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Optimal hybrid participation of customers in a smart micro-grid based on day-ahead electrical market

ARTIFICIAL INTELLIGENCE REVIEW 2022年第7期55卷 5891-5915页

作者： Chamandoust, Heydar Islamic Azad Univ Dept Elect Engn Damavand Branch Tehran Iran

One of main challenges in the many countries with attention to growth people in the world is sustainable consumption and production of energy to improve environmental and economic issues by smart energy systems. In this paper, a multi-objective function model is developed to supply the demand of a smart micro-grid (SMG) with the aim of minimizing first) the operation cost, second) the emission pollution, and third) the deviation between the original demand curve and its desired level in the day-ahead time period. The third proposed objective function is a new strategy which can be used by the SMG operators to manage the demand consumption through responsible customers (RCs) with shiftable loads. Moreover, a number of consumers can participate in the energy management problem of the system through curtailing the demand as a reserve. The proposed objective functions are optimized to obtain the non-dominated solutions using the epsilon-constraint method. Then, the best solution is selected using combined fuzzy and Weighted sum approaches. To evaluate the effectiveness of the proposed model and its solution approach, it is applied on a test system considering four different case studies. The emission pollution and operation cost in the first case (base case) are 8832.24 kg and $692,930.2. In second case and with the participation of reserve, the reduction of the operation cost and the emission are equal to 6.03% and 7.98% than first case. With the participation of the demand shifting strategy in third case, operation cost and the emission are decreased by 20.2% and 19.89% according to base case. Finally, in fourth case and with participation of reserve and demand shifting strategy, the operation cost and the emission pollution are reduced by 26.5% and 38.1% in comparison with the base case.

关键词： Multi-objective functions Smart micro-grid Reserve epsilon-constraint method Weighted sum approach

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A Class of Linear Multi-Objective Decision Making Model Based on Level-2 TFNwTFC Coefficients and Its Application to Supplier Selection

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INTERNATIONAL JOURNAL OF UNCERTAINTY FUZZINESS AND KNOWLEDGE-BASED SYSTEMS 2014年第3期22卷 339-366页

作者： Zhou, Xiaoyang Xu, Jiuping Zhu, Qing Shaanxi Normal Univ Int Business Sch Xian 710062 Peoples R China Sichuan Univ Sch Business Chengdu 610064 Peoples R China

In this paper, we concentrate on a class of linear multi-objective decision making models with level-2 TFNwTFC coefficients. Firstly, we define a level-2 triangular fuzzy number with a triangular fuzzy centre (TFNwTFC) based on level-2 fuzzy set theory, and propose a theorem on how to transform it into an (alpha, beta)-level trapezoidal fuzzy number(TrFN). Secondly, in order to deal with the linear multi-objective decision making model with TrFN coefficients, we present an expected multi-objective model with chance constraints, and discuss its equivalent model. Then the epsilon-constraint method is employed to determine a solution to the crisp equivalent model. Finally, a supplier selection problem is used to illustrate the proposed models and approaches.

关键词： Level-2 TFNwTFC linear multi-objective decision making model expected model with chance constraints epsilon-constraint method supplier selection

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A novel multi-objective model for green forward and reverse logistics network design

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JOURNAL OF CLEANER PRODUCTION 2019年 208卷 1304-1316页

作者： Zarbakhshnia, Navid Soleimani, Hamed Goh, Mark Razavi, Seyyedeh Sara IAU Qazvin Branch Young Researchers & Elites Club Qazvin Iran IAU Qazvin Branch Fac Ind & Mech Engn Dept Ind Engn Qazvin Iran Natl Univ Singapore NUS Business Sch Singapore Singapore Natl Univ Singapore Logist Inst Asia Pacific Singapore Singapore Islamic Azad Univ Qazvin Branch Dept Ind Management Fac Management & Accounting Qazvin Iran

With a greater awareness of responsibility for the environment and the need to sustain profitability in a competitive market, reverse logistics has become a key part of supply chain management. This paper therefore seeks to consider the designing and planning of a green forward and reverse logistics network, through a mixed integer linear programming model. The model is applied to a multi-stage, multiproduct, and multi-objective problem whereby the first objective is to minimize the cost of operations, processes, transportation, and fixed costs of the establishment. The second objective is to minimize the amount of CO2 emissions based on the gram unit, while the third is to optimize the number of machines in the production line. For validation, the model is applied to the home appliance industry through several test problems. In terms of the solution methodology, an epsilon-constraint method is developed as the area of optimization in order to obtain a set of Pareto solutions. Finally, sensitivity analysis is conducted to understand the effects of changes in the demand, cost, and rate of return of the used product, on the objective function values. (C) 2018 Elsevier Ltd. All rights reserved.

