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A Multi-Objective Optimization Approach to Risk-Constrained Energy and Reserve Procurement Using Demand Response

IEEE TRANSACTIONS ON POWER SYSTEMS 2018年第4期33卷 3940-3954页

作者： Paterakis, Nikolaos G. Gibescu, Madeleine Bakirtzis, Anastasios G. Catalao, Joao P. S. Eindhoven Univ Technol Dept Elect Engn NL-5600 MB Eindhoven Netherlands Aristotle Univ Thessaloniki Dept Elect & Comp Engn Thessaloniki 54124 Greece Univ Porto Inst Syst & Comp Engn P-4200465 Porto Portugal Univ Porto Fac Engn P-4200465 Porto Portugal Univ Beira Interior Ctr Mech & Aerosp Sci & Technol P-6201001 Covilha Portugal Univ Lisbon Inst Super Tecn Inst Engn Sistemas & Comp Invest & Desenvolviment P-1049001 Lisbon Portugal

The large-scale integration of wind generation in power systems increases the need for reserve procurement in order to accommodate its highly uncertain nature, a fact that may overshadow its environmental and economic benefits. For this reason, the design of reserve procurement mechanisms should be reconsidered in order to embed resources that are capable of providing reserve services in an economically optimal way. In this study, a joint energy and reserve day-ahead market structure based on two-stage stochastic programming is presented. The developed model incorporates explicitly the participation of demand side resources in the provision of load following reserves. Since a load that incurs a demand reduction may need to recover this energy in other periods, different types of load recovery requirements are modeled. Furthermore, in order to evaluate the risk associated with the decisions of the system operator and to assess the effect of procuring and compensating load reductions, the Conditional Value-at-Risk metric is employed. In order to solve the resulting multi-objective optimization problem, a new approach based on an improved variant of the epsilon-constraint method is adopted. This study demonstrates that the proposed approach to risk management presents conceptual advantages over the commonly used weighted sum method.

关键词： augmented epsilon-constraint method conditional value-at-risk day-aheadmarket demand side reserves load recovery risk management stochastic optimization wind power

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Sustainable and clean oilfield development: Optimal operation of wastewater treatment and recycling system

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JOURNAL OF CLEANER PRODUCTION 2020年 252卷 119819-119819页

作者： Zhou, Xingyuan Zhang, Haoran Long, Yin Song, Mengjie Qiu, Rui Yan, Yamin Yang, Xiaofan Liang, Yongtu China Univ Petr Natl Engn Lab Pipeline Safety Beijing Key Lab Urban Oil & Gas Distribut Technol Fuxue Rd 18 Beijing Peoples R China Univ Tokyo Ctr Spatial Informat Sci 5-1-5 Kashiwanoha Kashiwa Chiba 2778568 Japan Univ Tokyo Grad Sch Frontier Sci Dept Environm Syst 5-1-5 Kashiwanoha Kashiwa Chiba 2778563 Japan Univ Tokyo Grad Sch Frontier Sci Dept Human & Engn Environm Studies 5-1-5 Kashiwanoha Kashiwa Chiba 2778563 Japan CNPC Ltd Xinjiang Oilfield Branch 1 Oil Prod Plant Shengli Rd 43 Karamay City 834000 Xinjiang Peoples R China

With the increasing concerns over sustainable development and environmental protection, wastewater treatment and recycling, a crucial issue to address to ensure an oilfield's economic and clean production, is of great significance to achieve water pollution prevention and rational and scientific use of water resources. In this paper, aiming at the optimal operation of oilfield wastewater treatment and recycling system, a multi-objective mixed-integer linear programming model is proposed to ensure minimum costs and maximum amounts of recycled water. Various technical and operational constraints of wastewater treatment stations, waterflooding stations, and water allocation rooms are taken into consideration. For the safe and efficient operation of the system, the flowrate and energy balance equations of water delivery and waterflooding networks are also included. The augmented epsilon-constraint method is introduced to deal with the two conflicting objectives and generate the Pareto front. Lastly, taking a real-world wastewater treatment and recycling system in the Xinjiang Oilfield, China, as an example, the model's validity and applicability as well as analysis of the conflicting objectives trade-offs are demonstrated. Compared with manually developed plans, the model solution could not only lower the total costs but also improve the staff working efficiency and the correlation of sub-systems. With different levels of importance given to sustainable development and operational economy, a set of optimal operation schemes can also be provided for reference and decision-support. (C) 2020 Elsevier Ltd. All rights reserved.

