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Stochastic energy planning of a deltoid structure of interconnected multilateral grids by considering hydrogen station and demand response programs

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APPLIED ENERGY 2024年 375卷

作者： Shaterabadi, Mohammad Ahmadi, Shahab Jirdehi, Mehdi Ahmadi Kermanshah Univ Technol Dept Elect Engn Kermanshah Iran

This paper presents triple-objective stochastic energy planning and management of a deltoid structure in which a microgrid, nano-grid, and main grid connect and exchange power simultaneously. In addition, the impact of hydrogen stations due to the growth of hydrogen vehicles and their crucial role in the power system's future to reduce pollution is also discussed. Moreover, the effect of time-based demand response programs (TOU) according to the elasticity matrix (different operators and price-sensitive flexible loads) for the proposed multilateral grid is investigated under diverse scenarios. Stochastic planning is performed to make results more realistic and authentic. The uncertain parameters for stochastic planning include wind pace, solar radiation, fuel rate, and various demands. The assumed triple objective functions for the proposed planning are the microgrid's profit, the nano-grid's cost, and the total multilateral grid's pollution. The problem is modeled as mixed-integer linear programming (MILP) and solved using the GAMS and LP metric approach. The final results show that by implementing the supposed planning, the microgrid's profit increases by about 22.53 $/day (10.8%), and the nano-grid's cost decreases by about 1.31 $/day (9.8%). On the other hand, the total environmental pollution is reduced significantly and reaches 1.06 kg/day.

关键词： Demand response programs Energy management Hydrogen application multi-objective programming multilateral grid Stochastic planning

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A fuzzy compromise approach for solving multi-objective stratified sampling design

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NEURAL COMPUTING & APPLICATIONS 2021年第17期33卷 10829-10840页

作者： Ghufran, Shazia Gupta, Srikant Ahmed, Aquil Aligarh Muslim Univ Dept Stat & Operat Res Aligarh Uttar Pradesh India Jaipuria Inst Management Jaipur Rajasthan India

In this paper, we established a framework for finding out the optimal allocation in the multivariate stratified sample using the fuzzy compromise method. The problem of multivariate stratified sample is formulated as an all integer nonlinear programming problem, and a solution is obtained by using the criterion of "Minimizing the sum of the squares of coefficient of variation for different characteristics." There is also a quantitative illustration being carried out to explain the statistical nature of the approaches and solved through the LINGO program. We have also studied different techniques for comparison.

关键词： Fuzzy compromise allocation multivariate stratified sampling multi-objective programming

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Stochastic two-stage multi-objective unit commitment of distributed resource energy systems considering uncertainties and unit failures

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RELIABILITY ENGINEERING & SYSTEM SAFETY 2025年 253卷

作者： Liu, Jingfan Zhang, Shijie Chinese Acad Sci Inst Engn Thermophys Beijing 100190 Peoples R China Univ Chinese Acad Sci Beijing 100049 Peoples R China

Compared to centralized generation technology, distributed energy resource systems are susceptible to energy risks caused by boundary uncertainties and unit failures. This study introduces a stochastic two-stage multi- objective optimization method to address reliability-based unit commitment issues. In the day-ahead stage, operational state and reserve capacity are determined to minimize prescheduled operation costs based on forecasted parameters. In the real-time stage, a decision-dependent stochastic reliability method is proposed to simulate outage scenarios. Reserve resources within available units are allocated to mitigate forecasting errors and unit failures. Additionally, the grid interaction ratio and penalty cost are added to restrict the depth and frequency access to the grid. Four comparative cases analyze the effects of the proposed methodology. This method innovatively achieves the simulation of stochastic multi-unit outages and delete faulty units in the operation scheme. The optimal results show that the risks of electricity and cooling supply are underestimated, while the risks of heating are overestimated, compared to N-1 reliability. Furthermore, Pareto analysis of the multi-objective problem enhances independent operational capacity through utilization of reserve resources. Grid dispatch pressure is reduced since purchased power can be used as day-ahead planning. Thus, the methodology achieves collaborative optimization of reliability with a reduction of operation costs, offering effective guidance for engineering applications.

