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Optimal sizing of hybrid Systems for Power loss Reduction and Voltage improvement using pso algorithm: Case study of Guissia Rural Grid

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ENERGY REPORTS 2022年 8卷 86-95页

作者： Djidimbele, Repele Ngoussandou, Bello-Pierre Kidmo, Dieudonne Kaoga Kitmo Bajaj, Mohit Raidandi, Danwe Univ Maroua Natl Adv Sch Engn Maroua Dept Renewable Energy Maroua Cameroon Natl Inst Technol Delhi Dept Elect Engn Delhi India Univ Maroua Natl Adv Sch Engn Maroua Dept Civil Engn & Architecture Maroua Cameroon

This work proposes a method for sizing and reducing power losses (MSRPL) of a hybrid photovoltaic and wind system (HPWS) in a radial distribution network (RDN) by developing an objective function, thanks to particles swarm optimization (pso). The constraints defined on the objective function has permitted us to size the photovoltaic generator, wind turbine and total production cost. The proposed system configuration (PSC) improved the voltage level and minimized the power losses (PL) in the radial network. The proposed pso algorithm was tested on Guissia (10 degrees 30'N, 15 degrees 18'E) rural electric grid (GREG) in the far north of Cameroon, which has a radial configuration. The integration of a battery bank allowed the system to have the power factor correction and production of active and reactive power. The test on IEEE 33-bus and IEEE 69 bus showed the robustness of the system and the reliability of the proposed method which also minimized the total cost of the system over 20 years. (c) 2022 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://***/licenses/by-nc-nd/4.0/).

关键词： Guissia rural electric grid Power loss pso algorithm Radial distribution

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Grey-box model-based demand side management for rooftop PV and air conditioning systems in public buildings using pso algorithm

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ENERGY 2024年 296卷

作者： Sun, Yue Luo, Zhiwen Li, Yu Zhao, Tianyi Dalian Univ Technol Inst Bldg Energy Dalian Peoples R China Cardiff Univ Welsh Sch Architecture Cardiff Wales Donghua Univ Coll Environm Sci & Engn Shanghai Peoples R China

As the major power consumer in buildings, Heating, ventilation and air conditioning (HVAC) systems can significantly contribute to the economical operation of the power system during the peak periods in summer or winter, by flexibly responding to the grid demands. Indoor air temperature set-point resetting is a typical passive demand response (DR) control strategy that have potentials to be widely implemented by inverter air conditioners in residential buildings. However, in the existing small and medium-size public buildings, the compressor motor of HVAC systems mostly does not allow for stepless speed changes. This means that the indoor temperature set-point resetting strategy may results in frequent on/off switching of the chiller plant, leading to a compromised lifespan. Although rooftop photovoltaic systems (PVs) are expected to be widely adopted in new buildings, their potential for peak load shaving or valley load filling has received limited investigation. This study proposes a grey-box model-based demand side management (DSM) method for variable air volume systems (VAVs) and rooftop PVs in public buildings. The DSM method utilizes the particle swarm optimization (pso) algorithm to determine optimal indoor air temperature and/or evaporator outlet water temperature set-point schedules for the VAVs, as well as optimal charging/discharging schedules for the storage battery of rooftop PVs. This approach aims to reduce the peak power demands of the integrated system without causing severe thermal discomfort, increasing chiller mechanical costs (refers to frequent on/off switching of the chiller plant in this paper), or overcharging/over-discharging of storage batteries. The results of case studies demonstrate that the strategy of co-resetting indoor air temperature - evaporator outlet water temperature set-points outperforms the indoor air temperature set-point resetting strategy in terms of both peak power demands reduction and mechanical cost saving when applie

关键词： Grey-box model Demand side management VAV system Rooftop PV system pso algorithm

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A modified pso algorithm for linear optimization problem subject to the generalized fuzzy relational inequalities with fuzzy constraints (FRI-FC)

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INFORMATION SCIENCES 2017年 418卷 317-345页

作者： Ghodousian, Amin Parvari, Maryam Raeisian Univ Tehran Dept Engn Sci Coll Engn Tehran 113654563 Iran Univ Tehran Dept Algorithms & Computat Tehran Iran

