scholarly journals Research on Optimization of Linkage Operation of Integrated Energy System in Industrial Parks based on Chaotic Particle Swarm Algorithm

2021 ◽  
Vol 245 ◽  
pp. 01052
Author(s):  
Yang Yang ◽  
Mengjin Hu ◽  
Mengju Wei ◽  
Yongli Wang ◽  
Minhan Zhou ◽  
...  
Keyword(s):  
Particle Swarm ◽  
Clean Energy ◽  
Energy System ◽  
Utilization Efficiency ◽  
Particle Swarm Algorithm ◽  
Energy Structure ◽  
Industrial Park ◽  
Industrial Parks ◽  
Integrated Energy System ◽  
Swarm Algorithm

Industrial parks cover a variety of production capacities and energy-consuming entities, with large load demand and complex energy-using structure, and common problems such as low energy utilization efficiency and unreasonable energy structure. The construction of an integrated energy system (IES) with a combined cooling, heating and power system as the core unit in the industrial park is of great significance for achieving reliable, efficient and clean energy use in the park. Therefore, this article is based on the integrated energy system of the industrial park, aims at the lowest total cost of park operators, and considers the constraints of grid node balance, equipment output and energy storage equipment, and constructs source-grid-load-storage linkage operation optimization model, and build a chaotic particle swarm algorithm (CPSO) to solve the model. Finally, a typical industrial park in my country is taken as an example to analyze the scientificity of the model.

scholarly journals Research on Optimal Design and Control Method of Integrated Energy System Based on Improved Cloud Adaptive Particle Swarm

2021 ◽  
Vol 257 ◽  
pp. 02009
Author(s):  
Peng Ye ◽  
Shuo Yang ◽  
Feng Sun ◽  
Mingli Zhang ◽  
Na Zhang
Keyword(s):  
Global Optimization ◽  
Control Method ◽  
Particle Swarm ◽  
Energy Coupling ◽  
Energy System ◽  
Particle Swarm Algorithm ◽  
Output Constraints ◽  
Integrated Energy System ◽  
Swarm Algorithm ◽  
And Control

In order to rationally design the capacity of each energy coupling unit of the integrated energy system, effectively coordinate and optimize the control of the integrated energy system equipment. This paper proposes an improved cloud adaptive particle swarm algorithm design control method. First, three busbars and multi-energy coupling equipment models based on electric, thermal, and gas loads are established, and then the model has better global optimization capabilities and defenses. Then, an improved cloud adaptive particle swarm algorithm with better global optimization capabilities and anti-premature convergence characteristics is used to optimize the annual economic optimization model established to meet the power balance constraints of each bus and energy coupling equipment. Finally, under the conditions of output constraints and system energy purchase constraints, taking a typical park as an example, the simulation verifies the effectiveness of the method proposed in this paper in the optimization design and control operation of the integrated energy system.

Regional integrated energy system schemes selection based on risk expectation and Mahalanobis-Taguchi system

2021 ◽  
pp. 1-18
Author(s):  
Jiahang Yuan ◽  
Yun Li ◽  
Xinggang Luo ◽  
Lingfei Li ◽  
Zhongliang Zhang ◽  
...  
Keyword(s):  
Energy Demand ◽  
Choquet Integral ◽  
Subjective Evaluation ◽  
Risk Attitude ◽  
Energy System ◽  
Energy Utilization ◽  
Utilization Efficiency ◽  
Energy Structure ◽  
Fuzzy Measures ◽  
Integrated Energy System

