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Multi-objective energy procurement strategy of electricity retail companies based on normalized normal constraint methodology

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INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 2022年 135卷 107281-107281页

作者： Khojasteh, Meysam Polytech Porto Inst Engn Rua DR Antonio Bernardino Almeida 431 P-4200072 Porto Portugal

The electricity retail market provides a marketplace for domestic consumers and retailers to buy and sell electricity in a competitive environment. Permitting final consumers to choose electricity retailers promotes suppliers' pluralism and clients' freedom, which leads to improvements in the quality of electricity retailing service. The main aim of a retailer and consumers is profit maximization, which highly depends on retail-selling price. Retailer's profit may be explicitly reduced by decreasing retail selling-price or implicitly reduced by increasing retail selling-price as increasing these prices may decrease clients' consumption. Accordingly, the retail sellingprice, retailer energy procurement strategy, and clients' consumption should be simultaneously analyzed from the viewpoints of retailer and clients. In this paper, a multi-objective optimization problem is introduced to obtain the retailer's energy procurement strategy in terms of the profits of energy buyers and sellers. Moreover, the normalized normal constraint method as a proficient multi-objective optimization technique is utilized to solve the proposed multi-objective optimization problem determining the retailers' energy procurement strategy and retail selling-prices. Since the wholesale energy price is a highly volatile uncertainty source affecting the retailer's profit, the point estimate method is utilized to characterize the uncertainty of the wholesale energy price. Simulation results illustrate the effectiveness of the proposed non-deterministic multi-objective optimization problem.

关键词： Energy procurement Multi-objective normalized normal constraint method Point estimate method Retailer

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Optimal design of an autothermal membrane reactor coupling the dehydrogenation of ethylbenzene to styrene with the hydrogenation of nitrobenzene to aniline

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CHEMICAL ENGINEERING SCIENCE 2010年第10期65卷 3113-3127页

作者： Abo-Ghander, Nabeel S. Logist, Filip Grace, John R. Van Impe, Jan F. M. Elnashaie, Said S. E. H. Lim, C. Jim Univ British Columbia Chem & Biochem Engn Dept Vancouver BC V6T 1Z3 Canada Katholieke Univ Leuven Dept Chem Engn BioTeC B-3001 Louvain Belgium MUST Coll Engn Sixth Of October City Egypt

Coupling the dehydrogenation of ethylbenzene to styrene with the hydrogenation of nitrobenzene to aniline in a catalytic fixed bed membrane reactor has the potential for significantly improving both processes (Abo-Ghander et al., 2008. Modeling of a novel membrane reactor to integrate dehydrogenation of ethylbenzene to styrene with hydrogenation of nitrobenzene to aniline. Chemical Engineering Science, 63 (7), 1817-1826). In a continuing effort to realize this potential, an optimal design is sought for a co-current coupled flow, catalytic membrane reactor configuration. To achieve this objective, two conflicting objective functions, namely: the yield of styrene on the dehydrogenation side and the conversion of nitrobenzene on the hydrogenation side, are considered. The total number of the decision variables considered in the optimization problem is 12, representing a set of operating and dimensional parameters. The problem is solved numerically by two deterministic multi-objective optimization approaches: the normalized normal constraint method and the normal boundary intersection method. It was found that the integrated reactor system can be operated to produce a maximum styrene yield of 97% when production of styrene is emphasized and, on the other hand, up to 80% of nitrobenzene conversion when nitrobenzene conversion is concentrated on. The resulting sets of Pareto optimal solutions obtained by both techniques are shown to be identical. Qualitative explanations are provided for the effect of the decision variables on both objectives. (C) 2010 Elsevier Ltd. All rights reserved.

关键词： Membrane fixed-bed reactor Bi-objective optimization normalized normal constraint method normal boundary intersection method Optimal design Coupled reactions

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A metamodel-based multicriteria shape optimization process for an aerosol can

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ALEXANDRIA ENGINEERING JOURNAL 2018年第3期57卷 1905-1915页

作者： Benki, Aalae Habbal, Abderrahmane Mathis, Gael INRIA Sophia Antipolis OPALE Project Team 2004 Route Lucioles F-06902 Sophia Antipolis France Univ Nice Sophia Antipolis Math Dept 28 Ave Valrose F-06103 Nice 2 France ArcelorMittal Global R&D Route St Leu F-60761 Montataire France

In this paper, we study a multicriteria shape design of a highly nonlinear mechanical 2D structure, namely the shape optimization of the aerosol can bottom. In fact, it is made depending on two criteria, the dome growth DG and the dome reversal pressure DRP, that define the resistance of the bottom against the internal pressure. This two criteria are known to be conflicting;therefore, a multicriteria optimization problem is formulated to represent the trade-offs among the design parameters. Due to the expensive time-consuming cost to solve this kind of optimization problems (e.g., capturing the Pareto front), the use of a surrogate model (e.g., metamodel) cheap to evaluate is mandatory. For this reason, we have developed an algorithm which is a coupling between the normalized normal constraint method (NNCM) and the radial basis function metamodel (RBF). The NNCM-RBF coupling was tested for several academic test cases and for our industrial problem and the obtained results clearly show the efficiency of our coupling to solve all the problems treated with a remarkable gain in the computational time. (C) 2017 Faculty of Engineering, Alexandria University. Production and hosting by Elsevier B.V.