关键词： Distributed energy resource system Uncertainties and outages Stochastic two-stage UC Energy and reserve scheduling multi-objective programming

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Spatio-temporal evolution analysis of land use change and landscape ecological risks in rapidly urbanizing areas based on multi-Situation simulation - a case study of Chengdu Plain

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ECOLOGICAL INDICATORS 2024年 166卷

作者： Wei, Yali Zhou, Peiyun Zhang, Luoqi Zhang, Yan Sichuan Agr Univ Sch Resources Chengdu 611130 Peoples R China

Land use change in emerging nations raises landscape ecological risks (LERS), hastens the deterioration of urban and rural ecosystem services, endangers human well-being, and undermines sustainable development in the face of rapidly increasing urbanization. Here, using the Chengdu Plain as the study area and long time series data from 2000 to 2020, the optimal time span is selected for multi-context spatio-temporal simulation. The land use map of Chengdu Plain in 2025 under the four scenarios of "Natural Development" (ND), "Economic Priority Development" (END), "Ecological Priority Development" (ELD), and "Sustainable Development" (SD) was simulated, and the multi-indicator landscape ecological risk index (ERI) was generated to compare and analyze the differences between land use and landscape ecological risk under different policy preferences. Subsequently, the land use data from 2025 to 2040 were simulated, the landscape ecological risk pattern was mapped, and the spatial and temporal evolution analysis from 2010 to 2040 was conducted to explore the spatial evolution law of land use change and landscape ecological risk. Based on the results, the high ecological risk aggregation areas are prone to appear in END scenarios, whereas medium-ecological risk aggregation areas are more likely to appear in ELD scenarios, and the government should focus its policy on arable land protection. Moreover, the land use pattern of cultivated land surrounding construction land and forested land surrounding cultivated land, caused by the irrational single-core development pattern and the policy of returning farmland to forests, has exacerbated the landscape ecological risk of the Chengdu Plain, constituting a unique landscape ecological risk pattern. It's also important to remember that the Chengdu Plain's less economically developed regions need to focus on the high-quality development of ecological land use. We adopted high-precision simulation methods to simulate the complex land

关键词： Landscape ecological risk multi-contextual simulation Time-space evolution multi-objective programming PLUS model

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Self-adaptive metaheuristic-based emissions reduction in a collaborative vehicle routing problem

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SUSTAINABLE CITIES AND SOCIETY 2024年 110卷

作者： Kahalimoghadam, Masoud Thompson, Russell G. Rajabifard, Abbas Univ Melbourne Fac Engn & IT Dept Infrastruct Engn Parkville Australia

Global climate change-related initiatives such as the 2015 Paris Agreement have highlighted the necessity of sustainable transportation. Nevertheless, the rapid growth of e-commerce has notably escalated vehicle kilometres travelled (VKT) and CO2 emissions within cities, posing a direct challenge to sustainability initiatives. To address these challenges, this study formulates a collaborative multi-depot green vehicle routing problem. This model utilises micro-consolidation centres (MCCs) as shared hubs alongside a microscopic approach linking emission rates to vehicle and route characteristics, in order to assess MCCs' effectiveness in reducing CO2 emissions. Introduced here is an innovative self-adaptive metaheuristic algorithm hybridising intelligent water drops and simulated annealing. This methodology differs from established approaches by incorporating a feedback control system that actively monitors the algorithm's performance and convergence towards the global minimum solution. Through continuous adjustments to algorithm parameters via a feedback loop, this methodology strikes a balance between exploitation and exploration. The algorithm is tested in a context-specific approach, first applying it to the Cordeau benchmark and comparing it with previous state-of-the-arts, followed by a case study comparing the collaborative network to an independent one. This approach achieves 43 % and 25 % reductions in VKT and emissions, respectively, enhancing urban logistics networks' efficiency and sustainability.

关键词： MDVRP multi-objective programming Network distribution design Hybrid metaheuristics algorithm Comprehensive Modal Emission Model Knowledge-based systems

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Efficient and equitable irrigation management: A fuzzy multi-objective optimization model integrating water movement processes

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JOURNAL OF ENVIRONMENTAL MANAGEMENT 2024年 371卷 123164页

作者： Chang, Hong Li, Gang Zhang, Chenglong Huo, Zailin China Agr Univ Ctr Agr Water Res China Beijing 100083 Peoples R China China Agr Univ State Key Lab Efficient Utilizat Agr Water Resourc Beijing 100083 Peoples R China

