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Adapting water tariffs to climate change: Linking resource availability, costs, demand, and tariff design flexibility

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JOURNAL OF CLEANER PRODUCTION 2021年 290卷 125803-125803页

作者： Silva Pinto, F. de Carvalho, B. Cunha Marques, R. Univ Lisbon Inst Super Tecn CESUR CERIS Av Rovisco Pais 1 P-1049001 Lisbon Portugal

Utilities face challenges that may cause net damage costs able to defy our society and environment. An ever more frequent impact is water resource scarcity due to an increasingly uncertain climate, over-exploitation and contamination of resources, as well as lack of infrastructure. Thus, in the water supply sector, the robustness and resilience of systems depends on 'preparedness' measures able to establish a link between resources availability, utility costs, water tariffs (or other sources of revenue) and demand. In this study, the interplay regarding the instability of environmental phenomena, water supply and demand management is established to model tariffs in a novel flexible framework. The social, economic and environmental impacts are assessed related to costs, demand, and water resources availability. The Sao Paulo metropolitan area (Brazil) case-study is assessed, particularly the Cantareira reservoir system. Water supply tariffs and operational adjustments are proposed on an 'ex-ante time frame'. By providing a rationale to price changes related to resource variability (e.g., scarcity-related) the often reliance on heuristics or simplified decision-making models is avoided. The results achieved highlight that water supply tariffs can be planned according to climatic and hydrologic information, utility costs, water demand, rational and flexible tariff design, to avoid unnecessary constraints on utilities, allowing to defer investment requirements. Benefits accrued to customers are: reductions from 10% to 44% in lower consumption levels (usually connected to high-value uses) and, when in resource scarcity situations, increases in higher consumption blocks from 3% to 106%. (C) 2021 Elsevier Ltd. All rights reserved.

关键词： Water tariffs Climate change Impact assessment mixed integer linear programming Water supply system Water resources

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Oilfield development system optimization under reservoir production uncertainty

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OCEAN ENGINEERING 2021年 225卷 108758-108758页

作者： Silva, L. M. R. Soares, C. Guedes Univ Lisbon Ctr Marine Technol & Ocean Engn CENTEC Inst Super Tecn Av Rovisco Pais P-1049001 Lisbon Portugal

An optimization approach is proposed to support the design decisions of floating production systems and their subsea layout, regarding the production and investment planning. The optimization methodology extends a previous approach by including the dynamics and uncertainty of the oil production during the reservoir lifetime, and the associated dynamics of the gas and water production. The new model integrates production forecast with facilities requirements and economic optimization. An uncertainty assessment methodology is provided and applied to the reservoir production including its decline curve. A case study from Brazil waters is presented and discussed to demonstrate the performance of the method applied to a specific production system.

关键词： Production system optimization Production uncertainty modelling Offshore oilfield development mixed integer linear programming Optimization model

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Case Study of Multi-Period MILP HENS with Heat Pump and Storage Options for the Application in Energy Intensive Industries

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ENERGIES 2021年第20期14卷 6741页

作者： Prendl, Leopold Hofmann, Rene TU Wien Inst Energy Syst & Thermodynam Getreidemarkt 9-BA A-1060 Vienna Austria

The environmental goals of initiatives such as the European Green Deal, which aims to achieve climate neutrality for the EU by 2050, increase the importance of improving and optimizing industrial processes. Mathematical optimization methods like heat exchange network synthesis (HENS) are crucial tools in enabling industry to identify potential energy savings and cost reductions. The lack of publicly available industry data suitable for comprehensive testing of novel optimization procedures is often a major obstacle in development and research. To tackle this problem for extended HENS with potential heat pump and storage integration and show the potential of energy integration in energy-intensive industries (EII), the authors introduce a set of four use-cases based on representative industrial processes from the EII. The application of a previously presented a HENS approach for the integration of heat pumps and storage on these cases resulted in a potential reduction of total annual costs up to 55.43% and total external energy demand up to 87.1%. The presented cases, their solutions, and the open-access mathematical formulation of the optimization procedure make a valuable contribution to the literature and future research in the field of HENS.

关键词： mixed integer linear programming heat recovery heat pump thermal energy storage design optimization case study

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Retail order picking scheduling with missing operations and limited buffer 21st

Retail order picking scheduling with missing operations and ...

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21st IFAC World Congress on Automatic Control - Meeting Societal Challenges

作者： Souiden, Sawssen Cerqueus, Audrey Delorme, Xavier Rascle, Jean-Lucien Univ Clermont Auvergne Mines St Etienne CNRS UMR LIMOS 6158Inst Henri Fayol F-42023 St Etienne France Boa Concept SAS F-42000 St Etienne France

Order picking is one of the most critical activities in the warehousing process. In order to obtain high profits, e-commerce retailers have focused on dedicated and accurate order picking methods. Zone picking is a picking approach commonly used for retail order picking where small-sized items have to be collected. Nevertheless, to become more efficient, it requires a scheduling policy for managing the bins flow which avoids blocking and mitigates order pickers unproductive times. This paper studies a specific variant of the Non-Permutation Flow-Shop (NPFS) scheduling problem with missing operations, transportation times and limited capacity constraints. A mathematical formulation of this new problem is proposed to minimize the total elapsed time for all machines. We study an illustrative example to analyze the differences between the optimal solution of the proposed model and a naive solution. Copyright (C) 2020 The Authors.

