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Multi-objective and multi-algorithm operation optimization of integrated energy system considering ground source energy and solar energy

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INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 2023年 144卷

作者： Wu, Xiaonan Liao, Borui Su, Yaogang Li, Shuang Southwest Petr Univ Sch Civil Engn & Geomat Chengdu 610500 Sichuan Peoples R China Southwest Petr Univ Coll Engn Nanchong 637000 Sichuan Peoples R China

The optimized operation of integrated energy systems (IES) is of great significance to reduce carbon emissions and improve the overall efficiency of the system, at present, IES planning lacks comprehensive planning. As a response, in this paper, a grid-connected IES is proposed, which considers the complementarity of geothermal energy and solar energy and takes heat storage into account. The multi-objective optimization problem of IES is studied for the coupling mode of electric energy, heat energy and cold energy. Taking a multi-functional park as the research object, a multi-objective optimization model was established aiming at integrating operation cost, exergic efficiency and pollution gas emission penalty cost. MO-NSGA-II algorithm was proposed to solve the optimization model, and it was compared with MOI-PSO algorithm and MO-WA algorithm. The results show that MO-NSGA-II algorithm has stronger convergence, pareto solution set is obviously better than the other two optimization algorithms, and the solution set has better continuity and uniformity. Secondly, the comparison between IES and the traditional energy supply system proved the superiority of IES in multi-objective. The cost saving rate of IES was up to 57.3%, exergic efficiency was improved 39.5% and pollution emissions were reduced 54.8%. It also proved again that MO-NSGA-II algorithm had a good effect on solving the IES model in this paper. Then, we analyzed the cold, hot and electric energy hub scheduling diagram of the three algorithms and found that MO-NSGA-II algorithm had better self-regulation ability, and the coordinated output ratio of gas turbine and power grid was a key factor affecting the overall economic and environmental benefits of IES, which was strongly correlated with the operation strategy of the system. These results can provide reference for the optimization of integrated energy system and further tap the development potential of multi-energy system.

关键词： Integrated energy system Combined cooling heating and power system Energy storage Multi-objective optimization mixed integer linear programming

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Co-optimization of charging scheduling and platooning for long-haul electric freight vehicles

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TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES 2023年第1期147卷

作者： Alam, Md Rakibul Guo, Zhaomia Cluster Univ Cent Florida Dept Civil Environm & Construct Engn Resilient Intelligent & Sustainable Energy Syst Orlando FL 32766 USA 4353 Scorpius St Orlando FL 32816 USA

Freight mileages have been significantly increasing over the past decade, accounting for 11% of global greenhouse gas (GHG) emissions. Freight electrification and platooning are two promising technologies to mitigate the energy and environmental impacts of freight transportation. Effective coordination of charging and platooning are urgently needed to maximize the benefits of these two technologies, especially considering the current inadequate charging infrastructure, long charging duration, higher energy usage, and tight delivery schedules for long-haul electric freight vehicles (EFVs). In this study, we aim to co-optimize the platooning and charging strategies of EFVs. To achieve this goal, we developed a mixed-integer linear programming model to minimize the total system costs, including en-route charging cost, delivery delay cost, and hub charging cost. The proposed model was tested using a case study of a 595-mile Florida interstate highway route and solved by the state-of-the-art branch-and-cut algorithms, through which we demonstrated the effectiveness of using our model to identify the optimal charging and platooning schedules and quantify the spatial distribution of charging demand and platoon energy savings. We also performed sensitivity analyses to better understand the impacts of some critical factors, including the EFV models, charging station (CS) capacity, number of CSs, charging speed, and departure-time windows.

关键词： Electric freight vehicles Charging scheduling mixed integer linear programming Platooning Long-haul freight transportation

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Bad Data Identification Method for Medium Voltage Distribution Network

Bad Data Identification Method for Medium Voltage Distributi...

