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Manuel Castillo-Cagigal

Researcher at Technical University of Madrid

Publications -  23
Citations -  989

Manuel Castillo-Cagigal is an academic researcher from Technical University of Madrid. The author has contributed to research in topics: Photovoltaic system & Distributed generation. The author has an hindex of 11, co-authored 21 publications receiving 894 citations. Previous affiliations of Manuel Castillo-Cagigal include ETSI.

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PV self-consumption optimization with storage and Active DSM for the residential sector

TL;DR: Results show the relationship between the electricity flows and the storage capacity, which is not linear and becomes an important design criterion.
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Neural network controller for Active Demand-Side Management with PV energy in the residential sector

TL;DR: In this paper, the authors describe the development of a control system for demand-side management in the residential sector with Distributed Generation, which is composed of two modules: a scheduler and a coordinator, both implemented with neural networks.
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Passive design strategies and performance of Net Energy Plus Houses

TL;DR: In this article, an analysis of the passive strategies used in Net Energy Plus Houses has been made, and the results reflect the impact of passive design strategies on the houses' comfort and efficiency, as well as their influence in helping to achieve the Zero Energy Buildings category.
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A semi-distributed electric demand-side management system with PV generation for self-consumption enhancement

TL;DR: In this article, the authors present the operation of an electrical demand side management (EDSM) system in a real solar house, which is implemented by a control system which schedules the tasks commanded by the user.
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Improving photovoltaics grid integration through short time forecasting and self-consumption

TL;DR: In this paper, the effects of uncertainty associated to the forecast of photovoltaic generation in a residential electrical system equipped with DSM techniques and a local storage system are analyzed in a solar house that is able to displace a residential user's load pattern, manage local storage and estimate forecasts of electricity generation.