关键词： Aerosol can Multicriteria shape optimization normalized normal constraint method Radial basis function metamodel

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Bi-level optimization of novel distribution network with VPP and flexible load cluster

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ENERGY REPORTS 2024年 12卷 504-516页

作者： Li, Yuhao Yang, Xiaohui Deng, Fuwei Deng, Yeheng Wang, Xiaopeng Zhang, Zhonglian Nanchang Univ Sch Informat Engn Nanchang Peoples R China

To satisfy the power requirements of modern industrial parks, while also enhancing energy efficiency and system economy, a bi-level optimization model is proposed for a novel distribution network, which incorporates a virtual power plant (VPP) and flexible load cluster. The proposed optimization model for the distribution network layer considers factors such as minimum voltage offset and operating cost. It accounts for uncertainties associated with new energy sources, control of the soft open point (SOP), as well as dispatching of the static var compensator (SVC). A normalized normal constraint (NNC) method is used to obtain Pareto front. The power flow model is converted into a normalized cone programming model utilizing second-order cone relaxation technique. The VPP optimization layer aims to achieve the lowest operational cost and comprehensively considers the complementarity of multiple types of distributed energy resources. The bi-level iterative solution is obtained using the analytical target cascading (ATC) method. Finally, the enhanced IEEE 33-node system example demonstrates that the proposed bi-level optimization model effectively reduces the system's operating cost, optimizes the power flow distribution, and minimizes network losses.

关键词： normalized normal constraint method Virtual power plant Flexible load cluster Analytical target cascading method

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Multi-objective robust design of helical milling hole quality on AISI H13 hardened steel by normalized normal constraint coupled with robust parameter design

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APPLIED SOFT COMPUTING 2019年 75卷 652-685页

作者： Dutra Pereira, Robson Bruno da Silva, Laila Alves Lauro, Carlos Henrique Brandao, Lincoln Cardoso Ferreira, Joao Roberto Davim, J. Paulo Fed Univ Sao Joao del Rei UFSJ Dept Mech Engn Ind Engn 170 Frei Orlando Sq BR-36880000 Sao Joao Del Rei MG Brazil Fed Univ Itajuba UNIFEI Inst Ind Engn & Management 1303 BPS Ave BR-37500903 Itajuba MG Brazil Univ Aveiro Dept Mech Engn Campus Santiago P-3810193 Aveiro Portugal

Helical milling is a hole-making process which has been applied in hardened materials. Due to the difficulties on achieving high-quality boreholes in these materials, the influence of noise factors, and multi-quality performance outcomes, this work aims the multi-objective robust design of hole quality on AISI H13 hardened steel. Experiments were carried out through a central composite design considering process and noise factors. The process factors were the axial and tangential feed per tooth of the helix, and the cutting velocity. The noise factors considered were the tool overhang length, the material hardness and the borehole height of measurement. Response models were obtained through response surface methodology for roughness and roundness outcomes. The models presented good explanation of data variability and good prediction capability. Mean and variance models were derived through robust parameter design for all responses. Similarity analysis through cluster analysis was performed, and average surface roughness and total roundness were selected to multi-objective optimization. Mean square error optimization was performed to achieve bias and variance minimization. Multi-objective optimization through normalized normal constraint was performed to achieve a robust Pareto set for the hole quality outcomes. The normalized normal constraint optimization results outperformed the results of other methods in terms of evenness of the Pareto solutions and number of Pareto optimal solutions. The most compromise solution was selected considering the lowest Euclidian distance to the utopia point in the normalized space. Individual and moving range control charts were used to confirm the robustness achievement with regard to noise factors in the most compromise Pareto optimal solution. The methodology applied for robust modelling and optimization of helical milling of AISI H13 hardened steel was confirmed and may be applied to other manufacturing processes. (C) 2018 Elsev

关键词： Helical milling AISI H13 hardened steel Multi-objective robust optimization Robust parameter design normalized normal constraint method

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Multiobjective Optimal Dispatch of Mobile Energy Storage Vehicles in Active Distribution Networks

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IEEE SYSTEMS JOURNAL 2023年第1期17卷 804-815页

作者： Liu, Jie Lin, Shunjiang He, Sen Liu, Wanbin Liu, Mingbo South China Univ Technol Sch Elect Power Engn Guangzhou 510640 Peoples R China South China Univ Technol Sch Elect Power Engn Guangzhou Peoples R China Maintenance & Test Ctr EHV Power TransmissionCompa China Southern Power Grid Guangzhou 510663 Peoples R China

