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An optimal dispatch strategy of off-grid park integrated energy system considering source volatility

ENERGY REPORTS 2024年 12卷 1597-1607页

作者： Zhao, Yuyang Yang, Zhen Guo, Yingjun Song, Haiyun Sun, Hexu Hebei Univ Sci & Technol Sch Elect Engn Shijiazhuang 050018 Peoples R China Hebei Engn Lab Wind Power & PV Coupling Hydrogen P Shijiazhuang 050018 Peoples R China

An off-grid integrated energy system (IES) with hydrogen storage at park-level is proposed, utilizing wind, solar and natural gas as the main energy supply to replace fossil fuels, in order to overcome the insufficient consideration of energy source conversion and information exchange in the traditional energy system. Firstly, an IES schematic consisted with typical devices is proposed, and all the components are modelled in detail. Then, based on the renewable energy (RE) input requirements and the facility parameters, an optimal dispatch model for multi-energy conversion based on hydrogen storage has been demonstrated. In addition, an improved particle swarm optimization algorithm is also introduced to improve the strategy. Combined with the environmental characteristics, the multi-objective solution with the lowest economic cost and environmental cost, the highest energy supply reliability and energy efficiency as the optimization objectives is determined. Finally, a case study is conducted using the practical data of the Chongli Large-Scale Wind-Solar Complementary Coupled Hydrogen Production System Application Demonstration Project to validate the feasibility of the study under real conditions. The result shows that the RE consumption rate is greater than 99 % under the premise of considering the environmental cost and ensuring the operation reliability, which can effectively improve the operation economy and user economy of the power grid

关键词： Park integrated energy system multi-objective function Particle swarm optimization Hydrogen energy System optimal dispatch

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An automatic calibration framework based on the InfoWorks ICM model: the effect of multiple objectives during multiple water pollutant modeling

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ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH 2021年第24期28卷 31814-31830页

作者： Wu, Weilong Lu, Lijun Huang, Xiangfeng Shangguan, Haidong Wei, Zhongqing Tongji Univ Coll Environm Sci & Engn State Key Lab Pollut Control & Resource Reuse Shanghai 200092 Peoples R China Fuzhou City Construct Design & Res Inst Co Ltd Fuzhou 350000 Fujian Peoples R China

An automatic calibration framework of water quality parameters for surface runoff during modeling with InfoWorks ICM was constructed. The framework is based on a genetic algorithm (GA) and fully considers the calibration sequence for multiple water pollutants, namely, total suspended solids (TSS), chemical oxygen demand (COD), total nitrogen (TN), and total phosphorous (TP). Meanwhile, four different objective functions including the Nash-Sutcliff efficiency coefficient (NSE), coefficient of determination (R-2), percentage error in the peak (PEP), and percentage bias (PBIAS) were selected as fitness evaluators for the GA. The framework was applied successfully to a specific area of Fuzhou in China, and the multi-objective results were compared with the single-objective results. The comprehensive indexes of TSS, COD, TN, and TP by multi-objective calibration were lower than that of the single-objective calibration in both scenarios. Compared with single-objective calibration, the iterations to reach the optimal value were shortened 9, 5, 13, and 15 iterations by multi-objective calibration. Therefore, the findings showed that the multi-objective function GA was more balanced and more efficient than the single-objective function GA. Then, the uncertainty of the model was evaluated by using the samples generated by automatic calibration, which provided a reliable basis for the subsequent application of the model. This framework can be applied to other programs through adjustments of the number and weight of objective functions according to the specific situation, which will make the modeling more efficient and accurate.