关键词： Supply chain management Green forward and reverse logistics Multi-objective programming CO2 emissions epsilon-constraint method

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Exploring the trade-off between competing objectives for electricity energy retailers through a novel multi-objective framework

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ENERGY CONVERSION AND MANAGEMENT 2015年 91卷 12-18页

作者： Charvvand, Mansour Ahmadi, Abdollah Siano, Pierluigi Dargahi, Vahid Sarno, Debora HEPDC Bandar Abbas Iran Univ New S Wales Sch Elect Engn & Telecommun Sydney NSW Australia Univ Salerno Dept Ind Engn Fisciano Italy Clemson Univ Holcombe Dept Elect & Comp Engn Microgrid & Power Elect Lab Clemson SC 29634 USA

Energy retailer is the intermediary between Generation Companies and consumers. In the medium time horizon, in order to gain market share, he has to minimize his selling price while looking at the profit, which is dependent on the revenues from selling and the costs to buy energy from forward contracts and participation in the market pool. In this paper, the two competing objectives are engaged proposing a new multi-objective framework in which a epsilon-constraint mathematical technique is used to produce the Pareto front (set of optimal solutions). The stochasticity of energy prices in the market and customer load demand are coped with the Lattice Monte Carlo Simulation (LMCS) and the method of the roulette wheel, which allow the stochastic multi-objective problem to be turned into a set of deterministic equivalents. The method performance is tested into some case studies. (C) 2014 Elsevier Ltd. All rights reserved.

关键词： Energy retailer Forward contracts Multi-objective mathematical programming epsilon-constraint method

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Applying augmented ε-constraint approach and lexicographic optimization to solve multi-objective hydrothermal generation scheduling considering the impacts of pumped-storage units

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INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 2014年 55卷 195-204页

作者： Nezhad, Ali Esmaeel Javadi, Mohammad Sadegh Rahimi, Ehsan Islamic Azad Univ Sci & Res Branch Dept Elect Engn Fars Iran Islamic Azad Univ Najafabad Branch Dept Elect Engn Esfahan Iran

In this paper, the problem of optimal economic scheduling of multi-reservoir cascaded hydrothermal units is investigated in the presence of an individual pumped-storage generating unit in the network. The proposed problem is modeled in a multi-objective framework comprising two objective functions. The goal of the first objective function is to minimize the operation costs and the second one is set to minimize the emissions caused by the thermal units while all the technical constraints are satisfied. Furthermore, the valve loading effect is included in the first objective function as a sinusoidal function. The problem is modeled and solved as a Mixed Integer Non-Linear Programming (MINLP). The augmented E-constraint technique and lexicographic optimization are employed to solve the problem. Numerical results obtained from implementing the model on a case study are discussed. Also, the decision making procedure has been done using a fuzzy satisfying method to select the most preferred solution among the Pareto solutions derived through solving the multi-objective problem. (C) 2013 Elsevier Ltd. All rights reserved.

关键词： Pumped-storage Fuzzy decision making epsilon-constraint method Augmented epsilon-constraint Lexicographic optimization Hydrothermal scheduling

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A Bi-Objective Pollution Routing Optimisation Problem With Decentralised Cooperation and Split Delivery

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IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS 2023年第11期24卷 12357-12371页

作者： Shi, Weixuan Wang, Nengmin Zhang, Meng Jiang, Bin Xi An Jiao Tong Univ Sch Management Xian 710049 Peoples R China ERC Proc Min Mfg Serv Shaanxi Prov Xian 710049 Shaanxi Peoples R China Xian Technol Univ Sch Econ & Management Xian 710021 Peoples R China DePaul Univ Driehaus Coll Business Dept Management Chicago IL 60604 USA

