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Optimized Planning of Distribution Grids Considering Grid Expansion, Battery Systems and Dynamic Curtailment

ENERGIES 2021年第17期14卷

作者： Laribi, Ouafa Rudion, Krzysztof Univ Stuttgart Inst Power Transmiss & High Voltage Technol D-70174 Stuttgart Germany

The increasing integration of renewable energies into the grid is calling for the expansion of the power transport capacities in the distribution system. Yet, the expansion of the grid could require long authorization procedures and cannot be always asserted. Therefore, a higher utilization of the existing grid is becoming increasingly necessary today. This paper proposes a new time series-based planning method for distribution systems using classical grid expansion instruments as well as innovative planning instruments such as battery storage systems (BSS) and dynamic power curtailment (DPC). These planning instruments could be applied individually or combined. The aim of the BSS and DPC application is to enable a higher utilization of the grid at minimal costs. The proposed method, which has been implemented as an automated planning algorithm, determines the cost-optimal grid reinforcement measures that ensure the prevention of prognosticated congestions in the considered grid. Furthermore, the application of the proposed planning method on the considered power system has proven that a combination of BSS and grid expansion could be more economical than an individual application of BSS and grid expansion.

关键词： grid planning grid reinforcement grid expansion cost-optimal planning battery storage power curtailment distribution systems load flow calculation mixed integer linear programming

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Bioenergy supply chain optimization for addressing energy deficiency: A dynamic model for large-scale network designs

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JOURNAL OF CLEANER PRODUCTION 2021年 318卷

作者： Rafique, Raza Jat, Mohsin Hakeem-Ur-Rehman Chudhery, Muhammad Adnan Zahid Kean Univ Sch Management & Mkt Union NJ 07083 USA Univ Saskatchewan Edwards Sch Business Saskatoon SK Canada Univ Punjab Inst Qual & Technol Management Lahore Pakistan Tongji Univ Sch Econ & Management Shanghai 200092 Peoples R China Univ Sci & Technol China Int Inst Finance Sch Management Hefei 230026 Anhui Peoples R China

This study is motivated by the challenges faced by weak economies in addressing their energy deficiency. A gradual and strategic development of a sustainable bioenergy system is proposed as an opportunity to alleviate the connected energy and economy issues through a cleaner energy-mix. The optimization model presented in this study designs a bioenergy supply chain over multiple periods with the objective to minimize the energy gap under budget and biomass availability constraints. The dynamic elements of the model capture the interplay between population size, energy demand, biomass availability, energy consumption, and the Gross Domestic Product. A salient feature of the model is the consideration of an end-to-end bioenergy supply network from biomass reserves to the electricity demand zones. Besides facility setup and operating costs, the model considers biofuel transportation costs and transmission yield losses. The model is extensively analyzed through a case study. Practical insights about budget allocation and system expansion are discussed based on the case study. The analysis highlights that the cost for the optimum development of a bioenergy system can significantly vary over the planning horizon. The optimum setup starts as a highly centralized system and evolves into a largely decentralized system in which powerplants source biofuel and supply power locally.

关键词： Supply chain design Bioenergy Sustainable energy development mixed integer linear programming

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Carbon capture and storage from energy and industrial emission sources: A Europe-wide supply chain optimisation

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JOURNAL OF CLEANER PRODUCTION 2021年 290卷

作者： D'Amore, Federico Romano, Matteo Carmelo Bezzo, Fabrizio Univ Padua Dept Ind Engn CAPE Lab Comp Aided Proc Engn Lab Via Marzolo 9 IT-35131 Padua Italy Politecn Milan Dept Energy Via Lambruschini 4 IT-20156 Milan Italy

