Application of continuous-time Kautz functions in the MPC formulation for standalone micro-grid control
17 Dec 2020-
TL;DR: In this paper, continuous-time Kautz functions are used in the formulation of the MPC problem to address the computational effort involved in predicting the microgrid response with a nonlinear micro-grid model.
Abstract: The model predictive controller exhibits excellent constraint and non-linearity handling capabilities But still, it is less preferred as a centralized controller in the nonlinear standalone micro-grids for two reasons One is the computational effort involved in predicting the micro-grid response with a nonlinear micro-grid model The other one is the involvement of more decision variables in the MPC problem This paper uses the approximated linear model for the forced response prediction to address the first drawback and solves the nonlinear micro-grid model for natural response prediction Continuous-time Kautz functions are used in the formulation of the MPC problem to address the second drawback The Kautz functions approximate the control trajectory of each of the inputs within the control horizon The approximation decreases the decision variables in the MPC control problem While doing so, the performance capabilities of the controller can still be conserved
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01 Jan 2023
TL;DR: In this article , Orthonormal special functions are employed for approximating the original pulse operator-based control trajectories within the control horizon, aiming to decrease the number of decision variables (optimal variables) in the optimal control problem without compromising the controller's performance.
Abstract: In the LTI-MPC and LTV-MPC formulations discussed in the previous chapters, the number of optimal variables that are to be evaluated at each sampling instant increases with an increase in the length of the control horizon Nc and the number of control inputs nip in the micro-grid model. Orthonormal special functions are employed for approximating the original pulse operator-based control trajectories within the control horizon. The approximation aims to decrease the number of decision variables (optimal variables) in the optimal control problem without compromising the controller's performance. Two kinds of special functions, namely Laguerre functions and two-parameter Kautz functions, are employed in this chapter.
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01 Jan 1994
TL;DR: In this article, the authors present a model for the power system stability problem in modern power systems based on Synchronous Machine Theory and Modelling, and a model representation of the synchronous machine representation in stability studies.
Abstract: Part I: Characteristics of Modern Power Systems. Introduction to the Power System Stability Problem. Part II: Synchronous Machine Theory and Modelling. Synchronous Machine Parameters. Synchronous Machine Representation in Stability Studies. AC Transmission. Power System Loads. Excitation in Stability Studies. Prime Mover and Energy Supply Systems. High-Voltage Direct-Current Transmission. Control of Active Power and Reactive Power. Part III: Small Signal Stability. Transient Stability. Voltage Stability. Subsynchronous Machine Representation in Stability Studies. AC Transmission. Power System Loads. Excitation in Stability Studies. Prime Mover and Energy Supply Systems, High-Voltage Direct-Current Transmission. Control of Active Power and Reactive Power. Part III: Small Signal Stability. Transient Stability. Voltage Stability. Subsynchronous Oscillations. Mid-Term and Long-Term Stability. Methods of Improving System Stability.
13,467 citations
TL;DR: The major issues and challenges in microgrid control are discussed, and a review of state-of-the-art control strategies and trends is presented; a general overview of the main control principles (e.g., droop control, model predictive control, multi-agent systems).
Abstract: The increasing interest in integrating intermittent renewable energy sources into microgrids presents major challenges from the viewpoints of reliable operation and control. In this paper, the major issues and challenges in microgrid control are discussed, and a review of state-of-the-art control strategies and trends is presented; a general overview of the main control principles (e.g., droop control, model predictive control, multi-agent systems) is also included. The paper classifies microgrid control strategies into three levels: primary, secondary, and tertiary, where primary and secondary levels are associated with the operation of the microgrid itself, and tertiary level pertains to the coordinated operation of the microgrid and the host grid. Each control level is discussed in detail in view of the relevant existing technical literature.
2,358 citations
TL;DR: Using the model predictive control technique, the optimal operation of the microgrid is determined using an extended horizon of evaluation and recourse, which allows a proper dispatch of the energy storage units.
Abstract: This paper presents the mathematical formulation of the microgrid's energy management problem and its implementation in a centralized Energy Management System (EMS) for isolated microgrids Using the model predictive control technique, the optimal operation of the microgrid is determined using an extended horizon of evaluation and recourse, which allows a proper dispatch of the energy storage units The energy management problem is decomposed into Unit Commitment (UC) and Optimal Power Flow (OPF) problems in order to avoid a mixed-integer non-linear formulation The microgrid is modeled as a three-phase unbalanced system with presence of both dispatchable and non-dispatchable distributed generation The proposed EMS is tested in an isolated microgrid based on a CIGRE medium-voltage benchmark system Results justify the need for detailed three-phase models of the microgrid in order to properly account for voltage limits and procure reactive power support
537 citations
TL;DR: This method, which is based upon the use of orthogonal exponential functions, is carried out prin- cipally by time-domain rather than the more common frequency- domain operations.
Abstract: One of numerous available methods is described for synthesizing a network to have a specified transient response, with emphasis placed on the actual procedure of solution. This method, which is based upon the use of orthogonal exponential functions, is carried out prin- cipally by time-domain rather than the more common frequency- domain operations. It enjoys a broader applicability than most other solutions to the transient synthesis problem, each of which suffers from one or more of several disadvantages: lack of control over the approximation error in time; severe mathematical complexity; net- works with many more circuit elements than are necessary; or net- works conveniently realizable only in a fixed form (e.g., lossless lat- tices, resistance-capacitance chains, networks without parasitic ca- pacitance, etc.). Several examples are presented.
282 citations
TL;DR: A precise small-signal state-space model of the whole microgrid including droop controller, network, and loads is derived and genetic algorithm is introduced to search for optimal settings of the key parameters during time-domain simulation in MATLAB/Simulink.
Abstract: 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.
209 citations