A novel incentive-based demand response model for Cournot competition in electricity markets

This paper presents an analysis of competition between generators when incentive-based demand response is employed in an electricity market. Thermal and hydropower generation are considered in the model. A smooth inverse demand function is designed using a sigmoid and two linear functions for modeling the consumer preferences under incentive-based demand response program. Generators compete to sell energy bilaterally to consumers and system operator provides transmission and arbitrage services. The profit of each agent is posed as an optimization problem, then the competition result is found by solving simultaneously Karush-Kuhn-Tucker conditions for all generators. A Nash-Cournot equilibrium is found when the system operates normally and at peak demand times when DR is required. Under this model, results show that DR diminishes the energy consumption at peak periods, shifts the power requirement to off-peak times and improves the net consumer surplus due to incentives received for participating in DR program. However, the generators decrease their profit due to the reduction of traded energy and market prices

Learning Nonlinear Model Predictive Controllers and Virtual Sensors with Koopman Operators

Model Predictive Control is an industry-standard technique used to drive systems based on their internal dynamics. When not all states are available for feedback, a state estimator, such as an Extended Kalman Filter, is employed to achieve control over the complete system state. Nevertheless, when the system under control is nonlinear, these two combined methods can result in a computationally heavy control strategy, raising significantly the cost of implementing it online. In this paper, a data-driven strategy based on the Koopman Operator theory is presented to identify and replicate the dynamics of the Kalman Filter plus Model Predictive Controller pair in a resource-efficient scheme. First, a closed-loop operation data-set is generated from a pre-calibrated reference controller; then, a finite-dimensional approximation is derived for the Koopman Operator of the filter plus controller dynamics in the lifted space of observables; finally, the stability of the identified controller is evaluated through closed-loop simulations; in case the desired response has not been achieved, the identification process is performed iteratively with a progressively increasing regularization coefficient. A simulated example applied to the Van der Pol oscillator is presented to illustrate the effectiveness of the approach. Copyright (c) 2022 The Authors. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/

Rational consumer decisions in a peak time rebate program

A rational behavior of a consumer is analyzed when the user participates in a Peak Time Rebate (PTR) mechanism, which is a demand response (DR) incentive program based on a baseline. A multi-stage stochastic programming is proposed from the demand side in order to understand the rational decisions. The consumer preferences are modeled as a risk-averse function under additive uncertainty. The user chooses the optimal consumption profile to maximize his economic benefits for each period. The stochastic optimization problem is solved backward in time. A particular situation is developed when the System Operator (SO) uses consumption of the previous interval as the household-specific baseline for the DR program. It is found that a rational consumer alters the baseline in order to increase the well-being when there is an economic incentive. As results, whether the incentive is lower than the retail price, the user shifts his load requirement to the baseline setting period. On the other hand, if the incentive is greater than the regular energy price, the optimal decision is that the user spends the maximum possible energy in the baseline setting period and reduces the consumption at the PTR time. This consumer behavior produces more energy consumption in total considering all periods. In addition, the user with high uncertainty level in his energy pattern should spend less energy than a predictable consumer when the incentive is lower than the retail price

Experimental modeling of a web-winding machine: LPV approaches

This chapter presents the identification of a web-winding system as a linear parameter varying (LPV) system with the reel radius as the time-varying parameter. This system is nonlinear, time-varying and input–output unstable. Two identification methods are considered: in the first one, an LPV model is estimated in a single step using a novel approach based on sparse identification and set membership optimality evaluation. In the second one, several local linear time-invariant (LTI) models are identified using classical identification algorithms, and the overall LPV model is constructed as a weighted sum of the local models. The two methods are applied to experimental data measured on a real web-winding machine

Modelling and Simulation of Quasi-Resonant Inverter for Induction Heating under Variable Load

Single-switch quasi-resonant DC inverters are preferred in low-power induction-heating applications for their cheapness. However, they pose difficulties in enforcing soft-switching and show limited controllability. A good design of these converters must proceed in parallel with the characterization of the load and the operating conditions. The control of the switching frequency has a critical relationship to the non-linear behavior of the load due to electro-thermal coupling and geometrical anisotropies. Finite element methods enable the analysis of this kind of multiphysics coupled systems, but the simulation of transient dynamics is computationally expensive. The goal of this article is to propose a time-domain simulation strategy to analyze the behavior of induction heating systems with a quasi-resonant single-ended DC inverter using pulse frequency modulation and variable load. The load behavior is estimated through frequency stationary analysis and integrated into the time-domain simulations as a non-linear equivalent impedance parametrized by look-up tables. The model considers variations in temperature dynamics, the presence of work-piece anisotropies, and current harmonic waveforms. The power regulation strategy based on the control of the switch turn-on time is tested in a case study with varying load and it is shown that it is able to maintain the converter in the safe operation region, handling variations up to of (Formula presented.) in the equivalent load resistance

Modelo para la definición e implementación de procesos de gobierno de tecnologías de la información aplicado a CENIT Transporte y Logística de Hidrocarburos S.A.S.