In this paper, optimization of a linear objective function subject to a generalized fuzzy relational inequalities is investigated in which an arbitrary continuous t-norm is considered as fuzzy composition, and fuzzy inequality replaces ordinary inequality in the constraints. Unlike most optimization algorithms, in fuzzy relational inequalities with fuzzy constraints (FRI-FC) we find a near-feasible solution having a better objective value than those resulting from the resolution of the similar problems with crisp (ordinary) inequality constraints. Such solutions are called super-optima in this paper. Subsequently, an algorithm is proposed to find a super-optimum with pre-specified desirable infeasibility. For this purpose, we firstly study some structural properties of the FRI-FC problem and present a new formulization that is independent of t-norms used in the constraints of the problem. This new formulation converts the primary problem into an equivalent problem with simple constraints without considering any penalty parameters. However, it is proved that the transformed equivalent problem enables our algorithm to distinguish unfavorable points and generate a sequence of solutions converging to a super-optimum under a certain sufficient condition. Finally, a modified pso is presented in which the ability of pso to solve unconstrained problems with continuous domain, the structure of the transformed problem and some fuzzy structural modifications are combined and form an efficient algorithm to solve the generalized FRI-FC problems. The modified pso algorithm has been applied to the generalized FRI-FC problem defined with ten well-known continuous t-norms. Additionally, an idea of the FRI-FC problems as outer approximators for FRI problems with ordinary inequalities is also investigated. (C) 2017 Elsevier Inc. All rights reserved.

关键词： Fuzzy relational inequalities Linear optimization t-norm pso algorithm Fuzzy constraints

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Modeling MEA with the CPA equation of state: A parameter estimation study adding local search to pso algorithm

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FLUID PHASE EQUILIBRIA 2015年 400卷 76-86页

作者： dos Santos, Leticia Cotia Tavares, Frederico Wanderley Ruiz Ahon, Victor Rolando Kontogeorgis, Georgios M. Petrobras Ctr Pesquisas & Desenvolvimento CENPES BR-21941915 Rio De Janeiro RJ Brazil Univ Fed Rio de Janeiro COPPE Programa Engn Quim BR-21945970 Rio De Janeiro RJ Brazil Univ Fed Rio de Janeiro Escola Quim BR-21949900 Rio De Janeiro RJ Brazil Univ Fed Fluminense Dept Engn Quim & Petroleo BR-24210240 Niteroi RJ Brazil Tech Univ Denmark Dept Chem & Biochem Engn Ctr Energy Resources Engn DK-2800 Lyngby Denmark

Due to the intensification of environmental constrains combined with the tendency to process crude oils with high C/H, S/H ratios and natural gas with increasing CO2/CH4 and H2S/CH4 ratios, acid gas removal from gas streams is probably the most required process in the petroleum and gas industries nowadays. Absorption with aqueous alkanolamines such as MEA, is one commonly used process for this purpose. On modeling MEA with CPA, it has been shown that only the co-volume b parameter does not present local minima near the final solution and, also, VLE data are not sufficient to estimate reliable parameters for MEA. This work proposes adding LLE information systematically in the CPA parameter estimation procedure. At first, the parameter search space is defined by the results from the pso sensitivity analysis for VLE considering the experimental error for vapor pressures and liquid densities (objective function cut off). Then, two possible methodologies are discussed: the first one uses all the possible parameter sets and check them against the LLE and VLE experimental data. The second method explicitly incorporates LLE information into the objective function and uses both pso and pso-simplex hybrid algorithm to improve the convergence and refine the final solution. With this methodology it was possible to model simultaneously LLE and VLE. The CPA was then applied for a mixture containing cross-association (MEA-water) and the results show good agreement with experimental data indicating the effectiveness of the proposed strategies. (C) 2015 Elsevier B.V. All rights reserved.

关键词： MEA Cubic plus association (CPA) Parameter estimation pso algorithm VLE LLE

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A General Robot Inverse Kinematics Solution Method Based on Improved pso algorithm

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IEEE ACCESS 2021年 9卷 32341-32350页

作者： Yiyang, Liu Xi, Jiali Hongfei, Bai Zhining, Wang Liangliang, Sun Chinese Acad Sci Key Lab Networked Control Syst Shenyang 110016 Peoples R China Chinese Acad Sci Shenyang Inst Automat Shenyang 110016 Peoples R China Chinese Acad Sci Inst Robot & Intelligent Mfg Shenyang 110169 Peoples R China Univ Sci & Technol China Dept Automat Sch Informat Sci & Technol Hefei 230026 Peoples R China Shenyang Jianzhu Univ Informat & Control Engn Dept Shenyang 110168 Peoples R China

