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Bi-Level multi-objective Optimization Scheduling for Regional Integrated Energy Systems Based on Quantum Evolutionary Algorithm

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ENERGIES 2021年第16期14卷 4740页

作者： Fan, Wen Liu, Qing Wang, Mingyu North China Elect Power Univ Baoding State Key Lab Alternate Elect Power Syst Renewabl Baoding 071003 Peoples R China

Integrated energy systems have become an important research topic in the pursuit of sustainable energy development. This paper examines regional integrated energy systems, presents the typical architecture of regional integrated energy systems, and builds an integrated energy system model. Two evaluation indexes are proposed: the integrated energy self-sufficiency rate and the expected energy deficiency index. Based on these evaluation indexes and taking into account the uncertainty of wind power generation, a bi-level optimization model based on meta-heuristic algorithms and multi-objective programming is established to solve the problem of regional integrated energy system planning under different load structures and for multi-period and multi-scenario operation modes. A quantum evolutionary algorithm is combined with genetic algorithms to solve the problem.

关键词： integrated energy system quantum evolutionary algorithm multi-objective programming bi-level model uncertainty

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100% Renewable energy planning with complementarity and flexibility based on a multi-objective assessment

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APPLIED ENERGY 2019年 255卷 113819-000页

作者： Luz, Thiago Moura, Pedro Univ Coimbra Dep Elect & Comp Engn Inst Syst & Robot Polo 2 P-3030290 Coimbra Portugal

The decarbonization of the power sector has led many academic, governmental and non-governmental institutions to design scenarios with 100% renewable energy and several options to compensate the mismatch between demand and generation have been presented. This paper addresses the benefits to renewable energy integration ensured by the complementarity, and flexibility options, such as demand-side management and batteries. A non-linear multi-objective problem is proposed that maximizes the complementarity and minimizes the total expansion cost. The model also optimizes the battery integration, complementarity between sources and regions, costs, demand-side management, hydropower storage requirements and spatial technology distribution with hourly resolution. The methodology is implemented for the Brazilian case and a scenario able to guarantee three consecutive years of extreme drought in 2050 is presented, without the need of new large reservoirs. Such scenario is ensured with 10% of solar energy, 43% of wind energy, 4.3% of biomass, 41% of hydropower and 1.7% of demand-side management.

关键词： Power generation expansion planning multi-objective programming Renewable energy sources Generation flexibility Generation complementarity

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A multi-objective optimization approach for the selection of overseas oil projects

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COMPUTERS & INDUSTRIAL ENGINEERING 2021年 151卷 106977-106977页

作者： Chen, Hao Li, Xi-Yu Lu, Xin-Ru Sheng, Ni Zhou, Wei Geng, Hao-Peng Yu, Shiwei Renmin Univ China Sch Appl Econ Beijing 100872 Peoples R China China Univ Geosci Sch Econ & Management Wuhan 430074 Peoples R China Macau Univ Sci & Technol Sch Business Macau 999078 Peoples R China Univ Cambridge Energy Policy Res Grp EPRG Cambridge CB2 1AG England

Most good quality overseas oil projects, high in investment returns and abundant in resources, are located in politically unstable regions, where competing objectives present great challenges for investors to make informed decisions. Moreover, most of the existing models are single objective and do not adequately incorporate the unique characteristics of overseas oil investment. To bridge these gaps, this study develops a Non-linear multi-objective Binary Program (NMBP) to optimize the investment portfolios under three competing objectives. A solution algorithm is developed to solve this multiple objective program by integrating Non-dominated Sorting Genetic Algorithm II (NSGA-II) with Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). NSGA-II searches for the pareto set of optimal investment portfolios and TOPSIS determines the best compromise solution based on the investors' preferences. Finally, China's oil investment in the Belt and Road Initiative countries is taken as a case study to demonstrate the feasibility and effectiveness of the proposed approach.

