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IEEE Region 10 Conference

作者： Han Zhonghui Cheng Tao Zhou Yifan Zhang Peng State Grid Hunan Elect Power Co Changsha 410007 Hunan Peoples R China Tsinghua Univ Dept Elect Engn State Key Lab Power Syst Beijing 100084 Peoples R China

ISBN: (纸本)9781479986415

This paper focus on the multi-objective optimized scheduling for power system composed of thermal power, hydro power and wind power. According to the characteristics of hydro-thermal-wind power system, a multi-objective model is proposed with the objective to optimize the system operation cost, pollutant emission of thermal power and the net loss of power system, taking the operation constraints of each type power generator and the security requirements of the whole system into consideration. The pareto front of this multi-objective problem can be get by using CPLEX12.4. The validity of the proposed model is proved in IEEE 39-bus system. Also, some practical operation strategies for hydro-thermal-wind power system are proposed based on the pareto front.

关键词： hydro-thermal-wind power system multi-objective optimal scheduling MOPSO

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multi-objective optimal scheduling of Microgrid Integrated Energy Storage under Uncertain Scenarios 4

Multi-objective Optimal Scheduling of Microgrid Integrated E...

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4th IEEE New Energy and Energy Storage System Control Summit Forum, NEESSC 2024

作者： Lan, Tianxiao Fu, Jiajia Dong, Xuze Wu, Haige Qi, Zhiyuan Inner Mongolia University College of Electronic Information Engineering Hohhot China

ISBN: (纸本)9798350389012

The development of microgrids aims to meet the basic requirements of power supply while improving economic and environmental protection benefits. Energy storage devices play an important role in balancing power fluctuations of microgrids caused by renewable energy sources and load uncertainty. This paper proposed a multi-objective scheduling method for microgrids contain energy storage to minimize both operation and maintenance costs as well as environmental pollution costs. An improved non-dominated sorting genetic algorithm II (NSGA-II) is proposed to solve the model. A penalty ranking mechanism is introduced in the improved NSGA-II algorithm, which is able to reach the optimal solution faster. Meanwhile, a fast forward elimination way based on probabilistic distance is used to obtain renewable energy typical scenarios. Simulation results verify the viability of the proposed method. © 2024 IEEE.

关键词： improved NSGA-II method microgrid multi-objective optimal scheduling scenario generation

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multi-objective optimal scheduling of Virtual Power Plants Considering Cloud-Edge Collaboration 3

Multi-Objective Optimal Scheduling of Virtual Power Plants C...

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3rd IEEE International Conference on Electrical Engineering, Big Data and Algorithms, EEBDA 2024

作者： Chen, Kun Sun, Kaiyuan Chen, Haifeng Guan, Zhe Guangzhou Power Supply Bureau Guangdong Power Grid Co. Ltd. Csg Guangzhou510000 China

ISBN: (纸本)9798350380989

In order to effectively improve the operating economy and reliability of virtual power plants, this paper constructs a multi-objective optimal scheduling with dual consideration of energy and information. In the energy aspect, the economy of a single virtual power plant is considered, and the scheduling model is constructed with the goal of minimizing the power generation cost. In the information aspect, the cloud-edge synergy of computing resources in the scheduling process of multi-virtual power plant is taken into account, and the scheduling model is constructed with the goal of minimizing the delay of the cloud-edge system. Finally, the improved particle swarm algorithm is used to solve the model, and the examples verify that the algorithm is adapted to the scheduling problem in the virtual power plant scenario, so that it has the ability to solve the scheduling problem quickly. © 2024 IEEE.

