economic and environmental aspects. The optimal scheduling model was developed in the following two steps: (i) definition of the variables;and (ii) development of the optimal scheduling model of ESS with PV. Despite the rule-based scheduling could only raise lifecycle environmental benefit by sacrificing economic benefit, the optimal scheduling could raise both lifecycle economic and environmental benefits increasing the net income and self-sufficiency rate by up to US$2.8 per month and 2.7%, compared to the case of applying the PV system without ESS. This study has significant contributions in facilitating the wide use of ESS with PV by not only improving its economic and environmental benefits for the ESS owner but also reducing the cost for constructing additional power plants for the government. (C) 2019 Elsevier B.V. All rights reserved.

关键词： Energy storage system Multi-objective optimization mixed-integer linear programming Epsilon-constraint method Economic and environmental analysis

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Mathematical modelling and heuristic approaches to the location-routing problem of a cost-effective integrated solid waste management

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ANNALS OF OPERATIONS RESEARCH 2019年第1-2期273卷 75-110页

作者： Asefi, H. Lim, S. Maghrebi, M. Shahparvari, S. Univ New South Wales Sch Civil & Environm Engn Sydney NSW 2052 Australia Ferdowsi Univ Mashhad Dept Civil Engn Mashhad Iran RMIT Univ Sch Business IT & Logist Melbourne Vic 3000 Australia

Integrated solid waste management (ISWM) comprises activities and processes to collect, transport, treat, recycle and dispose municipal solid wastes. This paper addresses the ISWM location-routing problem in which different types of municipal solid wastes are factored concurrently into an integrated system with all interrelated facilities. To support a cost-effective ISWM system, the number of locations of the system's components (i.e. transfer stations;recycling, treatment and disposal centres) and truck routing within the system's components need to be optimized. A mixed-integer linear programming (MILP) model is presented to minimise the total cost of the ISWM system including transportation costs and facility establishment costs. To tackle the non-deterministic polynomial-time hardness of the problem, a stepwise heuristic method is proposed within the frames of two meta-heuristic approaches: (i) variable neighbourhood search (VNS) and (ii) a hybrid VNS and simulated annealing algorithm (VNS+SA). A real-life case study from an existing ISWM system in Tehran, Iran is utilized to apply the proposed model and algorithms. Then the presented MILP model is implemented in CPLEX environment to evaluate the effectiveness of the proposed algorithms for multiple test problems in different scales. The results show that, while both proposed algorithms can effectively solve the problem within practical computing time, the proposed hybrid method efficiently has produced near-optimal solutions with gaps of <4%, compared to the exact results. In comparison with the current cost of the existing ISWM system in the study area, the presented MILP model and proposed heuristic methods effectively reduce the total costs by 20-22%.

关键词： Municipal solid waste Integrated solid waste management Location-routing problem mixed-integer linear programming Simulated annealing Variable neighbourhood search

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Constraint programming model for multi-manned assembly line balancing problem

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COMPUTERS & OPERATIONS RESEARCH 2020年 124卷

作者： Cil, Zeynel Abidin Kizilay, Damla Izmir Democracy Univ Dept Ind Engn Izmir Turkey

In recent years, the multi-manned assembly line has become popular since the large-sized products allow more than one operator working simultaneously on the same product in a workstation. This line usually occurs in large-size products such as cars, buses, trucks, and so on. The multi-manned assembly line offers several advantages, such as fewer number of workers/workstation and less cycle time to improve the performance of the system. However, it has been analyzed by a few papers in literature due to being a relatively new and complex problem. The current study aims to develop an efficient exact solution approach, constraint programming, to solve from small to large-size problems by minimizing the cycle time as a primary objective and the total number of workers as a secondary objective. First, two mixed-integer linear programming (MILP) models are proposed based on previous studies to solve the small test cases of the problem optimally. However, the models are not capable of solving the large-size test instances. Therefore, a constraint programming (CP) model is formulated to address both small and large-size data sets. The results of the CP model are compared with two MILP models and two heuristic algorithms available in the literature. The computational results indicate that the CP model discovers optimal solutions, approximately 90% of all the instances, and small optimality gaps in the remaining instances. It is useful to highlight that the CP model is highly concise and solved by a black-box, commercial solver. (c) 2020 Elsevier Ltd. All rights reserved.