Power, steel, cement and refining sectors are currently responsible for the largest shares of carbon dioxide emissions from stationary sources. Carbon capture and storage is envisioned as a key player for decarbonising the power and industry sectors. To achieve a significant penetration of carbon capture and storage technologies, supply chain optimisation has emerged as a crucial research task for designing such complex systems. A Europe-wide carbon capture and storage supply chain is here optimised via a mixed integer linear programming framework. The most significant carbon dioxide emitters (242 power plants, 25 steel mills, 111 cement plants and 59 refineries) are identified on exact geographic coordinates and included as candidates for capture. Capture plants are thoroughly represented in techno-economic terms, considering scale effects and different technological options. Transport and sequestration stages are implemented for either onshore or offshore operation. Different case studies are taken into account to assess carbon capture and storage policies and results determine optimal configurations in terms of costs, scale effects, technology options and network complexity. The minimum CO2 avoidance cost is 52 (sic)/t, which increases by 9% if power plants are excluded from carbon sources. If offshore storage is preferred to onshore, cost raises by about 40%. (C) 2020 Elsevier Ltd. All rights reserved.

关键词： Carbon capture and storage mixed integer linear programming European supply chain optimisation Energy Steel Cement Oil refining

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Optimization Tool for the Strategic Outline and Sizing of District Heating Networks Using a Geographic Information System

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ENERGIES 2021年第17期14卷

作者： Resimont, Thibaut Louveaux, Quentin Dewallef, Pierre Univ Liege Dept Aerosp & Mech Engn B-4000 Liege Belgium Univ Liege Montefiore Inst B-4000 Liege Belgium

The implementation of district heating networks into cities is a main topic in policy planning that looks for sustainable solutions to reduce CO2 emissions. However, their development into cities is generally limited by a high initial investment cost. The development of optimization methods intended to draft efficient systems using heating consumption profiles into a prescribed geographic area are useful in this purpose. Such tools are already referred to in the scientific literature, yet they are often restricted to limit the computational load. To bridge this gap, the present contribution proposes a multi-period mixed integer linear programming model for the optimal outline and sizing of a district heating network maximizing the net cash flow based on a geographic information system. This methodology targets a large range of problem sizes from small-scale to large-scale heating networks while guaranteeing numerical robustness. For sake of simplicity, the developed model is first applied to a scaled down case study with 3 available heating sources and a neighborhood of 16 streets. The full-scale model is presented afterwards to demonstrate the applicability of the tool for city-scale heating networks with around 2000 streets to potentially connect within a reasonable computational time of around only one hour.

关键词： district heating energy integration heat storage mixed integer linear programming multi-period optimization

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Rolling horizon control architecture for distributed agents of thermostatically controlled loads enabling long-term grid-level ancillary services

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INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 2021年 127卷

作者： Radaideh, Ahraf Al-Quraan, Ayman Al-Masri, Hussein Albataineh, Zaid Yarmouk Univ Hijjawi Fac Engn Technol Elect Power Engn Dept Irbid Jordan Yarmouk Univ Hijjawi Fac Engn Technol Elect Engn Dept Irbid Jordan

This paper proposes novel modeling and control frameworks to evaluate the underlying capability of Thermostatically Controlled Loads (TCLs). The modeling architecture is based on distributed agents responsible for monitoring and controlling a small group of TCLs. Agents are mathematically formulated as a tracking problem in a mixed-integer linear programming format. Control actions are obtained by solving the agents sequentially in a rolling horizon control architecture. A step required to avoid the curse of dimensionality dictated by the number of devices and the duration of the planning horizon. The proposed architectures provide more practical evaluations in quantifying TCLs' capability. In essence, individual devices are described by distinct parameters and different operating conditions imitating real-life devices found in actual distribution systems. In contrast to aggregate models developed in the literature, this work inherently allows devices' heterogeneity, captures the outside temperature variations, and provides control access for both set-points and devices' status. In this paper, the scope of TCLs evaluation is providing long-term services such as load-shifting and sustained load-reductions. Simulation results have shown that 1000 heterogeneous TCLs represented by air-conditioners are able to achieve both services. However, consequences on customers' comfort are expected proportional to the extracted service. For instance, a sustained average power reduction of 319 KW causes an average set-point increase of 3.8 degrees F.