关键词： Sustainable development Oilfield clean production Wastewater treatment and recycling Optimal operation augmented epsilon-constraint method Mixed-integer linear programming

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A ROBUST TIME-COST-QUALITY-ENERGY-ENVIRONMENT TRADE-OFF WITH RESOURCE-CONSTRAINED IN PROJECT MANAGEMENT: A CASE STUDY FOR A BRIDGE CONSTRUCTION PROJECT

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JOURNAL OF INDUSTRIAL AND MANAGEMENT OPTIMIZATION 2022年第1期18卷 375-396页

作者： Lotfi, Reza Yadegari, Zahra Hosseini, Seyed Hossein Khameneh, Amir Hossein Tirkolaee, Erfan Babaee Weber, Gerhard-Wilhelm Yazd Univ Dept Ind Engn Yazd Iran Islamic Azad Univ Sci & Res Branch Dept Ind Engn Tehran Iran Univ Tehran Dept Project & Construct Management Tehran Iran Tarbiat Modares Univ Dept Project Management & Construct Tehran Iran MAPNA Grp Oil & Gas Div Tehran Iran Mazandaran Univ Sci & Technol Dept Ind Engn Babol Iran Istinye Univ Dept Ind & Syst Engn Istanbul Turkey Poznan Univ Tech Fac Engn Management Poznan Poland Middle East Tech Univ Inst Appl Math Ankara Turkey

Sustainable development requires scheduling and implementation of projects by considering cost, environment, energy, and quality factors. Using a robust approach, this study investigates the time-cost-quality-energy environment problem in executing projects and practically indicates its implementation capability in the form of a case study of a bridge construction project in Tehran, Iran. This study aims to take into account the sustain ability pillars in scheduling projects and uncertainties in modeling them. To model the study problem, robust nonlinear programming (NLP) involving the objectives of cost, quality, energy, and pollution level is applied with resource constrained. According to the results, as time diminished, the cost, energy, and pollution initially decreased and then increased, witha reduction in quality. To make the model close to the real world by considering uncertainties, the cost and quality tangibly improved, and pollution and energy consumption declined. We applied the augmented epsilon-constraint method to solve the proposed model. According to the result of the research,with regard to the time-cost, time-quality, time-energy, and time-pollution charts, as uncertainty increases, the cost and quality will improve, and pollution and energy will decrease. The proposed model can be employed for all industrial projects, including roads, construction, and manufacturing.

关键词： Robust optimization Multi-objective optimization Time-Cost-Quality-Energy-Environment Trade-off augmented epsilon-constraint method

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A new optimization approach for nozzle selection and component allocation in multi-head beam-type SMD placement machines

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JOURNAL OF MANUFACTURING SYSTEMS 2013年第4期32卷 700-714页

作者： Torabi, S. A. Hamedi, M. Ashayeri, J. Univ Tehran Coll Engn Sch Ind Engn Tehran Iran Tilburg Univ Dept Econometr & Operat Res NL-5000 LE Tilburg Netherlands

This paper addresses a highly challenging scheduling problem faced in multi-head beam-type surface mounting devices (SMD) machines. An integrated mathematical model is formulated aiming to balance workloads over multiple heads as well as improving the traveling speed of the robotic arm by incorporating the appropriateness factors in the model to evaluate the compatibility of component-nozzle pairs. The proposed model is a bi-objective mixed integer nonlinear programming one, which is first converted into a linearized model and then directly solved by using the augmented epsilon constraint method for small problem instances. As the model is turned out to be NP-hard, we also develop a Multi-Objective Particle Swarm Optimization (MOPSO) algorithm to solve the model for medium and large-sized problem instances. The parameters of the proposed MOPSO are tuned by using the Taguchi method and corresponding numerical results are provided. (C) 2013 The Society of Manufacturing Engineers. Published by Elsevier Ltd. All rights reserved.