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Cyber-Energy Systems and Intelligent Energy (ICCSIE), International Conference on

作者： Dong Jun Guo Bin Xuebin Shang Xiaoqiang Wu Zhao Yun Yuxin Lu Guangzhou Power Supply Bureau Guangdong Power Grid Co. Ltd. Guangdong China CSG Electric Power Research Institute Guangdong Provincial Key Laboratory of Intelligent Measurement and Advanced Metering of Power Grid Guangdong China

ISBN: (数字)9798350373318

ISBN: (纸本)9798350373325

Bad data identification is an essential prerequisite for state estimation in distribution networks. When multiple leverage measurements with bad data occur in the system, traditional residual-based methods are ineffective in identifying bad data, leading to potential misjudgments and missed detections. Additionally, traditional mixed-integer nonlinear programming methods for solving this issue suffer from low efficiency due to the large number of integer variables and nonlinear constraints in the model. Therefore, a bad data identification method based on mixed-integer linear programming is proposed. By employing the data-physical fusion-driven linearization method for linearization, a mixed- integer linear programming-based bad data identification model is constructed. Case studies demonstrate that the bad data identification method based on mixed-integer linear programming can significantly improve solution efficiency while ensuring accuracy in identification.

关键词： Accuracy Distribution networks Transforms Medium voltage programming Data models mixed integer linear programming Problem-solving Object recognition State estimation

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A Study of Crop Planting Strategies Based on the MILP Model and Monte Carlo Simulation

A Study of Crop Planting Strategies Based on the MILP Model ...

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Electronics, Energy Systems and Power Engineering (EESPE), IEEE International Conference on

作者： Daizhen Wu Kuangsheng Yao Zilong Tan PLA Dalian Naval Academy Dalian China

ISBN: (数字)9798350389579

ISBN: (纸本)9798350389586

The aim of this paper is to investigate crop cultivation strategies through mixed integer linear programming (MILP) models and Monte Carlo simulations. Firstly, based on 2023 data, the MILP model was constructed to maximise net returns and minimise stunting losses, and the impact of different market response strategies on economic efficiency was analysed. Second, the Monte Carlo simulation method was used to dynamically adjust the planting layout to cope with market fluctuations by taking into account the growth trend of crop sales and the uncertainty of other crop parameters. Finally, through the correlation analysis between crops, the substitutability and complementarity between crops were explored in depth to further optimise the planting strategy. The methodology of this paper provides an important reference for the optimization of crop planting strategies in similar regions, showing the potential of the MILP model and Monte Carlo simulation.

关键词： Economics Analytical models Monte Carlo methods Correlation Biological system modeling Layout Crops Market research mixed integer linear programming Optimization

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Coupling Clearing Model for Coordinated Operation of Inter provincial and Intra provincial Integration Electricity Market

Coupling Clearing Model for Coordinated Operation of Inter p...

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International Conference on Communication Systems and Network Technologies (CSNT)

作者： Boyang Chen Maomao Ding Jiamei Yan Shiyao Cheng Zhongwei Cai State Grid Customer Service Center Tianjin China

ISBN: (数字)9798331531935

ISBN: (纸本)9798331531942

This article proposes a coupled clearing model to address the market coupling and clearing mechanism issues in the coordinated operation of inter provincial and intra provincial electricity markets in China, in order to achieve effective integration and coordination of inter provincial and intra provincial electricity markets. Firstly, this study establishes a dual layer optimization model that considers the coupling characteristics between electricity markets in different provinces. The upper layer model is used to coordinate market transactions between different provinces, while the lower layer model is used for clearing calculations within the provincial market, ensuring optimal resource allocation and market fairness. Next, this study uses the mixed integer linear programming (MILP) algorithm to solve the model, in order to improve computational efficiency and stability. At the same time, a penalty factor is introduced to regulate market behavior, ensuring the convergence of the model and the rationality of the results. The experimental results show that the coupled clearing model reduced the average total electricity cost by about 5.4% within 10 days, from 11.45 million yuan to 10.6 million yuan, and increased the inter provincial electricity dispatch by about 4.2%, significantly improving the inter provincial utilization efficiency of electricity resources. It also increased the consumption of renewable energy in the intra provincial market by about 10%, verifying its advantages in improving resource allocation and market fairness.

关键词： Couplings Renewable energy sources Costs Computational modeling Electricity Electricity supply industry Computational efficiency mixed integer linear programming Resource management Optimization

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MILP-Based Dispatch and Network Topology Optimization Through Bus Splitting: a Preliminary Analysis for Grid Congestion Management

MILP-Based Dispatch and Network Topology Optimization Throug...