关键词： Constraint programming Multi-manned assembly line balancing mixed-integer linear programming

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Coordination of OLTC and smart inverters for optimal voltage regulation of unbalanced distribution networks

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ELECTRIC POWER SYSTEMS RESEARCH 2020年 187卷

作者： Li, Changfu Disfani, Vahid R. Haghi, Hamed Valizadeh Kleissl, Jan Univ Calif San Diego Ctr Energy Res La Jolla CA 92093 USA Univ Calif San Diego Dept Mech & Aerosp Engn La Jolla CA 92093 USA Univ Tennessee Dept Elect Engn Chattanooga TN 37403 USA

Photovoltaic (PV) smart inverters can improve the voltage profile of distribution networks. A multi-objective optimization framework for coordination of reactive power injection of smart inverters and tap operations of onload tap changers (OLTCs) for multi-phase unbalanced distribution systems is proposed. The optimization objective is to minimize voltage deviations and the number of tap operations simultaneously. A novel linearization method is proposed to linearize power flow equations and to convexify the problem, which guarantees convergence of the optimization and less computation costs. The optimization is modeled and solved using mixed-integer linear programming (MILP). The proposed method is validated against conventional rule-based autonomous voltage regulation (AVR) on the highly-unbalanced modified IEEE 37 bus test system and a large California utility feeder. Simulation results show that the proposed method accurately estimates feeder voltage, significantly reduces voltage deviations, mitigates over-voltage problems, and reduces voltage unbalance while eliminating unnecessary tap operations. The robustness of the method is validated against various levels of forecast error. The computational efficiency and scalability of the proposed approach are also demonstrated through the simulations on the large utility feeder.

关键词： Distribution network Photovoltaic Tap changer Smart inverter mixed-integer linear programming Voltage regulation

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Short-Term Peak-Shaving Operation of Head-Sensitive Cascaded Hydropower Plants Based on Spillage Adjustment

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WATER 2020年第12期12卷 1-19页

作者： Liao, Shengli Zhang, Yan Liu, Benxi Liu, Zhanwei Fang, Zhou Li, Shushan Dalian Univ Technol Inst Hydropower & Hydroinformat Dalian 116024 Peoples R China Power Dispatching Control Ctr China Southern Powe Guangzhou 510623 Peoples R China

There are many cascaded hydropower plants with poor regulation performance and sensitive water heads accompanied by water spillage during the wet season. Faced with the increasing load peak-valley differences, it is necessary to tap the peak-shaving potential of such head-sensitive cascaded hydropower plants (HSCHPs) because relying solely on hydropower plants with better regulation performance for peak shaving is inadequate. To address the modeling, solving, and water spillage treatment difficulties posed by HSCHPs, a new short-term peak-shaving method based on spillage adjustment is introduced. First, fuzzy cluster analysis is used to determine when to release more water spillage by automatically identifying valley periods of the daily load curve. Furthermore, a spillage adjustment strategy, implemented through an easy gate operation, is adopted to readjust the water release during each period of the load curve. The ratio of the water spillage released in advance in a certain period to its total water spillage is defined as the water spillage ratio (WSR) of the period. Finally, a mixed-integer linear programming model linearized by special ordered sets of type two is solved to determine the optimal WSRs, which achieves the optimal peak-shaving effect. HSCHPs in the Hongshui River Basin during the wet season were selected as case studies. The results demonstrate that the proposed method can achieve a good peak-shaving effect without significantly reducing the power generation and adding additional water spillage.

关键词： head-sensitive cascaded hydropower plants fuzzy clustering analysis water spillage ratio mixed-integer linear programming

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