In active distribution networks (ADNs), mobile energy storage vehicles (MESVs) can not only reduce power losses, shave peak loads, and accommodate renewable energy but also connect to any mobile energy storage station bus for operation, making them more flexible than energy storage stations. In this article, a multiobjective optimal MESV dispatch model is established to minimize the power loss, renewable energy source curtailment, and total operating cost of ADNs. Additionally, a method to directly obtain the compromise optimal solution (COS) of the Pareto optimal solutions (POSs) of a three-objective optimization problem is proposed. Based on the normalized normal constraint (NNC) method for solving the POSs of a three-objective optimization problem, a bilevel optimization model is established to directly obtain the COS. The innerlayer model uses the NNC method to calculate the POS corresponding to a point on the Utopia plane, and the outerlayer model uses the improved Nelder-Mead (INM) method to directly search the POS with the minimum distance to the Utopia point as the COS. Compared with the traditional method, which first solves the POSs of the three-objective optimization problem and then selects the COS, the proposed INM method has higher computational efficiency and obtains a better COS. Finally, case studies on the modified IEEE-33 bus distribution network and an actual 180 bus distribution network demonstrate the effectiveness of the proposed method.

关键词： Index Terms-Active distribution networks improved Nelder-Mead method mobile energy storage vehicles multiobjective optimal dispatch normalized normal constraint method

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Sustainable supply chain network design: A case of the glass manufacturer in Asia

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INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS 2022年 248卷

作者： Naeeni, Hannan Sadjady Sabbaghi, Navid Longwood Univ Coll Business & Econ 201 High St Farmville VA 23909 USA St Marys Coll Calif Sch Econ Business Adm 1928 St Marys Rd Moraga CA 94575 USA

Traditionally, profit maximization was the major objective for many businesses. However, due to growing stakeholders' pressure and awareness about the social and environmental impacts of supply chain activities, many companies are now focused on optimizing their profits, while reducing negative impacts of their activities on planet and society. While sustainable development requires concurrent and balanced consideration of social, environmental and economic dimensions, unbalanced approaches have been adopted both in real world practices, and in academic literature. We contribute to the stream of research in the literature that tries to address this gap. We propose a multi-objective mixed-integer programming (MOMIP) model for sustainable supply chain network design (SSCND), encompassing economic, environmental, and social objectives. Both strategic and tactical network design decision variables are considered, including location, size, and technology type of facilities, along with determining the flow of materials and transportation modes. The normalized normal constraint method is applied to generate evenly distributed Pareto frontiers. The case of a glass manufacturing company in Asia is used to demonstrate applicability of the model and solution procedure to real-world problems. Non-dominated solutions are analyzed, and a more sustainable and balanced network design alternative is proposed, which outperforms the current network configuration in terms of all three dimensions of sustainability. Managerial implications and future research directions are discussed.

关键词： Supply chain network design Sustainability Multi-objective optimization Mixed-integer programming normalized normal constraint method

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A Solution method for Many-Objective Security-Constrained Unit Commitment Considering Flexibility

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FRONTIERS IN ENERGY RESEARCH 2022年 10卷

作者： Lin, Shunjiang Wu, Hui Liu, Jie Liu, Wanbin Liu, Yanghua Liu, Mingbo South China Univ Technol Sch Elect Power Engn Guangzhou Peoples R China Guangdong Polytech Normal Univ Sch Electromech Engn Guangzhou Peoples R China

With the increasing penetration of wind power into power systems and the random fluctuation of the wind farm (WF) output, system flexibility must be considered in the optimal generation dispatch. Based on the extreme scenarios of the WF output, we proposed a flexibility risk index to evaluate the system flexibility of each time interval. We established a five-objective security-constrained unit commitment (SCUC) model of a power system with WFs, thermal generation plants, battery energy storage stations, and pumped storage hydro stations. The objectives were to minimize the system flexibility risk, total network loss, operation cost, power purchase cost, and pollutant gas emissions. To obtain the Pareto optimal solutions of the model, based on the objective selection and epsilon-constraint methods, we proposed two methods to reduce the dimension of objectives and transformed the five-objective optimization model into a series of three-objective optimization models. Then, we used the normalized normal constraint method to solve the Pareto frontier surface of each three-objective optimization model. We used a color column to represent the value change of the two upper layer objectives and visualized the Pareto frontier of the five-objective SCUC model in the three-dimensional ordinate space. Case studies on the modified IEEE-9 bus system and an actual power grid demonstrated the effectiveness and high computational efficiency of the proposed method.

关键词： flexibility many-objective optimization mixed integer convex programming normalized normal constraint method security-constrained unit commitment epsilon-constraint method

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