关键词： Order picking Scheduling Non-Permutation Flow-Shop Missing operations Limited buffer capacity mixed integer linear programming

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Framework for Modeling and Optimization of On-Orbit Servicing Operations Under Demand Uncertainties

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JOURNAL OF SPACECRAFT AND ROCKETS 2021年第4期58卷 1157-1173页

作者： du Jonchay, Tristan Sarton Chen, Hao Gunasekara, Onalli Ho, Koki Georgia Inst Technol Daniel Guggenheim Sch Aerosp Engn Atlanta GA 30332 USA

This paper develops a framework that models and optimizes the operations of complex on-orbit servicing infrastructures involving one or more servicers and orbital depots to provide multiple types of services to a fleet of geostationary satellites. The proposed method extends the state-of-the-art space logistics technique by addressing the unique challenges in on-orbit servicing applications and integrates it with the Rolling Horizon decision-making approach. The space logistics technique enables modeling of the on-orbit servicing logistical operations as a mixed-integer linear Program whose optimal solutions can efficiently be found. The Rolling Horizon approach enables the assessment of the long-term value of an on-orbit servicing infrastructure by accounting for the uncertain service needs that arise over time among the geostationary satellites. Two case studies successfully demonstrate the effectiveness of the framework for 1) short-term operational scheduling and 2) long-term strategic decision making for on-orbit servicing architectures under diverse market conditions.

关键词： Geostationary Satellites Space Logistics Models mixed integer linear programming Bipropellants Manufacturing Cost Hohmann Transfer Earth Logistics Network Monopropellants Satellite Services

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Minimizing makespan and flowtime in a parallel multi-stage cellular manufacturing company

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ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING 2021年 72卷 102182-102182页

作者： Saracoglu, Ilkay Suer, Gursel A. Gannon, Patrick Istanbul Atlas Univ Dept Ind Engn Istanbul Turkey Ohio Univ Dept Ind & Syst Engn Athens OH 45701 USA

This study proposes a 3-phase solution approach for a multi-product parallel multi-stage cellular manufacturing company. The study focuses on a case study involving a shoe manufacturing plant in which products are produced according to their due dates. The investigated manufacturing process has three stages, namely lasting cells, rotary injection molding cells, finishing-packaging cells. System performance is measured based on total flowtime and makespan. We propose a 3-phase solution approach to tackle the problem;1) the first phase of the proposed approach allocates manpower to operations in the lasting cells and finishing-packaging cells, independently. The objective is to maximize the production rates in these cells. 2) The second phase includes cell loading to determine product families based on a similarity coefficient using mathematical modeling and genetic algorithms (GA). The proposed GA algorithm for cell loading performs mutation prior to crossover, breaking from traditional genetic algorithm flow. The performance measures flow time and makespan are considered in this phase. 3) Flow shop scheduling is then performed to determine the product sequence in each (lasting, rotary injection molding, finishing-packaging) cell group. This 3-phase solution approached is repeated with alternative manpower level allocation to lasting and finishing-packaging cells where the total manpower level remains the same.

关键词： Flow shop scheduling Genetic algorithm mixed integer linear programming Cell loading Cellular manufacturing

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Modeling and scheduling of residential electric loads for energyself-sufficiency

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INTERNATIONAL JOURNAL OF NUMERICAL MODELLING-ELECTRONIC NETWORKS DEVICES AND FIELDS 2021年第1期34卷

作者： Narayanankutty, Ravishankar Achathuparambil Sankar, Ashok Sundaramoorthy, Kumaravel Natl Inst Technol Calicut Dept Elect Engn Kozhikode 673601 Kerala India

The utility company enforces a limit on the amount of energy injected into the utility grid from residential renewable plants due to the stability/protection concerns caused by the reverse power flow. Under this scenario, a proper load scheduling at the consumer end is necessary to ensure maximum renewable energy utilization during the surplus generation. This article proposes a novel objective function to impart energy self-sufficiency for residential consumers who own electric vehicles and renewable energy power plants. The proposed objective function aims to promote the consumers to utilize the local sources such as the battery of an electric vehicle, solar PV, wind, etc., effectively through load scheduling. A dedicated program inMATLABplatform is developed for load scheduling, and an experimental case study is conducted using the forecasted demand and generation profiles collected from 10 typical residential consumers. Three new techno-economic parameters namely, aggregate daily exchanged energy, daily average discharged energy, and daily average self-sufficiency hours are proposed to conduct the comparative study. An Average Rank ranking method is introduced to evaluate the effectiveness of the proposed and conventional objective functions statistically. The result analysis proves that load scheduling using the proposed objective function secure the best Average Rank of 2.02 compared to the conventional objective functions.