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IEEE Symposium on Systems and Information Engineering Design, SIEDS

作者： Pee Jay N. Gealone Adonis Emmanuel D.C. Tio University of the Philippines Diliman Electrical and Electronics Engineering Institute Quezon City Philippines Concurrently serves as a faculty of the Electrical Engineering Department Bicol University College of Engineering Legazpi City Albay Philippines

ISBN: (数字)9798331535759

ISBN: (纸本)9798331535766

The UN Sustainable Development Goals emphasize the necessity for sustainable, affordable, clean energy sources. This call has prompted many countries to set more ambitious objectives for transforming their energy mix to be primarily, if not entirely, composed of renewable energy sources. Integrating high levels of variable non-dispatchable renewable energy (VRE) with increased variable demand poses significant challenges in grid congestion management. The traditional approach to congestion management necessitates infrastructure investments to enhance line and substation capacities. Emerging technologies, such as grid-enhancing technologies and dynamic line rating, show promise but require time and investment. Because of this, there is growing interest in exploring topology reconfiguration, which utilizes existing line-switching and/or bus-splitting options as a tool for congestion management. This paper shows the preliminary analysis of the optimization model proposed that co-optimizes generation dispatch and network topology by incorporating the substation bus-splitting model into a mixed-integer linear programming problem. To achieve this, a DC power flow optimization model is developed to address congestion by (1) topology reconfiguration, (2) dispatch optimization, and (3) their combination. The paper used a simple IEEE 6-bus operated with 72-hour dispatch scenarios representing maximum VRE, average VRE, and minimum VRE output to demonstrate how the model works. These case studies demonstrate scenarios where congestion can be mitigated by reconfiguring the network through bus-splitting while minimizing VRE curtailment. The simulation indicated that by using bus-splitting in topology optimization, up to $50 \%$ of congestion scenarios can be resolved, and by co-optimizing it with optimal dispatch, all congestion scenarios can be addressed without load shedding. This work showed that treating static facilities such as the topology as dispatchable assets can be a p

关键词： Substations Network topology Optimization models Load shedding Topology mixed integer linear programming Sustainable development Optimization Investment Load flow

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High speed calculation method using convolution for calculating normal and disaster costs of buildings with energy generation and storage facilities

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ELECTRONICS AND COMMUNICATIONS IN JAPAN 2023年第3期106卷 e12407-e12407页

作者： Kinoshita, Sota Yamaguchi, Nobuyuki Kimura, Yuta Sato, Fuyuki Otani, Shinichiro Tokyo Univ Sci Dept Elect Engn Tokyo Japan Mitsubishi Electr Corp Informat Technol R&D Ctr Kamakura Kanagawa Japan

In recent years, resilience-enhanced building buildings have been attracting increasing attention, in which photovoltaic (PV) power generation and storage batteries are installed in office buildings to continue operations even during a grid outage. PV power generation and storage batteries can be introduced to office buildings to continue commercial operations in the case of grid outages. When introducing PV power generation and storage batteries into a building, the total cost, which is the sum of the equipment installation cost and the damage cost in the event of a disaster, is crucial. When installing PV power generation and storage batteries in a building and calculating the total cost of using these facilities in the event of a disaster, it is necessary to consider the uncertainty of power demand and the amount of power generated by PV power generation. Monte Carlo Simulation is a method to consider uncertainty. However, it has a problem that the combination of conditions becomes enormous, and the calculation load is high when the total cost is calculated. Therefore, in this study, we propose convolution as a method to reduce the computational load generated when calculating the probability distribution of the total cost generated by strengthening the resilience of the building.

关键词： mixed integer linear programming Monte Carlo simulation photovoltaic power generation resilience storage battery

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Optimization of wireless sensor networks deployment with coverage and connectivity constraints

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ANNALS OF OPERATIONS RESEARCH 2021年第1-2期298卷 183-206页

作者： Elloumi, Sourour Hudry, Olivier Marie, Estel Martin, Agathe Plateau, Agnes Rovedakis, Stephane UMA ENSTA ParisTech F-91762 Palaiseau France Telecom ParisTech LTCI 46 Rue Barrault F-75013 Paris France Conservatoire Natl Arts & Metiers CEDRIC EA 4629 292 Rue St Martin F-75003 Paris France