Robots whose geometric structure does not meet the Pieper criterion are called general robots. For the inverse kinematic operation of general robots, the closed solution method cannot be solved, and the numerical solution calculation amount is too large and the singular position cannot be calculated. To solve this problem, this paper proposes an inverse kinematics calculation method based on improved particle swarm optimization (pso) algorithm and applicable to general robots. In order to avoid the particle update rate not adapting to each stage of the optimization process, a nonlinear dynamic inertia weight adjustment method based on the concept of similarity is introduced, so that the search process is more robust;in addition, to overcome the problem of local optimal solution At the same time, multiple populations are introduced to perform optimization search at the same time, and the immigration operator is proposed to increase the diversity of the particle population in the iteration. This article uses Comau NJ-220 robot for test verification, compared with the original pso and multi-subswarm algorithm, the results show that the proposed improved pso has higher algorithm stability for general robot kinematics inverse solution problems, and can greatly improve the convergence accuracy and speed. This method provides a new solution to the field of robot inverse kinematics, and provides a more efficient and stable kinematics foundation for robot motion planning.

关键词： Robots Robot kinematics Kinematics Optimization Heuristic algorithms Convergence Service robots Robot kinematics analysis pso algorithm robot inverse kinematics artificial intelligence

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Texture shape optimization induced higher load carrying capacity of sealing ring based on improved pso algorithm

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PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART J-JOURNAL OF ENGINEERING TRIBOLOGY 2023年第3期237卷 469-483页

作者： Gong, Ran Cheng, Xing Jiao, Mei Jiangsu Univ Dept Automot Engn Zhenjiang 212013 Peoples R China China North Vehicle Res Inst Beijing Peoples R China

An improved particle swarm optimization (pso) algorithm is presented to optimize the texture shape of the sealing ring in order to enhance the load carrying capacity (LCC). The shape optimization uses the unrelated generation method of the texture curves, and two splines are applied to fit the boundary of the texture to improve the continuity. The inertia factor is adjusted through the differential strategy to enhance the local optimization capacity. The optimization model is verified by two optimization cases. The optimized texture is bullet-shaped. The increase of inlet oil pressure transforms the optimized texture from the bullet shape to the inner spiral shape. In addition, the increase of the texture depth leads to the gradual elongation of the texture shape. The increase in the number of textures flattens the seal texture. The results shows that the improved pso algorithm has high global optimization ability of the texture shape for the sealing ring in the vehicle transmission through appropriate parameter settings.

关键词： Sealing ring texture shape optimization load carrying capacity pso algorithm

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Cross-coupled control for contour tracking error of free-form curve based on fuzzy PID optimized by improved pso algorithm

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MEASUREMENT & CONTROL 2022年第7-8期55卷 807-820页

作者： Ji, Wei Cui, Xiang Xu, Bo Ding, ShiHong Ding, Yi Peng, JiaQi Jiangsu Univ Sch Elect & Informat Engn XueFu Rd 301 Zhenjiang 212013 Jiangsu Peoples R China

Aiming at the free-form curve contour tracking error problem of CNC machining, a cross-coupled controller based on Fuzzy PID using an improved pso algorithm is proposed. First, the exact formulas of the linear and circular arc contour errors under a plane trajectory are derived, and an estimation method for the free curve profile error under a plane trajectory based on the principle of approximate approximation of preferred points is designed. Second, a cross-coupled controller based on Fuzzy PID using an improved pso algorithm is achieved. An improved pso algorithm, whose learning factor is adjusted with the inertia weight, is used to optimize the controller parameters and achieve contour tracking of the free curve. Finally, a two-dimensional biaxial experimental platform is used to test the proposed method. The results demonstrate that the optimal gain parameters obtained by the proposed strategy can significantly improve contour control accuracy in biaxial contour tracking tasks. The proposed contour error control scheme can achieve not only a nearly perfect contouring error estimation, but also an obvious promotion of contouring accuracy.

