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Analysis and optimization of Droop controller for Microgrid System Based on Small-Signal Dynamic Model

IEEE TRANSACTIONS ON SMART GRID 2016年第2期7卷 695-705页

作者： Yu, Kai Ai, Qian Wang, Shiyi Ni, Jianmo Lv, Tianguang Shanghai Jiao Tong Univ Dept Elect Engn Shanghai 200240 Peoples R China

Droop control strategy enables the microgrid switch between grid-connected and islanded mode flexibly, and easily realizes the "plug and play" function of distributed generation and loads, which has recently aroused great concerns. However, small disturbances may occur during the changing process and eventually yield transient oscillation, thus the focus of microgrid control is how to switch smoothly within different operation modes. In order to improve the dynamic characteristics of an inverter-based microgrid, this paper derived a precise small-signal state-space model of the whole microgrid including droop controller, network, and loads. The key control parameters of the inverter and their optimum ranges, which greatly influence the damping frequency of oscillatory components in the transient response, can be obtained through eigenvalue analysis. In addition, genetic algorithm is introduced to search for optimal settings of the key parameters during time-domain simulation in MATLAB/Simulink. Simulation results verified the effectiveness of the proposed small-signal dynamic model and optimization algorithm, and enhanced the dynamic performance of the microgrid, which can be the reference for parameter design of droop control in low voltage microgrids.

关键词： Droop controller microgrid small-signal analysis dynamic model genetic algorithms control optimization

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Decentralized-coordinated model predictive control for a hydro-power valley

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MATHEMATICS AND COMPUTERS IN SIMULATION 2013年 91卷 108-118页

作者： Florez, J. Zarate Martinez, J. Besancon, G. Faille, D. Elect France EDF R&D F-78401 Chatou France Grenoble INP Control Syst Dept GIPSA Lab UMR 5216 F-38402 St Martin Dheres France Inst Univ France Paris France

This paper aims at improving control systems for hydro-power production, by combining model predictive control techniques with decomposition-coordination methods for a global optimization over a whole hydro-power valley. It first recalls the model predictive control formulation for a centralized solution presented as the reference for comparison, and emphasizes the possible use of explicit solutions in the considered problem, making easier its practical use. It then highlights the further interest of such solutions in a decomposition-coordination approach, allowing to reduce the computational cost even more with a purpose of realtime implementation, and at the same time to take advantage of the distributed nature of the considered system. The results are illustrated on the basis of a real-data-based case-study provided by EDF1 group. (C) 2012 IMACS. Published by Elsevier B.V. All rights reserved.

关键词： Hydroelectricity control optimization Model predictive control Decomposition-coordination Case-study validation

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ROBUSTNESS optimization OF STRUCTURAL AND controlLER PARAMETERS

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JOURNAL OF GUIDANCE control AND DYNAMICS 1989年第1期12卷 89-96页

作者： LIM, KB JUNKINS, JL VIRGINIA POLYTECH INST & STATE UNIV BLACKSBURGVA 24061 TEXAS A&M UNIV COLLEGE STNTX 77843

Several novel ideas in the definition and optimization of robustness for structures and structural controllers are presented. A robustness bound attributable to Patel and Toda is developed using eigenvalue conditioning analysis. Homotopy and sequential linear programming algorithms are used in lieu of conventional nonlinear programming to implement these ideas for an illustrative example. The numerical results confirm the conservatism of the stability robustness bound but nevertheless support the hypothesis that maximizing the robustness measure does significantly increase the true robustness of a closed-loop system. The results also indicate that maximizing the stability robustness measure produces more robust designs than minimizing eigenvalue sensitivity directly.

关键词： control optimization Sequential Linear Programming Nonlinear Programming Robust Design Output Feedback Young's Modulus Structural System Frequency Domain Cholesky Factorization Linear Programming

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Experiment Investigation and control Strategies on Two-Phase Refrigerant Injection Heat Pump System for Electric Vehicle in Start-up Stage

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Journal of Thermal Science 2021年第3期30卷 828-839页

作者： QIN Fei LIU Hanzhou ZOU Huiming CHEN Deqi TIAN Changqing Key Laboratory of Low-grade Energy Utilization Technologies and Systems Ministry of EducationChongqing UniversityChongqing 400044China Beijing Key Laboratory of Thermal Science and Technology and Key Laboratory of Cryogenics Technical Institute of Physics and ChemistryChinese Academy of SciencesBeijing 100190China

Due to the poor heating performance and operating safety in low ambient temperature,traditional Air Source Heat Pump(ASHP)for Electric Vehicles(EVs)has many limits in cold region,which can be solved by the ASHP with refrigerant *** the start-up stage of EV in winter,the inlet air temperature of the in-car condenser is the same as the ambient *** this situation,the performance and control strategy of the heat pump require special *** the present study,a series of experiments were carried out on the heating performance of the Refrigerant Injection Heat Pump(RIHP)system in start-up stage of EV,at the ambient temperature from–20℃ to–5℃.The effects of compressor speed and injected refrigerant state on the heating performance of the system were discussed in *** to the results,the control strategies during start-up stage have been discussed in the end of the *** study provides a practical control strategy for the RIHP system during the start-up stage of electric vehicles,helping to efficiently operate electric vehicles in cold regions.