关键词： Urban drainage model Water quality parameters Runoff Automatic calibration multi-objective function Uncertainty analysis

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Optimum generation dispatching of distributed resources in smart grids

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INTERNATIONAL TRANSACTIONS ON ELECTRICAL ENERGY SYSTEMS 2015年第7期25卷 1297-1318页

作者： Ansarian, Meghdad Sadeghzadeh, Seyed Mohammad Fotuhi-Firuzabad, Mahmud Islamic Azad Univ Sci & Res Branch Dept Elect Engn Tehran Iran Shahed Univ Dept Elect Engn Tehran Iran Sharif Univ Technol Dept Elect Engn Tehran Iran

Increasing interest in smart grids exhibits its potential benefits for providing reliable, secure, efficient, environmental friendly and sustainable electricity from renewable energy resources. Here, reliability models of four types of renewable and hybrid distributed generation were developed. A fuzzy multi-objective function was suggested for simultaneous optimization of reliability, electricity generation cost, grid loss and voltage profile. This not only considers uncertainty of renewable energy resources but also provides smart generation dispatching. An efficient reliability index consisting of energy and interruption frequency terms was also defined. A novel hybrid heuristic optimization method based on simulated annealing and particle swarm optimization methods was proposed. These approaches were applied to the generation dispatching of a smart grid, and the results were discussed in details. Scenarios including the changes of wind speed, sun light, fuel price and weight coefficients of the objective function were analyzed. This work succeeds to model uncertainty of renewable energy resources and performs technical and economical optimization in the power generation planning. Copyright (c) 2014 John Wiley & Sons, Ltd.

关键词： renewable energy resources smart grids generation dispatching reliability multi-objective function heuristic optimization techniques

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Optimal coordination of directional overcurrent relays using NSGA-II

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ELECTRIC POWER SYSTEMS RESEARCH 2015年第Feb.期119卷 228-236页

作者： Moravej, Zahra Adelnia, Farhad Abbasi, Fazel Semnan Univ Fac Elect & Comp Engn Semnan Iran Shahrud Univ Fac Elect Engn Shahrud Iran

This paper presents a new method for coordination of directional overcurrent relays to reduce the discrimination time of the primary and backup relays, by using nondominated sorting genetic algorithm-II (NSGA-II). In order to achieve a reliable protective system, it is necessary to find a solution to avoid having large discrimination times, in addition to coordination time interval (CTI). The novelty of the paper is to reduce the discrimination time of the primary and backup relays and simultaneously reduce the operating time of primary and backup relays, by introducing a new method. In contrast to the conventional intelligent methods, the proposed method does not require weighting factors for conversion of multi-objective function into an equivalent single objective function. The effects of both near and far-end faults are considered to solve the proposed problem formulation. Also, various overcurrent relays characteristics are considered within the program to select the best of them for each relay by optimization algorithm. The proposed method is implemented in three different test cases, i.e. three, eight and IEEE 30-bus network. The results are compared with previously proposed methods. (C) 2014 Elsevier B.V. All rights reserved.

关键词： Overcurrent relay Optimal coordination Relay characteristics Discrimination time Nondominated sorting genetic algorithm multi-objective function

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Design of pressure vessels using shape optimization: An integrated approach

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INTERNATIONAL JOURNAL OF PRESSURE VESSELS AND PIPING 2011年第5-7期88卷 198-212页

作者： Carbonari, R. C. Munoz-Rojas, P. A. Andrade, E. Q. Paulino, G. H. Nishimoto, K. Silva, E. C. N. Univ Sao Paulo Escola Politecn Dept Mechtron Engn BR-05508900 Sao Paulo Brazil Univ Estado Santa Catarina Dept Mech Engn BR-89223100 Joinville SC Brazil CENPES PDP Metodos Cient Petrobras Brazil Univ Illinois Dept Civil & Environm Engn Newmark Lab Urbana IL 61801 USA Univ Illinois Dept Mech Sci & Engn Urbana IL 61801 USA Univ Sao Paulo Escola Politecn Dept Naval Architecture & Ocean Engn BR-05508900 Sao Paulo Brazil

Previous papers related to the optimization of pressure vessels have considered the optimization of the nozzle independently from the dished end. This approach generates problems such as thickness variation from nozzle to dished end (coupling cylindrical region) and, as a consequence, it reduces the optimality of the final result which may also be influenced by the boundary conditions. Thus, this work discusses shape optimization of axisymmetric pressure vessels considering an integrated approach in which the entire pressure vessel model is used in conjunction with a multi-objective function that aims to minimize the von-Mises mechanical stress from nozzle to head. Representative examples are examined and solutions obtained for the entire vessel considering temperature and pressure loading. It is noteworthy that different shapes from the usual ones are obtained. Even though such different shapes may not be profitable considering present manufacturing processes, they may be competitive for future manufacturing technologies, and contribute to a better understanding of the actual influence of shape in the behavior of pressure vessels. (C) 2011 Elsevier Ltd. All rights reserved.