The logistics industry is a major source of global carbon emissions and energy consumption. Cooperative logistics and split delivery are effective methods for reducing carbon emissions and improving distribution efficiency, respectively. However, prior research on pollution routing problems (PRP) has primarily focused on centralized cooperation and has not fully explored the potential of split delivery as a strategy for addressing PRPs. This study fills this gap by integrating decentralised cooperation and split delivery to the PRP domain, offering an innovative approach to the problem. A bi-objective mixed integer linear PRP model with split delivery and request selection is put forward for the problem. In addition, an epsilon-constrained hybrid evolutionary algorithm is proposed herein, which combines a Greedy Randomized Adaptive Search Procedure-Evolutionary Local Search (GRASP-ELS) hybrid approach with the epsilon-constrained method. The results of experiments demonstrate that the proposed algorithm outperforms the well-known multi-objective optimization algorithms: NSGA-II, MOPSO, and SPEA-II. The study also provides several managerial insights through sensitivity analysis. The proposed model and algorithm can provide a basis for decision making for logistics companies to improve logistics efficiency and reduce carbon emissions.

关键词： Pollution routing problem cooperative logistics bi-objective optimisation epsilon-constraint method

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Optimal economic dispatch of FC-CHP based heat and power micro-grids

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APPLIED THERMAL ENGINEERING 2017年 114卷 756-769页

作者： Nazari-Heris, Morteza Abapour, Saeed Mohammadi-Ivatloo, Behnam Univ Tabriz Fac Elect & Comp Engn Smart Energy Syst Lab Tabriz Iran

Micro-grids (MGs) are introduced as a solution for distributed energy resource (DER) units and energy storage systems (ESSs) to participate in providing the required electricity demand of controllable and non-controllable loads. In this paper, the authors study the short-term scheduling of grid-connected industrial heat and power MG which contains a fuel cell (FC) unit, combined heat and power (CHP) generation units, power-only unit, boiler, battery storage system, and heat buffer tank. The paper is aimed to solve the multi-objective MG dispatch problem containing cost and emission minimization with the considerations of demand response program and uncertainties. A probabilistic framework based on a scenario method, which is considered for load demand and price signals, is employed to overcome the uncertainties in the optimal energy management of the MG. In order to reduce operational cost, time of -use rates of demand response programs have been modeled, and the effects of such programs on the load profile have been discussed. To solve the multi-objective optimization problem, the epsilon-constraint method is used and a fuzzy satisfying approach has been employed to select the best compromise solution. Three cases are studied in this research to confirm the performanC'e of the proposed method: islanded mode, grid-connected mode, and the impact of time of the use-demand response program on MG scheduling. (C) 2016 Elsevier Ltd. All rights reserved.

关键词： Fuel cell Combined heat and power (CHP) Economic dispatch Demand response (DR) program Heat and power micro-grid (MG) Storage devices epsilon-constraint method

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Optimization, validation and analyses of a hybrid PV-battery-diesel power system using enhanced electromagnetic field optimization algorithm and ε-constraint

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ENERGY REPORTS 2024年 11卷 5335-5349页

作者： Zhu, Chaoyang Zhang, Yunxiang Wang, Mengxia Deng, Jinxin Cai, Yiwei Wei, Wei Guo, Mengxing Univ China Inst Social Innovat & Publ Culture Commun Beijing 100000 Peoples R China Int Inst Engn Psychol Denver CO 80201 USA Univ Illinois Champaign Urbana Champaign IL 61801 USA Hainan Vocat Univ Sci & Technol Haikou 570100 Hainan Peoples R China Shenzhen High level Talents Dev Promot Assoc Shenzhen 518000 Guangdong Peoples R China CDA Int Accelerator Shenzhen 518000 Guangdong Peoples R China Shenzhen Res Inst Beijing Inst Technol Shenzhen 518000 Guangdong Peoples R China Univ Wollongong Wollongong NSW 2522 Australia Xian Univ Technol Sch Comp Sci & Engn Xian 710048 Shaanxi Peoples R China Shandong Open Univ Jinan 250000 Shandong Peoples R China

