Steady-State Optimality Analysis of MPC Controllers

Steady-state Optimality Analysis for Investigating the Energy Optimal Operation of Representative Natural Gas Liquefaction Cycles

Modelling, Steady State Analysis and Optimization of the Catalytic Efficiency of the Triosephosphate Isomerase

Computational software for steady-state analysis and optimization of power networks is critical. Unfortunately, advances in computational technologies often take a long time to reach industry applications or never get adopted at all. This is partly due to the vast but fragmented spectrum of computational software used by the community, and the lack of an efficient, flexible, and accessible tool that facilitates the transition of new techniques and algorithms into tools that can be tested and used by power system engineers and practitioners. With the goal of filling this gap, a new open-source library has been developed. An overview of this library is presented here along with an example and experimental results that demonstrate its use, performance, and accuracy.

Steady-State Analysis and Optimization of the Unreliable M/G/1 Queueing Model Under <i>D</i>-Policy

The steady-state model, which relates the manipulated conditions to both the process and performance quantities, has been developed in this work for plasma etching process by regression analysis. Non-intrusive techniques, namely optical emission spectroscopy and laser interferometry, are employed to estimate the relative plasma species concentrations and electron energy of the process and real-time etch rate respectively in order to maintain the integrity of the etching environment. This information can be used to find the correlations and also feed into the model to track back proper operating conditions. Correlations are developed to directly relate inputs, semi-outputs and outputs in the SF/sub 6//Ar etching system. Response surface methodology is used as a basis for further modelling of nonlinear plasma etching. Results presented in this paper are compared favourably to the known discharge characteristics, experimental data and some interpretations of etching and discharge mechanism as well as the comprehensive reactor model. >

Extending fuel cell lifetime is a necessary objective for reducing fuel cell power generation cost of electricity. Capital costs comprise the most significant fraction of the cost of electricity. Reducing the frequency of fuel cell replacement can be achieved by implementing a control strategy that prevents excursions into operating regions causing failure. In this paper we implement a constrained MIMO model predictive controller (MPC) to avoid the failure modes relevant for a high-temperature tubular solid oxide fuel cell (SOFC) system while performing load-following. The primary causes of failure are catalyst poisoning, fuel or air starvation, carbon deposition, and microcracking. Prior steady-state thermomechanical stress analysis in literature has demonstrated that the minimum cell temperature and maximum negative radial thermal gradient are primary causes of microcracking in the SOFC. State-of-the-art SOFC control literature often seeks to track a mean or outlet cell temperature. The authors have presented the first approach to control the primary two causes of thermally-driven microcracking in tubular SOFCs using constrained control. Constraints are also incorporated into a steady-state optimization to ensure a feasible optimum.

This paper presents a physics-based steady-state equivalent circuit model of a two-stage bidirectional inverter. These inverters connect distributed energy resources (DERs), such as photovoltaic (PV) and battery systems, to distribution grids. Existing inverter models have technical gaps on three fronts: i) inadequate modeling of inverter losses ii) use of mathematical abstractions for bidirectional flow of power, iii) inability to integrate different control modes into nonlinear solvers without loss of generality. We propose an inverter model that explicitly captures losses in passive circuit components, grounded in circuitlevel principles. We enable bidirectional power flow without binary or complementarity constraints by formulating loss terms as smooth, sign-aware expressions of current. We introduce and parameterize controlled current sources with twice-differentiable continuous functions to enable inverter control modes without loss of generality. We integrate DERs with the proposed inverter model at the load buses of distribution networks to perform power flow and optimization studies on real-world distribution networks with over 20,000 nodes. We demonstrate that the proposed model is more accurate, integrates seamlessly with various control modes without loss of generality, and scales robustly to large optimization problems.