关键词： Overseas oil investment Portfolio choices multi-objective programming NSGA-II TOPSIS Belt and road initiative

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Vícekriteriální optimalizace portfolia

Vícekriteriální optimalizace portfolia

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作者： Malá, Alena Charles University of Prague

The goal of this thesis is to summarize three basic principles of solving multi-objective programming problems. We focus on three approaches: a linear combination of objective functions, ε-constrained approach and a goal programming. All these methods are subsequently applied to US data. We consider monthly excess returns of ten US representative portfolios based on individual stock market capitalization of equity that serve as basic assets. Our aim is to find the efficient portfolios. Next we investigate a structure of these portfolios and their mutual relationships. Graphic representation of efficient frontiers is also included in the thesis. All calculations were performed using Mathematica software version 8.

关键词： multi-objective programming linear combination of objective functions epsilon-constrained approach goal programming

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A bi-objective mathematical model for an unrelated parallel machine scheduling problem with job-splitting

JOURNAL OF THE FACULTY OF ENGINEERING AND ARCHITECTURE OF GA...

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JOURNAL OF THE FACULTY OF ENGINEERING AND ARCHITECTURE OF GAZI UNIVERSITY 2022年第4期37卷 2293-2307页

作者： Sarac, Tugba Tutumlu, Busra Eskisehir Osmangazi Univ Fac Engn & Architecture Ind Enginering Dept TR-26480 Eskisehir Turkey Kutahya Dumlupinar Univ Fac Engn Ind Enginering Deparment TR-43100 Kutahya Turkey

Studies dealing with parallel machine scheduling problems generally assume that jobs are not split. However, splitting of jobs can offer opportunities such as delivering the jobs on time or evenly distributing the jobs to the machines. In this study, two different multi-objective mathematical models are proposed for the unrelated parallel machine scheduling problem without and with job-splitting. The first model is for the unrelated parallel machine scheduling problem without job-splitting and it was developed based on the model proposed by Sarac and Tutumlu [1]. In the second model, in which the jobs can split, besides the machines to which the jobs will be assigned and their order, it is also determined how the jobs will split and in which ratios the jobs will be processed on which machines. The objectives of both models are to minimize the completion time of the last job and the number of machines to be used. multi-objective models were transformed into a single-objective structure with the epsilon constraint method. Randomly generated test problems were solved with the proposed models using the GAMS/Cplex solver, and the results were compared. Considering the problems for which the optimum solution is obtained, the first model found a solution in an average of 85% less time than the model in the literature [1], and the second model shortens the completion time of the last job in an average of 14%. In addition, a mathematical heuristic algorithm is proposed for solving large-size problems.

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Adapting to climate change in arid agricultural systems: An optimization model for water-energy-food nexus sustainability

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AGRICULTURAL WATER MANAGEMENT 2024年 303卷

作者： Radmehr, Riza Brorsen, B. Wade Shayanmehr, Samira Oklahoma State Univ Dept Agr Econ Stillwater OK 74078 USA Ferdowsi Univ Mashhad Dept Agr Econ Mashhad *** Iran

Sustainable management of water, energy, and food (WEF) under climate change will be a significant challenge for arid agricultural systems. This study developed a fractional non-linear multi-objective programming (FNLMOP) model to optimize resource allocation and improve agricultural sustainability in these systems under climate change. The model was designed in the framework of the WEF nexus to simultaneously improved energy productivity (profit/energy), and water productivity (profit/water), while mitigating environmental damage (damage to groundwater resources/output) and ensuring food security in an arid watershed in Iran. The long Ashton research station weather generator (LARS-WG) and the coupled model intercomparison project 6 (CMIP6) were employed to project climate parameters for both future dry and wet conditions. The sustainability of the optimal solutions was then assessed using a hybrid criteria importance through intercriteria correlation (CRITIC)-VIKOR approach. The optimal solutions revealed a reduction in the land under cultivation and produced less water-intensive crops. The optimization model can ensure WEF security, enhancing agricultural system sustainability by optimizing crop cultivation patterns and resource allocation. Current crop choices were highly inefficient with the bigger changes being from the current crops to optimal crops. Climate change showed a substantial but lesser influence on optimal crop choice.