Regional integrated energy system (RIES) provides a platform for coupling utilization of multi-energy and makes various energy demand from client possible. The suitable RIES composition scheme will upgrade energy structure and improve integrated energy utilization efficiency. Based on a RIES construction project in Jiangsu province, this paper proposes a new multi criteria decision-making (MCDM) method for the selection of RIES schemes. Because that subjective evaluation on RIES schemes benefit under criteria has uncertainty and hesitancy, intuitionistic trapezoidal fuzzy number (ITFN) which has the better capability to model ill-known quantities is presented. In consideration of risk attitude and interdependency of criteria, a new decision model with risk coefficients, Mahalanobis-Taguchi system and Choquet integral is proposed. Firstly, the decision matrices given by experts are normalized, and then are transformed to minimum expectation matrices according to different risk coefficients. Secondly, the weights of criteria from different experts are calculated by Mahalanobis-Taguchi system. Mobius transformation coefficients based on interaction degree are to calculate 2-order additive fuzzy measures, and then the comprehensive weights of criteria are obtained by fuzzy measures and Choquet integral. Thirdly, based on group decision consensus requirement, the weights of experts are obtained by the maximum entropy and grey correlation. Fourthly, the minimum expectation matrices are aggregated by the intuitionistic trapezoidal fuzzy Bonferroni mean operator. Thus, the ranking result according to the comparison rules using the minimum expectation and the maximum expectation is obtained. Finally, an illustrative example is taken in the present study to make the proposed method comprehensible.

scholarly journals Evaluation Model of Low-Carbon Circular Economy Coupling Development in Forest Area Based on Radial Basis Neural Network

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Chang Liu
Keyword(s):  
Neural Network ◽  
Circular Economy ◽  
Carbon Emission ◽  
Evaluation Model ◽  
Particle Swarm ◽  
Particle Swarm Algorithm ◽  
Energy Structure ◽  
Low Carbon ◽  
Ecological Structure ◽  
Swarm Algorithm

In this paper, we study the radial neural network algorithm for low-carbon circular economy in forest area, design a coupled development evaluation model, study its algorithmic ideas operation mode and the update formula obtained by standard algorithm, and finally optimize the RBF neural network by particle swarm algorithm. After an in-depth analysis of the particle swarm algorithm, an improved particle swarm algorithm is proposed to improve the search accuracy and capability of the algorithm by nonlinearly adjusting the inertia weights and introducing the average extreme value factor, in response to the problems of premature convergence and poor search capability that appear in the particle swarm algorithm. Through the analysis and evaluation of the interaction between industrial ecosystem and carbon emission, the main influencing factors of carbon emission are identified, and the size and magnitude of the influence of economic growth, industrial structure, energy intensity, and energy structure on carbon emission are determined; the current situation of the industrial ecological structure is evaluated, and the direction of optimization and adjustment of industrial economic structure, energy structure, and ecological structure is clarified. We construct a multidimensional multiconstraint multimodel industrial ecological structure optimization prediction model, set the development scenarios of economy and society, and optimize the prediction of low-carbon industrial ecological structure in forest areas; based on the simulation analysis of the prediction results, we propose the direction of industrial ecological structure adjustment and the path of industrial ecological system construction.

Dynamic simulation of wind field in three-dimensional display space considering particle swarm algorithm fuzzy logic

2021 ◽  
pp. 1-6
Author(s):  
Honglei Xu ◽  
Linhuan Wang
Keyword(s):  
Fuzzy Logic ◽  
Dynamic Simulation ◽  
Wind Field ◽  
Three Dimensional ◽  
Measurement Data ◽  
Particle Swarm ◽  
Particle Swarm Algorithm ◽  
Three Dimensional Display ◽  
Swarm Algorithm ◽  
Synchronous Measurement

In order to improve the accuracy of dynamic detection of wind field in the three-dimensional display space, system software is carried out on the actual scene and corresponding airborne radar observation information data, and the particle swarm algorithm fuzzy logic algorithm is introduced into the wind field dynamic simulation process in three-dimensional display space, to analyze the error of the filtering result in detail, to process the hurricane Lily Doppler radar measurement data with the optimal adaptive filtering according to the error data. The three-dimensional wind field synchronous measurement data obtained by filtering was compared with three-dimensional wind field synchronous measurement data of the GPS dropsonde in this experiment, the sea surface wind field measurement data of the multi-band microwave radiometer, and the wind field data at aircraft altitude.

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