Wireless sensor networks have been widely deployed in the last decades to provide various services, like environmental monitoring or object tracking. Such a network is composed of a set of sensor nodes which are used to sense and transmit collected information to a base station. To achieve this goal, two properties have to be guaranteed: (i) the sensor nodes must be placed such that the whole environment of interest (represented by a set of targets) is covered, and (ii) every sensor node can transmit its data to the base station (through other sensor nodes). In this paper, we consider the Minimum Connected k-Coverage (MCkC) problem, where a positive integer k >= 1 defines the coverage multiplicity of the targets. We propose two mathematical programming formulations for the MCkC problem on square grid graphs and random graphs. We compare them to a recent model proposed by Rebai et al. (Comput Oper Res 59:11-21, 2015). We use a standard mixed integer linear programming solver to solve several instances with different formulations. In our results, we point out the quality of the LP-bound of each formulation as well as the total CPU time or the proportion of solved instances to optimality within a given CPU time.

关键词： Wireless sensor networks Grid networks Random graphs Sensor deployment Minimum connected k-coverage mixed integer linear programming Formulations

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A multi-period multi-criteria replacement and rejuvenation planning of underground cables in urban distribution networks

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INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 2023年第1期149卷

作者： Milosevic, Nikola D. Popovic, Zeljko N. Kovacki, Neven, V Power Distribut Co Serbia Segedinski Put 22 Subotica 24000 Serbia Univ Novi Sad Fac Tech Sci Trg Dositeja Obradov 6 Novi Sad 21000 Serbia

This paper presents an approach for determining the best multi-period reliability improvement plan in urban distribution networks by cable replacement and rejuvenation considering network expansions/changes in the planning period. It determines the number and locations of cables in the network that need to be replaced or rejuvenated in each year of the considered planning period to fulfill a decision-maker's goal. The goal considered in this paper is to achieve the desired balance between the improvement of reliability indices (SAIFI, SAIDI, ASIDI) and the costs of replacement and rejuvenation, considering budgetary limitations. This goal is achieved by applying the proposed multi-criteria mixed-integer linear programming (MILP) model, which determines a set of noninferior solutions (replacement and rejuvenation plans) in each of the considered periods. These plans are then used within the proposed multi-criteria dynamic programming (MCDP) algorithm to generate a set of multi -period plans and determine the best multi-period cable replacement and rejuvenation plan. The comparison (ranking) of plans within the proposed MCDP is performed using a multiple-criteria decision making technique for order preference by similarity to ideal solution (TOPSIS). This technique enables the consideration of different preferences of the decision maker regarding the levels of improvement of the reliability indices in the network.

关键词： Urban distribution network Reliability improvement Rejuvenation Replacement Multi -criteria Multi -period mixed integer linear programming Dynamic programming

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An MILP Approach Based Optimization Techniques for Offshore Wind Farms Electrical Collector Systems

An MILP Approach Based Optimization Techniques for Offshore ...

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2025 International Conference on Electrical Automation and Artificial Intelligence, ICEAAI 2025

作者： Huang, Lijuan Hou, Ting Pan, Zhen Cheng, Min Zhang, Yining Xin, Qingming Guangxi Power Grid Co. Ltd China Southern Power Grid Co. Ltd Guangxi Nanning530000 China Electric Power Research Institute Co. Ltd China Southern Power Grid Co. Ltd Guangdong Guangzhou510000 China

ISBN: (纸本)9798331506797

The sizing and placement of the lines between the offshore substation (OS) and the wind turbines (WTs) are optimized using the mixed integer linear programming-based approach to large-scale offshore wind farm collector system planning (OWF-CSP) that we offer in this work. In order to guarantee the radiality of the topology of the offshore wind farm's collector system and expedite the solution process, we discover that the problem is comparable to distribution system planning, where topological constraints from Distribution Network Extension Planning (DNEP) are implemented. The effectiveness of the proposed method is demonstrated by a case study based on an OWF with 42 fixed-location WTs. The OWF-CSP approach suggested in this paper reduces the computational time with the aid of radiality constraints and lowers the investment cost and power loss on the cables in comparison to the conventional design. © 2025 IEEE.

关键词： Distribution Network Extension Planning mixed integer linear programming offshore wind farm

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