关键词： PCB assembly Multi-head beam-type SMD machine augmented epsilon-constraint method Particle Swarm Optimization Taguchi method

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Allocation of demand response resources: toward an effective contribution to power system voltage stability

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IET GENERATION TRANSMISSION & DISTRIBUTION 2016年第16期10卷 4169-4177页

作者： Aghaei, Jamshid Alizadeh, Mohammad Iman Abdollahi, Amir Barani, Mostafa Shiraz Univ Technol Dept Elect & Elect Engn Shiraz Iran Tarbiat Modares Univ Dept Elect & Comp Engn Tehran Iran Shahid Bahonar Univ Dept Elect Engn Kerman Iran

In this study, capacity allocation of demand-response (DR) and the real-time savings earned from implementing DR programmes (DRPs) are investigated based on a mixed integer non-linear multi-objective programming (MINMOP) framework according to two conflicting concepts, titled;maximum achievable potential (MAP) and realistic achievable potential (RAP). MAP indicates that placing a value on DR resources must be strictly weighed against the value of avoiding the acquisition of short-term resources to meet critical peak period, whereas RAP takes into accounts the amount of savings that might be achieved through DRPs. The proposed MINMOP includes both technical and economic aspects of integrating DRPs into the power systems by considering optimal generation scheduling cost, voltage drop, voltage stability margin, network loss, and incentive payment as objective functions. In addition, augmented -constraint method is applied to solve the proposed MINMOP by means of off-the-shelf conventional optimisation software. The IEEE 24-bus reliability test system (RTS 24-bus) is used to demonstrate the applicability of the proposed method. Eventually, DR allocation is analysed through four cases based on different number of candidate buses which demonstrate the interest and effectiveness of the proposed technique.

关键词： demand side management power system stability resource allocation integer programming nonlinear programming power system reliability DR resource allocation power system voltage stability demand-response capacity allocation DRPs DR programmes mixed integer nonlinear multiobjective programming framework MINMOP framework maximum achievable potential MAP realistic achievable potential RAP optimal generation scheduling cost voltage drop voltage stability margin network loss incentive payment augmented epsilon-constraint method off-the-shelf conventional optimisation software IEEE 24-bus reliability test system RTS 24-bus

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Multi objective stochastic microgrid scheduling incorporating dynamic voltage restorer

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INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 2017年第Dec.期93卷 316-327页

作者： Jirdehi, Mehdi Ahmadi Tabar, Vahid Sohrabi Hemmati, Reza Siano, Pierluigi Kermanshah Univ Technol Dept Elect Engn Kermanshah Iran Univ Salerno Dept Ind Engn Salerno Italy

This paper focus on optimal scheduling of microgrid including thermal and electrical loads, renewable energy sources (solar and wind), combined heat and power (CHP), conventional energy sources (boiler and micro turbine), energy storage systems (thermal and electrical storages), and series flexible alternating current transmission system (FACTS) devices. Dynamic Voltage Restorer (DVR) is included in the line between the main network and the microgrid in order to achieve a higher power transfer to the upstream grid. In the proposed method, wind speed, solar radiation, and loads are modelled as uncertain parameters based on a stochastic approach. The problem is modelled as a linear, mixed integer, constrained, and multi objective optimization one aiming at minimizing cost and pollution at the same time. Also, a sensitivity analysis is proposed for studying the sensitive parameters in microgrid management. The proposed multi objective and stochastic problem is solved by using the augmented epsilon-constraint method. All results and calculations are obtained by using GAMS24.1.3/CPLEX12.5.1. Finally, in order to confirm the results of the proposed method, final results are compared to the genetic algorithm method. Simulation results demonstrate the viability and effectiveness of the proposed scheduling method for microgrid. (C) 2017 Elsevier Ltd. All rights reserved.