关键词： Crop pattern multi-objective programming Optimal resource allocation Sustainable development

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Water-agriculture-ecology nexus synergetic management based on spatiotemporal equilibrium and water transformation: A case study in Aksu River Basin, China

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AGRICULTURAL WATER MANAGEMENT 2024年 303卷

作者： Wang, Taishan Su, Xiaoling Wu, Haijiang Northwest A&F Univ Key Lab Agr Soil & Water Engn Arid & Semiarid Area Minist Educ Yangling 712100 Peoples R China Northwest A&F Univ Coll Water Resources & Architectural Engn Yangling 712100 Shaanxi Peoples R China

The temporal variability and spatial heterogeneity characteristics of the water-agriculture-ecology (WAE) nexus system have aggravated the difficulties in its synergetic management. Besides, in the inland river basin, the surface water and groundwater are tightly linked by the combination of canal and well irrigation. To address these issues, a spatiotemporal equilibrium-water transformation based water-agriculture-ecology nexus synergetic management (SEWT-WAE) model was proposed by incorporating a spatio-temporal robust optimization method and linear water transformation model. The SEWT-WAE model was then applied to the Aksu River Basin, an inland river basin of Xinjiang, China. The results indicated that the SEWT-WAE model was highly effective in achieving spatiotemporal equilibrium in groundwater balance and ecological water utilization, as well as in the integrated management of surface water and groundwater across upstream and downstream regions. The optimal synergetic management scheme was obtained based on the coordinated development degree. Compared to the current situation: (i) the irrigation amount provided by the surface water (groundwater) in the Tabei (Tanan) irrigation district was increased (decreased) by 21.4 % (70.2 %);(ii) the irrigated areas of grain crops and gardens were increased by 30.4 % and 20.1 %, respectively, while the irrigated area of cotton was decreased by 19.4 %;(iii) the ecological water utilization of the Populus euphratica forest was increased by 17.81 %. Overall, this study presents a new optimization model for achieving spatiotemporal equilibrium and conjunctive use of surface water and groundwater and provides decision support for WAE nexus synergetic management in the inland river basin.

关键词： multi-objective programming Robust optimization Conjunctive use multiple criteria analysis Water resource management Irrigation water

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Particle Swarm Optimization-Based multi-objective Planning Model for Marketing Strategy Decision

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JOURNAL OF CIRCUITS SYSTEMS AND COMPUTERS 2024年第16期33卷

作者： Li, Bohan Guo, Qi Univ Illinois Dept Biostat Chicago IL 60607 USA Univ Illinois Dept Business Adm Champaign IL 61820 USA

Intelligent algorithms have shown promise in supporting marketing strategy decisions through data mining. However, existing methods have primarily relied on expertise, lacking autonomous decision-making abilities. Consequently, a marketing strategy decision model based on particle swarm optimization and multi-objective programming is proposed. This study first explores the potential for integrating particle optimization and multi-objective programming models partially, and then assesses the overall effectiveness of each marketing strategy by defining a fitness function. Subsequently, the particle swarm optimization algorithm is employed to search for and optimize decision variables to identify the optimal combination of marketing strategies. Finally, several simulation experiments are conducted using external real data. The research findings indicate that the algorithm's error rate in this study was initially 0.23. However, after 500 training sessions, it decreased to 0.08 and maintained a relatively low level. The proportion of marketing strategy revenue increased by 15.2 percentage points between 0 and 100 training sessions, then remained relatively stable at over 30%. Its revenue proportion continued to rise during the training process, significantly surpassing that of other algorithms.

关键词： Particle swarm optimization multi-objective programming decision-making algorithm optimization

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Adaptation to seasonal drought in irrigation districts of south China: A copula-based fuzzy-flexible stochastic multi-objective approach for precise irrigation planning

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JOURNAL OF HYDROLOGY 2023年第PartA期625卷

作者： Yue, Qiong Cui, Ningbo Zhang, Fan Guo, Shanshan Jiang, Shouzheng Yu, Xiuyun Zhu, Bin Hohai Univ Coll Agr Sci & Engn Nanjing 211100 Peoples R China Sichuan Univ State Key Lab Hydraul & Mt River Engn Chengdu 610065 Peoples R China Sichuan Univ Coll Water Resource & Hydropower Chengdu 610065 Peoples R China Beijing Forestry Univ Sch Soil & Water Conservat Beijing 100083 Peoples R China Tsinghua Univ Dept Hydraul Engn State Key Lab Hydrosci & Hydraul Engn Beijing 100084 Peoples R China