关键词： Thermostatically control loads Demand response Load management mixed integer linear programming Distributed control Rolling horizon Ancillary services

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Novel robotic job-shop scheduling models with deadlock and robot movement considerations

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TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW 2021年 149卷

作者： Sun, Yige Chung, Sai-Ho Wen, Xin Ma, Hoi-Lam Hong Kong Polytech Univ Dept Ind & Syst Engn Hung Hom Kowloon Hong Kong Peoples R China Hang Seng Univ Hong Kong Dept Supply Chain & Informat Management Shatin Hong Kong Peoples R China

The robotic job-shop scheduling problem (RJSP) has become increasingly important due to the wide application of robots for material delivery in modern logistics and supply chain systems. With the common assumptions of negligible material transportation procedures and infinite machine buffers, the traditional job-shop scheduling problem (JSP) models can lead to system failures due to the potential deadlock for a robot-driven production line. In this study, we propose two novel robotic job-shop scheduling models with deadlock and robot movement considerations (RJSPDT). The proposed novel models simultaneously consider the scheduling of job operations and the movement of the robot, with the objective of minimizing makespan. In order to avoid deadlock, the machine blocking strategy is applied and a set of tight deadlock-avoidance constraints is proposed. Two modelling approaches are applied: the traditional position-based approach and the novel network-based approach which is inspired by aviation scheduling studies. Through numerical examples, it is illustrated that our proposed models can completely avoid transportation conflicts by considering deadlock and robot movement. Besides, through computational experiments, the network-based RJSPDT shows higher solution efficiency owing to the smaller model size than the position-based RJSPDT (e.g., reducing the computational time by 96% for small-scale problems). Moreover, we explore the impacts of job settings (e.g., number of jobs, number of operations in a job) and job entrance strategies (i.e., fixed entrance and flexible entrance) on model performances. Results show that the number of jobs imposes greater impacts than the number of operations in a job, while the fixed entrance strategy can reduce the average computational time by 60% with little impact on the makespan.

关键词： Robot-driven production lines Job-shop scheduling Deadlock Machine blocking Robot movement mixed integer linear programming

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A novel strategy to restore power systems after a great blackout. The Argentinean case

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ENERGY STRATEGY REVIEWS 2021年 37卷

作者： Alvarez, Gonzalo E. Inst Desarrollo & Diseno Ave 3657 Santa Fe Santa Fe Argentina

This paper presents a multi-objective mathematical model to perform power restoration. It considers simultaneously the objective functions: restoration time, load shedding, and cost. New formulations are developed to improve the maneuverability of the system elements. This distinguishes the novel proposal from the rest of the one or two objective approaches. The linear nature of the formulation allows for obtaining feasible solutions within efficient times. The proposal includes in the main objective function the social view in terms of prioritize the restitution of the system for as many users as possible. It enables using this proposal to restore large scale systems. Results indicate that more equitable and faster restoration solutions can be obtained than the reported one in the mentioned case.

关键词： mixed integer linear programming Lexicographic optimization Load shedding Generating costs Electric power systems

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MILP formulation improvement with k-means clustering for the beam layout optimization in multibeam satellite systems

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COMPUTERS & INDUSTRIAL ENGINEERING 2021年 158卷

作者： Camino, Jean-Thomas Artigues, Christian Houssin, Laurent Mourgues, Stephane CNRS LAAS 7 Ave Colonel Roche F-31077 Toulouse France Airbus Def & Space Telecommun Syst Dept Space Syst 31 Rue Cosmonautes F-31402 Toulouse France

This paper addresses an NP-hard design optimization problem in a multibeam satellite communication system. This problem consists in designing irregular beam layouts to satisfy non-uniform user traffic demands over the satellite service area, under antenna constraints, satellite payload constraints and a telecommunication mission criterion. Efficiently solving this problem is of crucial importance due to its impact on the system performance and cost. We compare three mixed-integer linear programming formulations. The first one, issued from previous work, is based on a linearization of both convex and non-convex Euclidean distance constraints. The two other aim at reducing the solution space size and at breaking symmetry inherent to the first formulation. For that purpose, we introduce a new process to interface k-means clustering with mixed-integer linear programming. We examine an exact and a heuristic approach for exploiting these principles that yield two new formulations. The heuristic approach outperforms the others based on our tests on a set of large-scale realistic problem instances, allowing to use mixed-integer linear programming in the industrial context.