This study presents a robust multi-objective model for optimizing irrigation water allocation to balance economic benefits, water equity and irrigation efficiency in irrigation decisions under uncertainty. Daily water movement among irrigation, soil, groundwater, and drainage is modeled through water balance simulation and integrated into an optimization model considering economic, social, and resource objectives. To effectively manage conflicts arising from multiple objectives under uncertainty, interval multi-objective programming and fuzzyboundary interval programming are employed. Here, interactive algorithms are used to align constraint feasibility with objective satisfaction to generate optimal solutions for irrigation water allocation. The model's applicability is demonstrated within the Hetao Irrigation District, addressing the rising conflicts between irrigation water supply and demand. The optimization model aims to maximize net economic benefits, minimize Gini coefficient and the proportion of blue water utilization in irrigation water, incorporating daily soil water and groundwater movement processes. By setting five feasibility levels, optimal water allocation solutions are derived for five irrigation subareas and three crops across their entire growth periods. The results analysis shows that an increased feasibility level makes the uncertainty range of the objective values decrease while lower feasibility levels lead to higher satisfaction with the objective values. Moreover, it is found that the decision satisfaction peaks at a feasibility level of 0.9 after balancing feasibility and objective satisfaction, aligning more closely with the decision maker's expectations. At this level, the economic benefit is [3.62, 13.60] x 109 Yuan. Compared to a feasibility level of 1.0, the average range of the economic benefits increases by 122.50 x 106 Yuan, and the Gini coefficient decreases from [0.7973, 0.7997] to [0.7963, 0.7996]. Therefore, the above results c

关键词： multi-objective programming Irrigation planning Physical processes Interactive fuzzy programming Uncertainty Decision-making

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Synergistic CO₂ and Air Pollution Reduction Based on multi-objective programming

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2nd International Conference on Energy, Environment and Sustainable Development (EESD 2012)

作者： Chang, Wentao Wen, Juan Bao, Jingling Li, Ran Tianjin Acad Environm Planning Tianjin Peoples R China Hebei Univ Technol Tianjin Peoples R China Nankai Univ Tianjin Peoples R China Tianjin Environm Protect Bur Tianjin Peoples R China

ISBN: (纸本)9783037855522

With increasing frequency of hazards caused by global climate change, the importance of regulating carbon dioxide emission and coping with climate change has been recognized by the entire society. This paper utilized an Energy Flow Diagram to incorporate the energy supplies, conversion and final consumption for analyses. A multi-objective programming model was established to reduce the economic investment on the reduction of air pollution and carbon emission, and applied in a case study of Tianjin, one of the economic hubs of North China. This study can be potentially useful for making decisions on the synergistic CO2 and air pollution reduction and solving conflicts between economic development and environmental protection in China.

关键词： multi-objective programming Air Pollutants CO2 Synergistic Carbon Emission Reduction

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A multi-stage quantitative resilience analysis and optimization framework considering dynamic decisions for urban infrastructure systems

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RELIABILITY ENGINEERING & SYSTEM SAFETY 2024年 243卷

作者： Wang, Feng Tian, Jin Shi, Chenli Ling, Jiamu Chen, Zian Xu, Zhengguo Zhejiang Univ State Key Lab Ind Control Technol Hangzhou 310027 Peoples R China Zhejiang Univ Coll Control Sci & Engn Hangzhou 310027 Peoples R China Huzhou Univ Inst Microbiol & Immunol Huzhou 313000 Zhejiang Peoples R China Beihang Univ Sch Reliabil & Syst Engn Beijing Peoples R China

In urban infrastructure systems, resilience is crucial for maintaining functionality, minimizing losses, and expediting recovery during disruptive incidents. Effective allocating resources across various phases of emerging disturbances can generally enhance the system's capacity to cope with disasters. However, it is imperative to recognize that distinct resource allocation strategies may lead to divergent outcomes in terms of resilience performance. Therefore, this study develops a framework for optimizing resource allocation based on multiple resilience objectives by understanding the interplay between resilience performance and dynamic decisionmaking. The resilience processes are first formalized into distinct stages, considering the technical and organizational resilience of the infrastructure system in the event of disruption. Building upon this foundation, five decision scenarios are proposed, contingent on the allocation or non-allocation of resources to each resilience stage. A multi-resilience-objective mixed-integer linear programming (MROMILP) model is formulated to optimize the resource allocation scheme for each resilience stage within the constraints of internal resources. Finally, the model and framework are tested using a power system as a tangible example. The integrated multi-stage quantitative resilience assessment and optimization method proposed in this study can assist decision-makers in making dynamic and continuous trade-offs between resources and resilience targets.