This study introduces and assesses a hybrid renewable energy system tailored for a practical, off-grid location. The integrated power system comprises a diesel generator, photovoltaic panels, battery storage system, and a converter. The primary objective is to formulate a system exhibiting optimal performance concerning cost, carbon emissions, and load satisfaction, necessitating a three-objective optimization approach. Leveraging the epsilon-constraint method alongside an enhanced optimization algorithm, the study compares the enhanced algorithm against its original version and established optimization algorithms using intricate benchmark functions. Outcomes indicate the enhanced algorithm's superiority, manifested through minimal error and standard deviation. Subsequently, the enhanced hybrid optimization method is employed to optimize the design and operation of the proposed power system, considering economic, environmental, and technical facets. Rigorous sensitivity analyses ascertain the system cost's responsiveness to varying parameters. To validate the efficacy of the proposed optimization approach, a parallel optimization of the hybrid power system is conducted using HOMER software. Results demonstrate that the proposed hybrid optimization method not only meets defined limits but also minimizes carbon emissions, emphasizing its effectiveness in designing sustainable and efficient off-grid energy systems.

关键词： Multi-objective optimization Enhanced electromagnetic field optimization algorithm epsilon-constraint method Hybrid renewable energy system Photovoltaic

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An integrated multi-objective framework for solving multi-period project selection problems

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APPLIED MATHEMATICS AND COMPUTATION 2012年第6期219卷 3122-3138页

作者： Khalili-Damghani, Kaveh Tavana, Madjid Sadi-Nezhad, Soheil Islamic Azad Univ S Tehran Branch Dept Ind Engn Tehran Iran La Salle Univ Lindback Distinguished Chair Informat Syst & Deci Philadelphia PA 19141 USA

Investment managers are multi-objective decision-makers (DMs) who make portfolio decisions by maximizing profits and minimizing risks over a multi-period planning horizon. Portfolio decisions are complex multi-objective problems which include both tangible and intangible factors. We propose an integrated multi-objective framework for project portfolio selection with respect to both the profits and risks objectives. The proposed method is based on the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) and an efficient version of the epsilon-constraint method. TOPSIS is used to reduce the Multi-Objective Decision Making (MODM) problem into a bi-objective problem. The efficient epsilon-constraint method is used to generate non-dominated solutions with a pre-defined and arbitrary resolution on the Pareto front of the aforementioned bi-objective problem. The results from the integrated framework proposed in this study are compared with the results from the conventional epsilon-constraint method based on a series of simulated benchmark cases. A sensitivity analysis is performed to study the sensitivity of the relative importance weights of the objective functions in re-generating the Pareto front. The practical application of the proposed framework illustrates the efficacy of the procedures and algorithms. (C) 2012 Elsevier Inc. All rights reserved.

关键词： Multi-objective decision making epsilon-constraint method Pareto front TOPSIS Mathematical programming Multi-period project selection

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Multi-objective models for biomass supply chain planning with economic and carbon footprint consideration

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ENERGY REPORTS 2021年 7卷 6833-6843页

作者： Duc, Duy Nguyen Meejaroen, Pasakorn Nananukul, Narameth Thammasat Univ Sch Management Technol Sirindhorn Int Inst Technol Bangkok Thailand

This paper focuses on designing multi-objective biomass supply chain planning models that aim to simultaneously minimize the total cost and the carbon footprint from the transportation. Stochastic and fuzzy models were developed for making strategic (optimal plant locations) and tactical decisions (material flows, truck types, etc.), while capturing the uncertainty of the demand. An epsilon-constraint method was applied to generate optimal solutions from these models. Managerial insights are provided based on a practical case study at a biomass plant in the Lower Northern region of Thailand;nine biomass plant candidates, nine rice husks suppliers and eight trucks were considered in the case study. A sensitivity analysis has been conducted to compare the results from the two models. The stochastic model can take into account all the scenarios of demand, while the fuzzy model can handle only a certain level of demand defined by a centroid value. The stochastic model needs to take into account a large number of variables and constraints, and therefore, requires more runtime to define an optimal solution, as compared to the fuzzy model. The trade-off between the operating cost and carbon emissions from both the models are provided with managerial insights. (C) 2021 The Authors. Published by Elsevier Ltd.

关键词： Biomass supply chain management epsilon-constraint method Multi-objective model Fuzzy model Stochastic model Carbon footprint Renewable energy

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