关键词： augmented epsilon-constraint method Dynamic voltage restorer Microgrid programming Multi objective programming Stochastic programming

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Robust fuzzy and multi-objective optimization approaches to generate alternate solutions for resource conservation of eco-industrial park involving various future events

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PROCESS SAFETY AND ENVIRONMENTAL PROTECTION 2016年第PartB期103卷 424-441页

作者： Kolluri, Srinivas Sahan Esfahani, Iman Janghorban Yoo, ChangKyoo Kyung Hee Univ Dept Environm Sci & Engn Coll Engn Ctr Environm Studies Seocheon Dong 1 Yongin 446701 Gyeonggi Do South Korea

Eco-industrial parks (EIPs), typically including industrial plants and companies, provide a promising resource conservation strategy that includes opportunities for material exchange between participating plants and minimizes the consumption of resources. However, when the participating plants in the EIP fail to share data, various possible future events are ought to happen in future. In this paper, we present various robust optimization approaches in order to generate alternate solutions for resource conservation in EIPs through water reuse networks that take various future events into consideration. Three different optimization approaches are discussed and solved in this study. In the first optimization approach, the objective function is set to minimize the overall energy of the EIP. In the second approach, an emergy-based fuzzy optimization model is presented and the objective function of the model is to maximize the overall degree of satisfaction. Finally, a solution method incorporating the lexicographic optimization and augmented e-constraint method is proposed in order to solve the multi-objective optimization (MOO) problem, which simultaneously minimizes the overall freshwater consumption and the regenerated water flow-rate. The resulting model is formulated as a mixed-integer linear programming problem taking into consideration two scenarios (EIP reuse network with a regenerator and direct reuse EIP network without a regenerator). The applicability of the proposed optimization approaches is demonstrated by comparison with a literature case study and by comparing the optimal resource conservation results for the two scenarios. The results show that a regeneration unit with a fixed outlet concentration into the base system causes a 15.6%, 9.8%, 21.2%, and 16.2% reduction in the overall emergy, TAC, freshwater, and wastewater, respectively, in comparison to that of direct reuse. (C) 2016 Institution of Chemical Engineers. Published by Elsevier B.V. All rights

关键词： Eco-industrial parks (EIPs) Fuzzy optimization Multi-objective optimization Lexicographic optimization augmented epsilon-constraint method Water reuse

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Mixed integer programming of multi-objective security-constrained hydro/thermal unit commitment

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RENEWABLE & SUSTAINABLE ENERGY REVIEWS 2014年第Jan.期29卷 911-923页

作者： Norouzi, Mohammad Reza Ahmadi, Abdollah Nezhad, Ali Esmaeel Ghaedi, Amir Islamic Azad Univ Dept Elect Engn Lamerd Branch Lamerd Iran Islamic Azad Univ Dept Elect Engn Sci & Res Branch Fars *** Iran Islamic Azad Univ Dept Elect Engn Dariun Branch Shiraz Iran

This paper proposes a method for short term security-constrained unit commitment (SCUC) for hydro and thermal generation units. The SCUC problem is modeled as a multi-objective problem to concurrently minimize the ISO's cost as well as minimizing the emissions caused by thermal units. The non-linearity of valve loading effects is linearized in the presented problem. In order to model the SCUC problem more realistically, this paper considers the dynamic ramp rate of thermal units instead of the fixed rate. Moreover, multi-performance curves pertaining to hydro units are developed and the proposed SCUC problem includes the prohibited operating zones (POZs). Besides, the model of SCUC is transformed into mixed integer linear programming (MILP) instead of using mixed integer non-linear programming (MINLP) which has the capability to be solved efficiently using optimization software even for real size power systems. Pareto optimal solutions are generated by employing lexicographic optimization as well as hybrid augmented-weighted epsilon-constraint technique. Furthermore, a Fuzzy decision maker is utilized in this paper to determine the most preferred solution among Pareto optimal solutions derived through solving the proposed multi-objective SCUC problem. Eventually, the proposed model is implemented on modified IEEE 118-bus system comprising 54 thermal units and 8 hydro units. The simulation results reveal that the solutions obtained from the proposed technique in comparison with other methods established recently are superior in terms of total cost and emission output. (C) 2013 Elsevier Ltd. All rights reserved.