The occurrence of seasonal drought has led to periodic water shortages in irrigation districts of south China, posing significant agricultural challenges on water and food security. Consequently, there is a pressing need for high-efficient water resources management from a sustainability perspective. To address this issue, a copulabased fuzzy-flexible stochastic multi-objective programming (CFSMP) model was proposed to facilitate irrigation planning under the combined influence of seasonal dry and wet conditions. The model was aimed to simultaneously achieve maximum economic benefit, water productivity and green water use efficiency, considering the economic, social, and environmental spheres of the irrigation district. The CFSMP model represented an innovative solution that was capable of (1) precisely describing the response of crop yield to water supply at ten-day time scale, which can be matched with practical irrigation demand;(2) characterizing joint distributions of seasonal dry and wet conditions of precipitation during different crop growth periods based on the copula function;(3) reconciling conflicts on objectives among economic, social, and environmental spheres of the irrigation district in complex and uncertain environments. The proposed model was applied to the Dongfeng Reservoir Irrigation District in south China. The downscaled ten-day Jensen water production functions of main grain and cash crops were fitted to recognize precise distributions of crop water demand and water sensitivity index. The Frank copula, with the smallest value of squared Euclidean distribution, was selected to describe the joint distribution of seasonal precipitation and gain insights into actual seasonal water availability and water scarcity. The results showed that the proposed model produced more water-saving and yieldpromoting irrigation planning policies than the current quota. The average water allocation of rice, wheat, maize, rape, and citrus decreased by 352.6 mm, 10

关键词： Seasonal drought South China Irrigation planning Copula multi-objective programming

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An integrated approach for reducing spatially coupled water-shortage risks of Beijing-Tianjin-Hebei urban agglomeration in China*

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JOURNAL OF HYDROLOGY 2021年第PartD期603卷 127123-127123页

作者： Cai, Yanpeng Wang, Hao Yue, Wencong Xie, Yulei Liang, Qingtian Guangdong Univ Technol Inst Environm & Ecol Engn Guangdong Prov Key Lab Water Qual Improvement & E Guangzhou 510006 Peoples R China Southern Marine Sci & Engn Guangdong Lab Guangzho Guangzhou 511458 Peoples R China Beijing Normal Univ State Key Lab Water Environm Simulat Beijing 100875 Peoples R China Dongguan Univ Technol Res Ctr Ecoenvironm Engn Dongguan 523808 Peoples R China Qingdao Coastal Architectural Design Co Ltd Qingdao 266011 Peoples R China

Growing agricultural and economic activities have brought tremendous pressure to regional water resources management. Considering the interactions of water resources allocation among adjacent regions with connected water systems, it is necessary to pay attention to the unification of socio-economic development and environmental protection between the regions. This is of significance to many agglomeration areas that are composed of multiple large cities such as the Beijing-Tianjin-Hebei urban agglomeration (BTH) in China. In this research, an ensemble approach was proposed to tackle water resources allocation problems under the constraints of water resources to reflect interdependence of the composed three areas, i.e., Beijing, Tianjin and Hebei. The approach included ARIMA (Autoregressive Integrated Moving Average) method, ANN (Artificial Neural Network) modelling, copula functions, and multi-objective chance-constrained programming model. It can 1) reflect the variations characteristic of regional water supply and demands, 2) solve the interactions between multi-regional water resources, and 3) obtain desired water resources allocation strategies under multi- scenario and scale conditions. Then, the approach was applied in typical regions of China, i.e., Beijing-Tianjin-Hebei urban agglomeration. Considering 27 scenarios of the nexus water shortage risk, multi-objective joint opportunity constraint programming model aimed at maximizing economic benefits and ecological benefits, in combination with economic, agricultural, water resources and environmental constraints. As the optimal strategies indicated, the maximum GDP in BTH would remain at 8514 billion yuan. The minimum amount of water allocation and wastewater discharge would be 24-26 billion m3 and 2100-2101 million m3 respectively.

关键词： Copula function multi-objective programming Nexus risks Beijing-Tianjin-Hebei urban agglomeration

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