关键词： Average Rank ranking electric vehicles mixed integer linear programming numerical modeling residential energy management

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Robust Scheduling for Pumping in a Water Distribution System under the Uncertainty of Activating Regulation Reserves

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ENERGIES 2021年第2期14卷 302页

作者： Negishi, Shintaro Ikegami, Takashi Tokyo Univ Agr & Technol Grad Sch Bioapplicat & Syst Engn 2-24-16 Naka Cho Koganei Tokyo 1848588 Japan Tokyo Univ Agr & Technol Inst Engn 2-24-16 Naka Cho Koganei Tokyo 1848588 Japan

A new robust scheduling method for pumping water in a water distribution system under the uncertainty of activating regulation reserves is proposed in this paper. During the operation of power systems, utilizing the energy equipment of the customer to enhance supply-demand control is attracting attention. Because water pumps have been already installed, they can be regarded as a relatively inexpensive, operational, and flexible resource. Changes in the operation of the water pump can contribute to the power supply and demand control. The proposed method helps generate a robust daily schedule for pumping water and provides regulation reserves under the uncertainty of activating regulation reserves. It is based on electric energy prices and regulation reserves, hourly water demand profiles, and the properties of water flow quantity and the electricity consumption of water pumps. This method comprises an optimization model formulated using mixed integer linear programming, validated through simulations of water pumping scheduling under certain scenarios. The results indicate that the net operational cost decreased when water pumps provided regulation reserves;further, the operational feasibility of providing these reserves from water pumps is clarified. The proposed model makes it possible to optimize power system operation that integrates the water supply system.

关键词： water pumps regulation reserves robust optimization mixed integer linear programming

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Effects of resilience-oriented design on distribution networks operation planning

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ELECTRIC POWER SYSTEMS RESEARCH 2021年 191卷 106902-106902页

作者： Shahbazi, Amid Aghaei, Jamshid Pirouzi, Sasan Niknam, Taher Shafie-khah, Miadreza Catalao, Joao P. S. Shiraz Univ Technol Dept Elect & Elect Engn Shiraz Iran Islamic Azad Univ Semirom Branch Power Syst Grp Semirom Iran Univ Vaasa Sch Technol & Innovat Vaasa 65200 Finland Univ Porto Fac Engn P-4200465 Porto Portugal INESC TEC P-4200465 Porto Portugal

This paper presents an optimal framework for the resilience-oriented design (ROD) in distribution networks to protect these grids against extreme weather events such as earthquakes and floods. This strategy minimizes the summation of daily investment and repair costs of back up distributed generation (DG), hardening and tie lines, operation cost of network and DGs, and load shedding cost. Also, it considers AC power flow equations, system operation limits and planning and reconfiguration constraints. This problem is generally a mixed integer nonlinear programming (MINLP) problem, but it is converted to a mixed integer linear programming (MILP) problem to achieve a globally optimal solution with a low computation time. Moreover, the Benders decomposition (BD) approach is used for the proposed problem to obtain higher computation speed in large scale networks. In addition, this problem includes uncertain parameters such as load, energy price, and availability of network equipment in the case of extreme weather conditions. Hence, a scenario-based stochastic programming (SBSP) approach is used to model these uncertain parameters in the proposed ROD method, based on a hybrid approach, including roulette wheel mechanism (RWM) and the simultaneous backward method. The proposed problem is simulated on 33-bus and large-scale 119-bus distribution networks to prove its capabilities in different case studies.

关键词： Distributed generation Natural disasters mixed integer linear programming Resilience Stochastic programming

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An integrated heuristic and mathematical modelling method to optimize vehicle maintenance schedule under single dead-end track parking and service level agreement

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COMPUTERS & OPERATIONS RESEARCH 2021年 132卷 105261-105261页

作者： Elhuseyni, Murat Unal, Ali Tamer Bogazici Univ Dept Ind Engn TR-34342 Istanbul Turkey Uskudar Univ Dept Ind Engn Istanbul Turkey

Inspired by real life maintenance operations, we introduce a vehicle maintenance scheduling problem in an urban light rail line which considers service level agreement (SLA), preventive maintenance cycles and corrective jobs on a single dead-end track. We show that the problem is strongly NP-Hard. Experts in real life make use of a heuristic. Yet, the heuristic calls vehicles in their preventive maintenance cycles as early as possible, which increases the number of maintenance calls in the long term. We build a mixed integer linear programming (MILP) model that handles all aspects of this problem. To improve the quality of the model, we modify it based on the structure of the problem and call MILP2. We enhance the heuristic and name ImprHeur. We introduce ImprHeur to provide a starting solution for the MILP2 model and call ImprHeur + MILP2. We perform computational experiments on random test instances and show that the ImprHeur + MILP2 drastically heightens the solution quality of the MILP model. We define key performance indicators (KPI) to assess the system behavior. We create a discrete-event simulation framework for different problem parameters to test the performance of these heuristics and ImprHeur + MILP2. We conclude that ImprHeur + MILP2 improves the real life heuristic by 74.72% with regard to the objective function value of the MILP model.

关键词： Vehicle maintenance scheduling Heuristic mixed integer linear programming Service level agreement Dead-end track parking

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