关键词： CNC machining contour error cross-coupled controller fuzzy PID pso algorithm

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Optimal reactive power control of DGs for voltage regulation of MV distribution systems using sensitivity analysis method and pso algorithm

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INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 2015年 68卷 52-60页

作者： Zad, B. Bakhshideh Hasanvand, H. Lobry, J. Vallee, F. Univ Mons Dept Elect Power Engn Fac Polytech B-7000 Mons Belgium TREC Tehran Iran

This paper addresses the problem of reactive power control of distributed generation (DG) units in the medium voltage (MV) distribution systems to maintain the system voltages within the predefined limits. An efficient approach for the load flow calculation is used here which is based on the topological structure of the network. It has been formulated for the radial distribution systems. A direct voltage sensitivity analysis method is developed in this paper which is also based on the topological structure of the network and independent of the network operating points. Thus, the sensitivity matrix is calculated once with the load flow program and it is used in all the system working conditions. The problem of DGs reactive power control is formulated as an optimization problem which uses the sensitivity analysis for linearizing the system around its operating points. The objective of the optimization problem is to return the system voltages inside the permitted range by using the reactive power of DGs in an optimal way. The optimal solutions are obtained by implementing particle swarm optimization (pso) algorithm. Then, the results are verified by running a load flow considering new values of DGs reactive power. The procedure is repeated as long as a voltage violation is observed. Simulation results reveal that the proposed algorithm is capable of keeping the system voltages within the permitted limits. (C) 2014 Elsevier Ltd. All rights reserved.

关键词： Distributed generation units Voltage control Reactive power control Sensitivity analysis pso algorithm

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Learning spatially correlation filters based on convolutional features via pso algorithm and two combined color spaces for visual tracking

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APPLIED INTELLIGENCE 2018年第9期48卷 2837-2846页

作者： Touil, Djamel Eddine Terki, Nadjiba Medouakh, Saadia Univ Biskra Energy Syst Modeling Lab Biskra Algeria Univ Biskra Dept Elect Engn Biskra Algeria

Last years, we have seen an emergence of wide methods in visual object tracking topic as convolutional neural network combined with correlation filter such as hierarchical features (HCF) (Ma et al. 20). However, upon the fact that some features may cause the tracking failures, the existing methods are still suffering of handling complex object appearance changes such as fast motion, significant deformation and occlusions. Further, they learn the correlation filter in frequency domain using Fourier transform, which cause unwanted boundary effects, which severely degrade the quality of the tracking model. Moreover, these methods are incapable of dealing with the illumination variation because they rely only on RGB base for color sequences. In this paper, we propose a novel method, which addresses the pre-cited problems. As first contribution, we learn adaptively three correlation filters in the spatial domain, with hierarchical convolutional features extracted from specific layers. Indeed, we apply the Particle Swarm Optimization algorithm to solve the update model equation of the correlation filters. Second, we propose that the switching between RGB and HSV color bases, give a soft manner to handle the illumination variation. For this aim, an HSV-energy condition is presented to choose the appropriate color base resorting to the energy of the second HSV component. Extensive experiments on a common benchmark dataset, justify that the proposed method outperforms the state-of-art methods.

关键词： Convolutional neural network Correlation filters Visual tracking pso algorithm HSV RGB

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Enhancement of heat transfer of confined enclosures with free convection using blocks with pso algorithm

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APPLIED THERMAL ENGINEERING 2016年 101卷 79-91页

作者： Azimifar, A. Payan, S. Univ Sistan & Baluchestan Dept Mech Engn Zahedan 98135161 Iran

In this paper, optimal shape of cavity with change of hot walls geometry is obtained using pso algorithm. In this method near domain of hot wall is divided into similar blocks as those can either be solid or fluid. Free convection is dominant in the cavity. Continuity, momentum and energy equations are discretized by finite volume method. These equations are solved by SIMPLER algorithm. pso algorithm is used for obtaining diffusion parameters near the hot walls. Diffusion coefficients obtained from pso algorithm (non-dimensional parameters for diffusion terms in momentum and energy equations) are replaced in governing equations such a way that average Nusselt number from cold wall to be maximized. The results are obtained for range of Rayleigh numbers and different boundary conditions. Results show that psoA is able to obtain size and location of changes in hot walls. These changes can increase heat transfer from cold wall between 13% and 40% for different boundary conditions. If hot and cold walls are near together, millimeter changes are enough for acceptable percent value of increase of heat transfer, but for cases that hot wall is far from cold wall, we must attach medium or large blocks on hot wall or construct new cavities in accordance with optimized shape obtained from pso algorithm. As told, this method can be applied toconstructed cavities with attachment of rectangular fins. (C) 2015 Elsevier Ltd. All rights reserved.

关键词： Free convection Optimized shape pso algorithm

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