A novel framework for integrating real-time optimization and optimal scheduling : Application to heat and power systems

The optimization of heat and power systems operation is a complex task that involves continuous and discrete variables, operating and environmental constraints, uncertain prices and demands and transition constraints for startups or shutdowns. This work proposes a novel methodology for integrating scheduling optimization and real-time optimization (RTO) in order to face and solve such optimization problem. In a first stage, an offline optimization finds a scheduling for the whole horizon under study, which sets the startups and shutdowns of pieces of equipment with long transition times. A second stage solves a multiperiod RTO, which corrects the forecasts and adapts the model before optimiz-ing the process. Although the proposed methodology is illustrated through a case study consisting in a heat and power system, it can be generalized to other systems and processes. The obtained results show significant improvements in comparison with applying the results of a single offline scheduling optimization.Sociedad Argentina de Informática e Investigación Operativa (SADIO

A novel framework for integrating real-time optimization and optimal scheduling : Application to heat and power systems

The optimization of heat and power systems operation is a complex task that involves continuous and discrete variables, operating and environmental constraints, uncertain prices and demands and transition constraints for startups or shutdowns. This work proposes a novel methodology for integrating scheduling optimization and real-time optimization (RTO) in order to face and solve such optimization problem. In a first stage, an offline optimization finds a scheduling for the whole horizon under study, which sets the startups and shutdowns of pieces of equipment with long transition times. A second stage solves a multiperiod RTO, which corrects the forecasts and adapts the model before optimiz-ing the process. Although the proposed methodology is illustrated through a case study consisting in a heat and power system, it can be generalized to other systems and processes. The obtained results show significant improvements in comparison with applying the results of a single offline scheduling optimization.Sociedad Argentina de Informática e Investigación Operativa (SADIO

Big Data and the Internet of Things

Advances in sensing and computing capabilities are making it possible to embed increasing computing power in small devices. This has enabled the sensing devices not just to passively capture data at very high resolution but also to take sophisticated actions in response. Combined with advances in communication, this is resulting in an ecosystem of highly interconnected devices referred to as the Internet of Things - IoT. In conjunction, the advances in machine learning have allowed building models on this ever increasing amounts of data. Consequently, devices all the way from heavy assets such as aircraft engines to wearables such as health monitors can all now not only generate massive amounts of data but can draw back on aggregate analytics to "improve" their performance over time. Big data analytics has been identified as a key enabler for the IoT. In this chapter, we discuss various avenues of the IoT where big data analytics either is already making a significant impact or is on the cusp of doing so. We also discuss social implications and areas of concern.Comment: 33 pages. draft of upcoming book chapter in Japkowicz and Stefanowski (eds.) Big Data Analysis: New algorithms for a new society, Springer Series on Studies in Big Data, to appea

Advances in Theoretical and Computational Energy Optimization Processes

The paradigm in the design of all human activity that requires energy for its development must change from the past. We must change the processes of product manufacturing and functional services. This is necessary in order to mitigate the ecological footprint of man on the Earth, which cannot be considered as a resource with infinite capacities. To do this, every single process must be analyzed and modified, with the aim of decarbonising each production sector. This collection of articles has been assembled to provide ideas and new broad-spectrum contributions for these purposes

Coordinating industrial production and cogeneration systems to exploit electricity price fluctuations

Las fluctuaciones en el precio de la electricidad, procedentes de la aplicación de programas de respuesta de la demanda, son una oportunidad para que las industrias que cuenten con sistemas de cogeneración puedan reducir sus costes de producción mientras hacen que la red eléctrica sea más estable y segura en su conjunto. Dada la cantidad de factores involucrados y la dificultad que esto supone a la hora de tomar decisiones, en esta tesis se presenta una metodología basada en optimización dinámica que permite la gestión óptima de ambos sistemas y se aplica en simulación al caso de estudio de una industria azucarera. Como principales resultados, se ha obtenido que utilizando la metodología propuesta los costes variables de producción se pueden reducir hasta un 2.55% si se utiliza una tarifa por tramos típica, y en torno a un 5.41% si se utilizan los precios dados por el mercado eléctrico directamente.Departamento de Ingeniería de Sistemas y AutomáticaDoctorado en Ingeniería Industria

Energy management in microgrids with renewable energy sources: A literature review

Renewable energy sources have emerged as an alternative to meet the growing demand for energy, mitigate climate change, and contribute to sustainable development. The integration of these systems is carried out in a distributed manner via microgrid systems; this provides a set of technological solutions that allows information exchange between the consumers and the distributed generation centers, which implies that they need to be managed optimally. Energy management in microgrids is defined as an information and control system that provides the necessary functionality, which ensures that both the generation and distribution systems supply energy at minimal operational costs. This paper presents a literature review of energy management in microgrid systems using renewable energies, along with a comparative analysis of the different optimization objectives, constraints, solution approaches, and simulation tools applied to both the interconnected and isolated microgrids. To manage the intermittent nature of renewable energy, energy storage technology is considered to be an attractive option due to increased technological maturity, energy density, and capability of providing grid services such as frequency response. Finally, future directions on predictive modeling mainly for energy storage systems are also proposed