关键词： Cloud-edge collaboration Improved particle swarm algorithm multi-objective optimal scheduling Virtual power plants

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Real-Time Peak Valley Pricing Based multi-objective optimal scheduling of a Virtual Power Plant Considering Renewable Resources

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ENERGIES 2022年第16期15卷

作者： Pandey, Anubhav Kumar Jadoun, Vinay Kumar Sabhahit, Jayalakshmi N. Manipal Acad Higher Educ Manipal Inst Technol Dept Elect & Elect Engn Manipal 576104 India

In the era of aiming toward reaching a sustainable ecosystem, the primary focus is to curb the emissions generated by non-conventional resources. One way to achieve this goal is to find an alternative to traditional power plants (TPP) by integrating various distributed energy resources (DERs) via a Virtual Power Plant (VPP) in modern power systems. Apart from reducing emissions, a VPP enhances the monetary benefits to all its participants, including the DER owners, participants, and utility personnel. In this paper, the multi-objective optimal scheduling of the VPP problem considering multiple renewable energy resources has been solved using the multi-objective black widow optimization (MOBWO) algorithm. Renewable resources consist of solar PV modules, wind turbines, fuel cells, electric loads, heat-only units, and CHP units. The weighting factor method was adopted to handle the multi-objective optimal scheduling (MOOS) problem by simultaneously maximizing profit and minimizing emission while satisfying the related constraints. In this research, a peak valley power pricing strategy is introduced and the optimal scheduling of the VPP is attained by performing a multi-objective scheduling strategy (MOSS), which is day-ahead (on an hourly basis) and 15-min based (for a one-day profile), to observe the behavior of the anticipated system with a better constraint handling method. This algorithm is capable of dealing with a complex problem in a reduced computational time, ensuring the attainment of the considered objective functions. The numerical results obtained by the MOBWO algorithm after 100 independent trials were compared with the latest published work showing the effectiveness and suitability of the developed system.

关键词： virtual power plant renewable energy resources black widow optimization multi-objective optimal scheduling peak valley pricing

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multilayer entropy-weighted TOPSIS method and its decision-making in ecological operation during the subsidence period of the Three Gorges Reservoir

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SCIENTIFIC REPORTS 2025年第1期15卷 1-16页

作者： Ai, Xueshan Yu, Yangxin Liang, Zhiming Shi, Xuanyu Cao, Rui Zhang, Xiaoke Wuhan Univ State Key Lab Water Resources Engn & Management Wuhan 430072 Peoples R China Wuhan Univ Hubei Key Lab Water Syst Sci Sponge City Construct Wuhan 430072 Peoples R China China Yangtze Power Co Ltd Hubei Key Lab Intelligent Yangtze & Hydroelect Sci Yichang 443000 Peoples R China China Three Gorges Corp River Basin Complex Adm Ctr Yichang 443000 Peoples R China

Coordinating the downstream ecological demand and the power generation demand of hydropower stations is an important task in the operation of reservoirs, and how to evaluate the ecological satisfaction of the scheduling process is a difficult problem that needs to be solved urgently. A multi-objective optimal reservoir scheduling model was constructed to coordinate the spawning flow demand of " Four Major Chinese Carps";The model takes the maximum power generation and the maximum membership degree of downstream river ecological water demand as the objective functions, and uses the dynamic programming multi-objective solution algorithm based on penalty factors to solve the problem, and obtains the non-inferior solution set in each scenario. The multilayer entropy-weighted TOPSIS method was used to study the non-inferior solution of the multi-objective scheduling model of the Three Gorges Reservoir, and the satisfactory solution ranking of the river flow rise process, ecological flow-related requirements, and power generation water requirements was obtained under the four schemes including 4d similar to 7d, which improved the reliability of the evaluation results and made up for the shortcomings of the traditional TOPSIS method in terms of hierarchy and weight science. The research results of this paper can provide a reference for decision-making on the ecological management of the spawning period of the " Four Major Chinese Carps" in the Three Gorges Reservoir of the Yangtze River.