关键词： refrigerant injection heat pump system heating performance electric vehicle start-up stage control optimization

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Special issue on applications of variational inequality problems

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optimization AND ENGINEERING 2012年第3期13卷 371-373页

作者： Tawhid, Mohamed A. Thompson Rivers Univ Kamloops BC Canada Univ Alexandria Alexandria Egypt Egypt Japan Univ Sci & Technol Alexandria Egypt

I am very pleased to see the completion of this special issue of optimization and Engineering: Applications of Variational Inequality Problems. Over the past several decades, variational inequalities have attracted a great deal of attention from both researchers and practitioners. It is well known that variational inequalities cover diverse disciplines in partial differential equations, optimal control, optimization, mathematical programming, mechanics, finance, operations research, engineering (dynamic rigid- body model, nonlinear obstacle problems), economics equilibrium models, and science.

关键词： body model mathematical programming optimization methods Engineering inequalities Completion Partial differential equations control optimization

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Development and evaluation of a constrained optimization model for traffic signal plan transition

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TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES 2012年第1期20卷 185-198页

作者： Lee, Jisun Williams, Billy M. N Carolina State Univ Dept Civil Construct & Environm Engn Raleigh NC 27695 USA Korea Transport Inst Dept Transport Safety & Disaster Prevent Res Goyang Si 411701 Gyeonggi Do South Korea

In advanced traffic signal control systems, plan transition is the process of switching from one timing plan to another to accommodate changes in traffic demand. In traditional coordinated system operation, whether plans are set by time of day or by traffic responsive plan selection, traffic flow can be severely disrupted by the sudden changes in traffic signal timing. Although various transition methods have been developed and refined, existing transition methods are not based on optimizing operational measures of effectiveness during plan transition periods. As the first step in remedying this situation, this paper presents a non-linear mathematical model that provides constrained delay minimization through incremental and simultaneous adjustments in offset and cycle length during plan transitions. According to the simulation results, currently used transition methods tend to assign an excessive amount of green time to the main street, resulting in additional side street delay without performance improvement for the total transportation network. By contrast, the proposed transition method showed measurable improvement in delay performance under a broad range of traffic and geometric conditions. (C) 2011 Elsevier Ltd. All rights reserved.

关键词： Traffic control Signal plan transition control optimization Genetic algorithms

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Iterative Learning-Based Path optimization With Application to Marine Hydrokinetic Energy Systems

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IEEE TRANSACTIONS ON control SYSTEMS TECHNOLOGY 2022年第2期30卷 639-653页

作者： Cobb, Mitchell Reed, James Daniels, Joshua Siddiqui, Ayaz Wu, Max Fathy, Hosam Barton, Kira Vermillion, Chris Blue Origin Kent WA 98032 USA North Carolina State Univ Dept Mech & Aerosp Engn Raleigh NC 27695 USA US Air Force Washington DC 20330 USA Univ Michigan Dept Mech Engn Ann Arbor MI 48109 USA Univ Maryland Dept Mech Engn College Pk MD 20742 USA Windlift Inc Morrisville NC 27560 USA

This article presents an iterative learning control (ILC)-based approach for optimizing the flight path geometry of a tethered marine hydrokinetic (MHK) energy system. This type of system, which replaces the tower of a conventional system with a tether and a lifting body, can capture energy either through an on-board rotor or by driving a generator with tension in the tether. In the latter mode of operation, which represents the focal point of this effort, net positive energy is generated over one cycle of high-tension spool-out followed by low-tension spool-in. Because the net energy generation is sensitive to the shape of the flown path, we employ an iterative learning update law to adapt the path shape from one lap to the next. This update law is complemented with an iterative power take-off (PTO) controller, which adjusts the spooling profile at each iteration to ensure zero net spooling. We present and validate the proposed control approach in both uniform and spatiotemporally varying turbulent flow environments, based on a realistic ocean model detailed in this article. Finally, based on simulation results across a wide range of excitation levels, we perform a simulation-based assessment of convergence properties, comparing these results against bounds derived in the authors' prior work.