关键词： mixed integer linear programming Multibeam satellite systems design K-means clustering

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Peak load minimization in smart grid by optimal coordinated ON-OFF scheduling of air conditioning compressors

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SUSTAINABLE ENERGY GRIDS & NETWORKS 2021年 28卷

作者： Uddin, Md Forkan Hassan, K. M. Naimul Biswas, Soumav Bangladesh Univ Engn & Technol Dept Elect & Elect Engn Dhaka 1205 Bangladesh

We address the problem of minimizing the peak load by optimal coordinated ON-OFF scheduling of the compressors of air conditioners (ACs) connected in a smart grid. For this purpose, we consider a simplified model of power consumption profile, i.e., on-time and off-time durations and power consumption values of a split type AC. We model the necessary constraints and formulate an optimization problem to minimize the peak load by optimal coordinated ON-OFF scheduling of the AC compressors. The optimization problem is found to be a complex mixed integer linear programming problem. We optimally solve the problem for a small number of ACs by using an optimization tool. Unfortunately, due to the computational complexity, the tool cannot solve the problem for a large number of ACs. For a large number of ACs, we develop a heuristic algorithm to solve the problem. Using the optimization tool and the heuristic algorithm, we determine the peak load, load variance, and energy consumption in operating a number of ACs and compare them with the results obtained for a traditional non-coordinated AC operation. We find that both the optimal and heuristic solution approaches significantly reduce the peak load and load variance with some increment of energy consumption. Further, the computation time of the scheduling of the AC compressors of an air conditioning system under the heuristic algorithm is found to be significantly less compared to the time bound on scheduling computation of the AC compressors even when the number of ACs in the system is large. (C) 2021 Elsevier Ltd. All rights reserved.

关键词： Air conditioning system Dead-band temperature Smart grid Load scheduling Optimization mixed integer linear programming Heuristic algorithm Power consumption

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Adaptive neighborhood simulated annealing for sustainability-oriented single machine scheduling with deterioration effect

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APPLIED SOFT COMPUTING 2021年 110卷

作者： Salama, Mohamed Srinivas, Sharan Univ Missouri Coll Engn Dept Ind & Mfg Syst Engn Columbia MO 65211 USA Univ Missouri Trulaske Coll Business Dept Mkt Columbia MO 65211 USA Univ Missouri Inst Data Sci & Informat Columbia MO 65211 USA

This research considers the realistic phenomenon of cutting tool deterioration in the scheduling of jobs and tool replacement activities to ensure sustainable machining operations. Typically, each job has a basic processing time (independent of tool deterioration) and a tool age-dependent prolongation function. Nevertheless, such a strategy may replace the cutting tools before its useful lifespan to avoid longer processing time as it leads to higher energy consumption and likelihood of tardy jobs. Given the reduced tool operating duration, the prospect of exploiting its capability to limit the processing time prolongation is not considered by prior works. In this research, a single-machine scheduling approach that determines the job processing time based on tool age and operating duration (utilization) is studied. The problem is formulated as a mixed-integer linear program (MILP) with the objective of minimizing the weighted costs of energy consumption, tooling, and job tardiness. Due to its computational complexity, a new variant of simulated annealing (SA) algorithm is proposed to solve large instances, where an adaptive strategy is utilized to determine the neighborhood size for enhanced exploration and exploitation. Computational results for an exhaustive set of instances indicate the proposed scheduling strategy to always outperform the existing method, yielding up to a 43% reduction in total cost. Besides, the proposed variant of SA effectively solves the scheduling problem and consistently dominates the traditional SA method. (C) 2021 Elsevier B.V. All rights reserved.

关键词： Sustainable machine scheduling Simulated annealing mixed integer linear programming Deteriorating tool Tool-utilization-dependent processing times

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