关键词： Ecological operation multi-objective optimal scheduling Non-inferior solution set multilayer entropy-weighted TOPSIS method Four Major Chinese Carps

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optimal scheduling of green heating systems in buildings considering economy and exergy efficiency

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ENERGY AND BUILDINGS 2024年 323卷

作者： Dai, Yuanyuan Tian, Jianyan Liu, Shuwei Ji, Zhengxiong Taiyuan Univ Technol Coll Elect & Power Engn Taiyuan 030024 Peoples R China

Green heating in buildings is of great significance to global energy conservation and emission reduction, and the design of optimal scheduling models is the key to achieve cost reduction and efficiency improvement in heating systems. For the building heating system containing multiple heterogeneous energy sources such as solar energy, air energy and electricity, a multi-objective optimal scheduling model is established with the goal of maximizing the exergy efficiency and minimizing the economic cost of the system, taking into account the quality difference of energy in the conversion process. Regarding the nonconvex and nonlinear constraints in the scheduling model, the incremental linearization method and Big-M method are used to linearize the transformation, and obtain the multi-objective mixed-integer linear programming model. Further, the epsilon-constraint method is used to solve the Pareto frontier of multi-objective optimization and the technique for order preference by similarity to ideal solution (TOPSIS) method is used to make decision. Finally, the simulation study of the model is carried out, and the results show that the proposed multi-objective optimal scheduling can balance the system operation economy and exergy efficiency compared with the belief rule base and evidential reasoning (BRB-ER) method, and the system's daily economic cost are reduced by 9.66 %, 9.94 % and 17.24 %, respectively, and the system's average daily coefficient of performance (COP) are improved by 4.66 %, 14.05 % and 13.22 %, respectively, on three typical days, it is verified that the proposed optimal scheduling model has better economy and exergy efficiency. The proposed multi-objective optimal scheduling model introduces exergy efficiency rather than energy efficiency as one of the optimization objectives of the heating system and reasonably solves the optimization model, which can provide a new idea and reference for the multi-objective optimal scheduling of the green heati

关键词： Heating system multi-objective optimal scheduling Economic costs Exergy efficiency Peak shaving and valley filling

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Cloud control for IIoT in a cloud-edge environment

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Journal of Systems Engineering and Electronics 2024年第4期35卷 1013-1027页

作者： YAN Ce XIA Yuanqing YANG Hongjiu ZHAN Yufeng School of Automation Beijing Institute of TechnologyBeijing 100081China School of Electrical and Information Engineering Tianjin UniversityTianjin 300072China

The industrial Internet of Things(IIoT)is a new indus-trial idea that combines the latest information and communica-tion technologies with the industrial *** this paper,a cloud control structure is designed for IIoT in cloud-edge envi-ronment with three modes of *** 5G based IIoT,the time sensitive network(TSN)service is introduced in transmission network.A 5G logical TSN bridge is designed to transport TSN streams over 5G framework to achieve end-to-end *** a transmission control protocol(TCP)model with nonlinear disturbance,time delay and uncertainties,a robust adaptive fuzzy sliding mode controller(AFSMC)is given with control rule *** workflows are made up of a series of subtasks that are linked by the dependencies between sensor datasets and task *** workflow scheduling is a non-deterministic polynomial(NP)-hard problem in cloud-edge *** adaptive and non-local-convergent particle swarm optimization(ANCPSO)is designed with nonlinear inertia weight to avoid falling into local optimum,which can reduce the makespan and cost *** and experiments demonstrate that ANCPSO has better performances than other classical algo-rithms.