关键词： Security-constrained unit commitment Mixed integer linear programming Multi-objective optimization augmented epsilon-constraint method Hydro units

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Designing a sustainable supply chain for battery PVC cases: A multi-objective optimization approach

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COMPUTERS & INDUSTRIAL ENGINEERING 2024年 193卷

作者： Tajik, Mahmoud Tosarkani, Babak Mohamadpour Makui, Ahmad Rahmani, Donya Iran Univ Sci & Technol Sch Ind Engn Tehran Iran Univ British Columbia Sch Engn Okanagan Campus Kelowna BC V1V 1V7 Canada KN Toosi Univ Technol Dept Ind Engn Tehran Iran

Nowadays, Polyvinyl Chloride (PVC) and its derivatives are being used in a wide range of products, including car battery cases, due to their corrosion resistance and exceptional durability. As PVC production has grown, the amount of non-hazardous waste generated from PVC products has dramatically increased. In this context, incorporating PVC waste management into the PVC supply chain can effectively address the PVC waste generation issue. This study investigates the design of the Polyvinyl Chloride Closed-Loop Supply Chain (PVCCLSC) based on a triple-objective model for Abadan Petrochemical Company. The first objective aims to minimize the total cost of PVCCLSC, the second objective focuses on minimizing environmental impact, and the third objective maximizes the improvement of Occupational Health and Safety (OHS). In this study, an integrated solution approach is developed encompassing four main phases: (i) Developing an accelerated K-means clustering algorithm, along with the Elbow method (EM) and Average Silhouette method (ASM), to estimate the quality of returned PVC products, (ii) Employing a robust optimization method to capture the uncertainty, (iii) Implementing an augmented epsilon-constraint method to solve the proposed multi-objective model, and (iv) Applying a Bender's Decomposition Algorithm (BDA) to solve the model and determine optimal solutions. As a result of the proposed BDA, relative optimality gaps have been reduced from 4.56 % in the conventional solution to zeros, and runtime has been reduced from 55 min to 20 min. Furthermore, as a result of this study, more than 44 % of returned PVC products should be recycled using the tertiary method to fulfill environmental requirements.

关键词： Sustainable polyvinyl chloride supply chain Uncertainty Accelerated K-means clustering algorithm Scenario-based robust optimization model augmented epsilon-constraint method

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Developing an integrated model for planning the delivery of construction materials to post-disaster reconstruction projects

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JOURNAL OF COMPUTATIONAL DESIGN AND ENGINEERING 2022年第3期9卷 1135-1156页

作者： Gharib, Zahra Yazdani, Maziar Bozorgi-Amiri, Ali Tavakkoli-Moghaddam, Reza Taghipourian, Mohammad Javad Univ Tehran Coll Engn Sch Ind Engn Tehran *** Iran Univ New South Wales Sch Civil & Environm Engn Sydney NSW 2052 Australia Islamic Azad Univ Dept Business Management Chalous Branch Chalous 46615397 Iran

Construction material delivery to post-disaster reconstruction projects is challenging because of the resource and time limitations that follow a large-scale disaster. There is compelling evidence that inadequate planning jeopardises the success of a large number of post-disaster reconstruction projects. Thus, the current study proposes an integrated approach to facilitate the procurement planning of construction materials following a large-scale disaster. The proposed approach clustered the location of construction projects using a differential evolution (DE)-K-prototypes, a new partitional clustering algorithm based on DE and K-prototypes, method. Then, using a permanent matrix prioritises cluster points based on route reliability-affecting factors. The model's objectives are to minimise the total travel time, maximise the reliability of the route, and minimise the total weighted undelivered materials to projects. In the case of distribution of material through land vehicles, the possibility of breakdowns in the vehicle is considered, allowing for the determination of vehicle breakdown under various scenarios and the minimisation of undelivered materials to projects. As a result of the uncertain character of the disaster, the demands of construction projects are fuzzy, and Jimenez's method is used to handle it. Due to the complexity of the problem, two algorithms are proposed, a multi-objective evolutionary algorithm based on decomposition (MOEA/D) and a non-dominated sorting genetic algorithm-II (NSGA-II). The results confirm that the proposed MOEA/D has a higher accuracy while NSGA-II has a shorter computational time. By providing new theoretical perspectives on disaster recovery strategies in the construction sector, this study contributes to the growing body of knowledge about disaster recovery strategies in the sector. The findings of this study can be employed to develop an integrated planning system for the delivery of construction materials to post-disaste

关键词： post-disaster reconstruction non-dominated sorting genetic algorithm-II post disaster construction material multi-objective evolutionary algorithm based on decomposition augmented epsilon-constraint method

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