关键词： Shape optimization Pressure vessel multi-objective function

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A comprehensive technique for optimal allocation of distributed energy resources in radial distribution systems

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APPLIED ENERGY 2018年 211卷 1245-1260页

作者： Quadri, Imran Ahmad Bhowmick, S. Joshi, D. Delhi Technol Univ Elect Engn Dept Delhi India

Distributed generation (DG) is a better alternative to meet power demand near the load centers than centralized power generation. Optimal placement and sizing of DGs plays a crucial role in improving the performance of distribution systems in terms of network loss reduction, voltage profile improvement, reliability of power supply and stability issues. This paper presents a comprehensive teaching learning-based optimization (CTLBO) technique for the optimal allocation of DGs in radial distribution systems to improve network loss reduction, voltage profile and annual energy savings. The proposed technique can handle mixed integer variables, is parameter independent and possesses immunity to local extrema trappings. The effectiveness of the proposed method is first validated on standard mathematical benchmark functions. It is observed to have better convergence characteristics than teaching learning-based optimization (TLBO) and quasi-oppositional teaching learning based optimization (QOTLBO). Subsequently, it is applied to optimal DG allocation in IEEE 33-bus, 69-bus and 118-bus radial distribution test systems. Both single and multi-objective formulations are considered. In addition, the selection of the optimal number of DGs in the distribution networks is also investigated and case studies are carried out. Results demonstrate that optimal allocation of DGs using the proposed technique results in marked improvement in the performance of distribution systems over TLBO and QOTLBO. The applicability of the proposed technique for DG allocation in distribution systems with practical load profiles results in further improvement in annual energy loss reduction and cost savings.

关键词： Distributed Generation (DG) Optimization multi-objective function Comprehensive teaching-learning optimization TLBO

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Optimal load balancing strategy-based centralised sensor for a WSN-based cloud-IoT framework using a hybrid meta-heuristic strategy

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INTERNATIONAL JOURNAL OF AUTONOMOUS AND ADAPTIVE COMMUNICATIONS SYSTEMS 2024年第3期17卷 247-271页

作者： Yogaraja, G. S. R. Thippeswamy, M. N. Venkatesh, K. SJC Inst Technol Dept Informat Sci & Engn Chickaballapur 562101 India Ramaiah Inst Technol Dept Comp Sci & Engn AI&ML & Cyber Secur Bangalore 560054 Karnataka India Nitte Meenakshi Inst Technol Dept Comp Sci & Engn Bangalore 560064 India

This paper is to implement a load balancing centralised server to control the wireless sensor networks (WSN) connected to internet of things (IoT) and cloud. The WSN gathers data pertaining to diverse applications and transfers it to a centralised server in the cloud through the IoT channel. Sever controls the routing of each node in the WSN through an optimal load balancing strategy. A hybrid meta-heuristic algorithm with the Forest-Cat Optimisation Algorithm (F-COA) is introduced for accomplishing a centralised load balanced strategy in the communication system. The fundamental constraints used in the proposed models are clustering parameters like distance between nodes, energy, and delay, load balancing parameters like response time, turnaround time, server load, and QoS parameters like resource utilisation, execution time, and throughput. The experimental results present superior performance through multi-objective optimisation when compared to the other approaches in terms of different constraints.