关键词： 5G and time sensitive network(TSN) industrial Internet of Things(IIoT)workflow transmission control protocol(TCP)flows control cloud edge collaboration multi-objective optimal scheduling

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multi-objective solution and decision-making framework for coordinating the short-term hydropeaking-navigation-production conflict of cascade hydropower reservoirs

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JOURNAL OF CLEANER PRODUCTION 2023年 422卷

作者： Ma, Xiangyu Liao, Shengli Liu, Benxi Zhao, Hongye Cheng, Chuntian Su, Huaying Dalian Univ Technol Inst Hydropower & Hydroinformat Dalian 116024 Peoples R China Guizhou Power Grid Co Ltd Elect Power Dispatching Control Ctr Guiyang 550002 Guizhou Peoples R China

The transformation of energy structure motivates hydropower to participate in peak shaving operations for grid stability, which conflicts with the multiple uses of cascade hydropower reservoirs. To coordinate the principal contradictory tasks of peak shaving, ship navigation, and power generation in day-ahead scheduling, a mixed integer linear programming model for the short-term multi-objective optimal scheduling is constructed. Specifically, a novel power release-based indicator is adopted to describe the navigation objective, while the minimization of the peak-valley difference of the residual load and the total water released are taken as the other two objective functions. Constraint aggregation and rectangular meshing methods are employed to handle the challenging nonlinear and nonconvex constraints. Subsequently, the Normalized Normal Constraint method, integrated with the mathematical optimization solver Gurobi, generates a set of well-distributed Pareto solutions, each representing a scheduling scheme. Finally, the Combined Weighting Technique for Order Preference by Similarity to Ideal Solution is utilized as a decision-maker to trade off and determine a compromise solution for final implementation. Case studies on the cascade hydropower reservoirs of the Wujiang River in China demonstrate that the proposed model can adequately characterize the demands of various stakeholders, and the suggested framework can obtain an even and extensive Pareto front, mediate conflicts, and make reasonable decisions. Compared to the original peak-shaving scheme, the finalized compromise scheme reduces the peak shaving effect by just 27.82% but offers simultaneous boosts of 96.54% in navigation benefits and 10.88% in power generation benefits. Consequently, the presented framework can be a promising alternative for conflict resolution of cascade hydropower reservoirs.

关键词： multi-objective optimal scheduling Peak shaving Cascade hydropower reservoirs Normalized normal constraint Mixed integer linear programming CW-TOPSIS

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optimal reservoir operation based on hydrological and hydraulic methods incorporating the multiple water replenishment process

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JOURNAL OF CLEANER PRODUCTION 2020年 276卷

作者： Mao, Yingzhu Huang, Juping Li, Ran Huang, Wendian Wang, Qingguo Feng, Jingjie Sichuan Univ State Key Lab Hydraul & Mt River Engn Chengdu Sichuan Peoples R China

A reservoir usually functions as multi-objectives. Different objective has various requirement in water volume and temporals process due to the fact that some objectives require different constant base flow in different months and some objectives demand ephemeral flood pulse. How to balance reservoir functioning and water allocation of multiple targets has become increasingly significant at present. In the past, the multi-objectives operation was usually designed based on water quantity balance, neglecting the coupling with the hydrodynamic process. Sometimes the coupling is so important for some ecological factors and the neglecting may result in failure to meet the hydraulic requirements of the downstream ecological environment. By coupling the hydrologic and hydrodynamic methods, an integrated reservoir model for multiple-objectives optimal operation was presented including water balance model, one-dimensional unsteady flow model, two-dimensional depth-averaged model and ecological baseflow model. The different process demands include water allocation at the dam site, unsteady flow process at different sections downstream the dam site. Taking a reservoir in northern China as an example, the minimum change of the hydrological process in the river mouth section was set as the objective function for the optimal operation. Regarding the demand for aquatic organisms, the low and high baseflow schemes were suggested by the comprehensive use of different ecological flow methods (the Tennant method, the flow duration curve method and the wetted perimeter method). According to the ecological flooding during the wetland water supplement, the Wetland Water Replenishment Model was applied to calculate the replenishment process under different flood cases. The Lake Water Replenishment Model was used for flow scheduling of the downstream lake. Regarding the wet years, the objective functions at the river mouth section were 16.0% with the low baseflow scheme and 15.5% with the

关键词： Ecological operations multi-objective optimal scheduling River baseflow Wetland replenishment Lake water replenishment Flood pulse

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