关键词： Infrastructure systems Resilience optimization multi-objective programming Resource allocation

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Air traffic management in parallel-point merge systems under wind uncertainties

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JOURNAL OF AIR TRANSPORT MANAGEMENT 2022年第0期104卷

作者： Donmez, Kadir Cetek, Cem Kaya, Onur Eskisehir Tech Univ Dept Air Traff Control Eskisehir Turkey Eskisehir Tech Univ Dept Ind Engn Eskisehir Turkey

The point merge system (PMS) was developed by EUROCONTROL in 2006 to enable controllers to implement systematic sequences and replace the traditional vector technique in Terminal Maneuver Area (TMA) even during peak hours. A conventional PMS includes two arc-shaped route segments referred to as sequencing legs and a single merge point to merge arrivals. When necessary, arrivals can be delayed along these legs using path stretching before they are directed to the merge point. After merging, aircraft join the final approach. The parallel-point merge system (P-PMS), however, has a more complex route structure which consists of two oppositely located PMS and a set of common points located between the merge points and final paths of runways. This system increases the capacity of the airspace and provides the advantages of the single PMS. However, especially in simulation studies where P-PMS has been tested, the emphasis on wind sensitivity came to the fore as one of the main issues affecting the use of the system. The use of P-PMS was stated as feasible but more difficult due to the loss of symmetry, especially when the wind is perpendicular to the sequencing legs. Controllers may need help in providing safe and efficient sequences in this type of structure. In this study, a multi-objective two-stage stochastic programming model is developed for P-PMS to obtain robust aircraft sequences, schedules, and runway assignments considering the uncertainties of both wind direction and speed. The model was implemented on the existing layout of Istanbul Airport having a P-PMS serving five parallel runways using the real traffic and wind data. A scenario-based approach was adopted to represent the uncertainties of the model. Also, to meet the demands of the various stakeholders in the air traffic system, the minimization of total fuel consumption, total flight time, and total delays were considered as single and multi-objectives. As a result, it was found that the stochastic approa

关键词： Air traffic management Stochastic programming multi-objective programming Parallel-point merge system Wind uncertainties

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On solving multi-objective fully quadratic fractional optimisation model with interactive FGP approach

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INTERNATIONAL JOURNAL OF QUALITY & RELIABILITY MANAGEMENT 2022年第10期39卷 2286-2301页

作者： Rani, Namrata Goyal, Vandana Gupta, Deepak Maharishi Markandeshwar Deemed Univ Dept Math Ambala India

Purpose - The main motive behind framing this paper is to provide a compromised solution for trapezoidal fuzzy number-multi-objective fully quadratic fractional optimisation model (TrFN-MOFQFOM) by avoiding ambiguities and confusion of decision-makers (DMs). Many researchers have used Taylor's series and parametric approach to transform fractional objective function into non-fractional ones, but Taylor's series expansion is valid only up to a neighbourhood. To avoid these extra efforts, this article suggests a methodology in which numerator of objective function is optimised under the condition of optimising denominator. Design/methodology/approach - This paper suggests an efficient procedure to search for compromised solution of MOFQFOM with fuzzy coefficients using alpha-level set and FGP approach. Incomplete data in model is dealt with alpha-level set. Then after defuzzification, non-fractional models are built from fractional model to get optimal solution of every objective. Finally, the linear weighted sum of negative deviational variables is minimised to satisfy all objective functions up to maximum possible extent. Findings - On applying suggested approach to the example given in end, the authors arrived at compromised solution having mu(O1) (O-1(x)) =1 and mu(O2) (O-2(x)) = 0.71. The applied procedure requires less computational efforts and provides the preferred compromised solution. Originality/value - This work has not been done previously by anyone. The idea being developed here of constructing non-fractional model by dealing numerators and denominators separately is completely new. 10;In the end, an algorithm, flowchart and numerical are also given to clarify the applicability of the suggested approach.

关键词： alpha-Cut method Non-fractional models multi-objective programming Trapezoidal fuzzy number (TrFN) Fuzzy goal programming (FGP)

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