关键词： Poles and towers optimization Wind energy Shape Wind energy generation Heuristic algorithms Convergence Autonomous systems control optimization iterative learning control (ILC) renewable energy tethered energy systems

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Effect of Large-Eddy Simulation Fidelity on Predicted Mechanisms of Jet Noise Reduction

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JOURNAL OF PROPULSION AND POWER 2012年第2期28卷 259-268页

作者： Kim, Jeonglae Bodony, Daniel J. Freund, Jonathan B. Univ Illinois Dept Mech Sci & Engn Urbana IL 61801 USA Univ Illinois Dept Aerosp Engn Urbana IL 61801 USA

The aeroacoustic control of a Mach 1.3 turbulent jet demonstrates an unexpectedly subtle importance of accurate numerics for predicting and reducing turbulent jet noise. We observe that two nominally high-wave-number filters (as used to stabilize large-eddy simulations), one explicit that is optimized based upon an integral criterion and the other implicit with a tunable parameter, lead to significant changes in the near-field turbulence with concomitant changes in the acoustic field on the order of 2-4 dB. An apparent consequence is that an adjoint-based optimization procedure identities different controls for the two simulated jets despite similar reductions of radiated sound. This suggests that sound-generating mechanisms of the Mach 1.3 turbulent jet may be more fundamentally modified by subtle changes in numerics than previously expected.

关键词： Direct Numerical Simulation Jet Noise Reynolds Averaged Navier Stokes Shear Layers Velocity Profiles Plasma Actuator Navier Stokes Equations control optimization Jet Flow Finite Difference Scheme

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Framework for field optimization to maximize asset value

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SPE RESERVOIR EVALUATION & ENGINEERING 2005年第1期8卷 7-21页

作者： Bailey, WJ Couët, B Wilkinson, D Schlumberger Doll Res Ctr Risk & Optimizat Program Ridgefield CT USA

In this paper, we propose an optimization framework for maximizing asset value, both with and without uncertainty. We first present the methodology to treat a general control optimization in the presence of uncertainty, followed by a brief section on the optimization algorithms used. We then describe the field model example used to illustrate the application of the methodology. Through a systematic analysis of various deterministic and stochastic cases, we address the various objectives sought. Using net present value (NPV) as a measure, we also explore the valuation of advanced completions along with the returns gained from expanding surface gas-handling facilities. The method also generates an efficient frontier that can be used for risk and decision analysis. The results clearly demonstrate the value of such a framework for value maximization in planning both near- and long-term time horizons as well as providing the necessary foundation for maximizing asset value.

关键词： cost accounting Frameworks deterministic Maximize Completion optimization algorithms System analyses Uncertainty Gas surfacing control optimization Decision analysis

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Numerical simulation modelling on whole municipal solid waste incineration process by coupling multiple software for the analysis of grate speed and air volume ratio

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PROCESS SAFETY AND ENVIRONMENTAL PROTECTION 2023年 176卷 506-527页

作者： Tang, Jian Zhuang, Jiabin Aljerf, Loai Xia, Heng Wang, Tianzheng Gao, Bingyin Beijing Univ Technol Fac Informat Technol Beijing 100124 Peoples R China Beijing Lab Smart Environm Protect Beijing 100124 Peoples R China Damascus Univ Fac Sci Dept Chem Key Lab Organ Ind Damascus Syria Beijing GaoAnTun Waste Energy CO LTD Beijing 100024 Peoples R China

Uncertainties in the calorific value and composition of municipal solid waste (MSW), the variability in operations, equipment performance decline, maintenance needs, and other dynamic factors make it challenging for operational experts to accurately gauge the overall combustion impact under fluctuating conditions. There is a need for a visual numerical simulation of the full MSW incineration (MSWI) process, with a focus on the effectiveness of the grate speed and air volume ratio. Unfortunately, software like Aspen Plus struggles to visually depict the effect of typically manipulated variables such as grate speed, and it is not well-suited for simulating solid-phase combustion and flue gas treatment. In response to these challenges, our study introduces a numerical simulation method for the MSWI process using a multi-software coupling approach. This simulation method incorporates (a) the use of custom software for simulating solid-phase combustion on the grate, (b) the application of Computational Fluid Dynamics (CFD) software for gas-phase combustion in the furnace, and (c) the utilization of chemical process simulation software for non-grate solid-phase combustion. The benchmark condition was determined using real-time running data from the Beijing MSWI Power Plant. The results show that for the incinerator's third flue, flue gas G1, and flue gas G3, the relative errors between the simulated and actual values for flue gas temperature and oxygen concentration were 0.3% and 1.1%, 3.5% and 20%, and 0.2% and 20% respectively. In addition, we used eight non-benchmark conditions to study the effects of grate speed and air volume ratio. When the grate speed was gradually increased from 6 m/h to 8 m/h, O2, CO2, sulfur dioxide (SO2), sulfur trioxide(SO3), nitrogen monoxide (NO), and nitrogen oxide (NO2) at G1 had error fluctuation ranges of 5.9%-48.5%, 2.5%-11.5%, 10.42-28.57%, 7-23%, 29.10-45.52%, and 24.39-48.78%, respectively. When the primary air ratio was gradually in

关键词： Municipal solid waste incineration (MSWI) Numerical simulation Multiple software coupling Grate speed Air volume ratio control optimization

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