El crecimiento que ha venido presentando CENIT Transporte y logística de hidrocarburos S.A.S. ha conducido a su área de tecnología a revisar los procesos tecnológicos con los que apoya a todas las áreas de negocio para el logro de la estrategia empresarial. Para poder cumplir con esta promesa de valor hacia la organización, el área de tecnología bajo un marco de trabajo reconocido debe analizar, definir, estructurar e implementar formalmente sus procesos y de esta manera también cumplirá con los lineamientos establecidos por la casa matriz Ecopetrol S.A. COBIT 5-ISACA (2012) como marco de trabajo que integra las mejores practicas a nivel de tecnología, permite ser usado como el estándar que mejor se adecua a la necesidad del área de tecnología para definir e implementar un gobierno de TI en CENIT. Este trabajo propone un modelo para la definición e implementación de procesos de gobierno de tecnologías de la información que cuenta con una herramienta que basada en el nivel de importancia, aporte al foco de análisis y esfuerzo requerido permite de manera automática que los procesos se clasifiquen y prioricen generando las bases para estructurar el plan de trabajo que permitirá de manera organizada lograr la formalización de sus procesos. Este modelo y su herramienta se usaron para definir y clasificar los procesos que permitirán la implementación del gobierno de TI en CENIT. El resultado es que tres (3) de los procesos de COBIT 5.0 que inicialmente ayudarán a implementar formalmente el gobierno de TI, son en su orden APO01, APO02 y EDM01. Adicionalmente este modelo y herramienta propuesta pueden ser usadas para clasificar los procesos de COBIT 5.0 bajo diferentes focos de análisis.The increase that has been occurring in CENIT Hydrocarbon transportation and logistics S. A. S has led to check the technological processes of the technology area which supports all business areas to achieve business strategy. To fulfill this objective of value to the organization, the technology area under a recognized framework should analyze, define, structure and implement formal processes and this also will comply with the guidelines established by the parent company Ecopetrol S. A. COBIT 5-ISACA (2012) as a framework that integrates the best practices in terms of technology , it can be used as the best standard to the necessity of the area of technology to define and implement IT governance at CENIT. This document proposes a model for defining and implementing governance processes of the information technology which has a tool that based on the level of importance, contribution to the focus of analysis and the effort required which make automatically classified and prioritized the process, creating the basis for structuring to create the plan that will allow to obtain the formalization of its processes by the organized way. This model and tool are used to define and classify the processes which are going to permit the implementation of IT governance at CENIT. The result is three (3) of COBIT 5. 0 processes, that initially could help to implement a formally IT governance, are in order APO01, APO02 and EDM01. In addition, this model and proposed tool can be used to classify COBIT 5. 0 processes under different focus of analysis.Centro de Estudios Empresariales para la Perdurabilida

SMGO: A Set Membership Approach to Data-Driven Global Optimization

Many science and engineering applications feature non-convex optimization problems where the objective function can not be handled analytically, i.e. it is a black box. Examples include design optimization via experiments, or via costly finite elements simulations. To solve these problems, global optimization routines are used. These iterative techniques must trade-off exploitation close to the current best point with exploration of unseen regions of the search space. In this respect, a new global optimization strategy based on a Set Membership (SM) framework is proposed. Assuming Lipschitz continuity of the cost function, the approach employs SM concepts to decide whether to switch from an exploitation mode to an exploration one, and vice-versa. The resulting algorithm, named SMGO (Set Membership Global Optimization) is presented. Theoretical properties regarding convergence and computational complexity are derived, and implementation aspects are discussed. Finally, the SMGO performance is evaluated on a set of benchmark non-convex problems and compared with those of other global optimization approaches

An ElectroThermal Digital Twin for Design and Management of Radiation Heating in Industrial Processes

The design and management of thermoforming systems based on radiation heat transfer require the development of a mathematical model that can be used at all stages of the system's life cycle. For this reason, in this paper, we present a digital twin based on a hybrid ElectroThermal model that can integrate mathematical equations and data acquired in the field. The model's validity is verified with experiments performed on a test bench. The presented model is modular and can be easily used to represent new configurations of the heating elements for simulation and design. Thanks to the low computational complexity of the proposed Digital Twin, it enables the development of advanced control strategies and the analysis and optimization of the main geometric parameters of the system. In addition, it can support the identification of the best configuration and choice of measurement points