关键词： IoT internet of things cloud computing WSN wireless sensor networks optimal routing F-COA Forest-Cat Optimisation Algorithm load balancing multi-objective function

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Evaluation method of renewable energy absorptive capacity based on Monte Carlo

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INTERNATIONAL JOURNAL OF GLOBAL ENERGY ISSUES 2024年第6期46卷 603页

作者： He, Jinding Qin, Wenchao Yunnan Elect Power Dispatching Control Ctr Kunming Yunnan Peoples R China

Because the traditional assessment method of renewable energy absorptive capacity has the problems of low assessment accuracy and long assessment time, a Monte Carlo-based assessment method of renewable energy absorptive capacity is proposed. First, build a renewable energy absorptive capacity evaluation system, obtain the evaluation indicators, then analyse the renewable energy wind output characteristics, extract the characteristics of renewable energy absorptive capacity and then set the maximum renewable energy absorptive capacity, the system power balance, the minimum conventional power technology output, and the minimum production cost as the optimisation objectives to establish a multi-objective function for evaluation. Finally, under the constraint conditions, the objective function is solved by Monte Carlo method, and the solution is the evaluation result. The simulation results show that the proposed method has higher accuracy and shorter evaluation time for renewable energy absorptive capacity evaluation.

关键词： Monte Carlo renewable energy absorptive capacity wind output multi-objective function

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Robot path planning based on laser range finder and novel objective functions in grey wolf optimizer

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SN APPLIED SCIENCES 2020年第8期2卷 1-19页

作者： Toufan, Navid Niknafs, Aliakbar Shahid Bahonar Univ Kerman Dept Comp Engn Kerman Iran

Mobile robots are the robots that can move through the environment and be used in many applications, including the industrial environment, planet exploration, warehousing, and daily household chores. They can be controlled by an operator, set to do some specific jobs, or work autonomously. Robot path planning is the task of an autonomous robot to move safely from one position to another. In this paper, three new objective functions are introduced in the structure of improved grey wolf optimizer (IGWO) and improved particle swarm optimization (IPSO) for the robot path planning problems. As another part of our proposed method, a reduction of laser range finder (LRF) data is performed, and the avoidance collision approach is also introduced. Robots determine the next position by using LRF data and IGWO (IPSO) algorithms in a local approach. The initial and the goal positions are predefined for each robot. Moreover, the location of static obstacles and other robots are unknown for each robot. Finally, the experimental results of the robot path planning using IGWO are compared to different algorithms. The results indicate that the proposed method performs better in determining an optimal, short, safe, and smooth path. Also, it has less power and time consumption than other methods. All the algorithms are implemented in the V-REP robot simulator.

关键词： multi robot path planning Grey wolf optimizer multi-objective function Optimal path Laser range finder V-REP robot simulator

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Configuration Designs and Parametric Optimum Criteria of an Alkaline Water Electrolyzer System for Hydrogen Production

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INTERNATIONAL JOURNAL OF ELECTROCHEMICAL SCIENCE 2011年第7期6卷 2566-2580页

作者： Zhang, Houcheng Su, Shanhe Lin, Guoxing Chen, Jincan Xiamen Univ Dept Phys Xiamen 361005 Peoples R China

An alkaline water electrolyzer system for hydrogen production and its semi-empirical equations are directly used to analyze and optimize the performance of the system. The results obtained through thermodynamic-electrochemical analysis show clearly that for such an alkaline water electrolyzer system, there exist some optimal values of the electrolyte concentration under different operating temperatures and the Joule heat resulting from the irreversibilities inside the alkaline water electrolyzer is larger than the additional heat needed in the water splitting process. Consequently, some new configurations for utilizing the surplus heat in the alkaline water electrolyzer are put forward to improve the performance of the system. The general performance of these new configurations is discussed, from which the lower bound of the operating current density is determined. In order to further optimize the characteristics of these configurations, a multi-objective function including both the efficiency and hydrogen production rate is originally put forward and used to determine the upper bound of the operating current density. The optimum criteria of main parameters and the optimally working region of the alkaline water electrolyzer system are given. In addition, the effects of some important parameters on the performance of the system are analyzed in detail.

关键词： Alkaline water electrolyzer overpotentials configuration design multi-objective function parametric optimum criterion

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