Caricamento in corso...
Electrical load management, forecasting and control
01LYXRV
A.A. 2018/19
Course Language
Inglese
Degree programme(s)
Doctorate Research in Ingegneria Elettrica, Elettronica E Delle Comunicazioni - Torino
Course structure
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Lecturers
| Teacher | Status | SSD | h.Les | h.Ex | h.Lab | h.Tut | Years teaching |
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Co-lectures
Context
| SSD | CFU | Activities | Area context | *** N/A *** |
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PERIODO: SETTEMBRE 2018
The recent developments in the electrical sector and the increasing interactions among the energy and economic sectors call for developing specific techniques and tools for the electrical load modelling, management, forecasting and control. The course deals with various applications to the residential, industrial and tertiary sectors, and to the aggregated load at different levels. Various techniques related to the electrical load pattern analysis are illustrated and applied to load characterization (with deterministic and probabilistic representations) load classification and profiling (with clustering techniques), load forecasting (with artificial intelligence applications, neural networks), load management and control (demand response and thermostat-controlled loads). All course activities will be in English.
The recent developments in the electrical sector and the increasing interactions among the energy and economic sectors call for developing specific techniques and tools for the electrical load modelling, management, forecasting and control. The course deals with various applications to the residential, industrial and tertiary sectors, and to the aggregated load at different levels. Various techniques related to the electrical load pattern analysis are illustrated and applied to load characterization (with deterministic and probabilistic representations) load classification and profiling (with clustering techniques), load forecasting (with artificial intelligence applications, neural networks), load management and control (demand response and thermostat-controlled loads). All course activities will be in English.
•Introduction to the representation of the electrical load
• Aggregated load models for residential users
• Load models for non-residential users
• Electricity customer classification techniques and load profiling
• Notes on Direct Load Control and Demand Response
• Thermostat-controlled loads and Cold Load Pickup
• Load forecasting principles
• Artificial intelligence applications to load forecasting
Period: 17-21 September 2018
Lecturers: prof. Gianfranco Chicco (DENERG), prof. Federico Piglione
(DENERG) Intensive course (one week, including the final test)
Location: Lab. “Tommasini”, Dipartimento Energia “Galileo Ferraris", North side (close to the entrance from corso Montevecchio 71), underground floor.
Course calendar:
Monday 17 September 2018: hours 10:00-13:00 and 14:30-18:00
Tuesday 18 September 2018: hours 10:00-13:00 and 14:30-18:00
Wednesday 19 September 2018: hours 10:00-13:00 and 14:30-18:00 Thursday 20 September 2018: hours 10:00-13:00 and 14:30-17:00
Friday 21 September 2018: final exam (hours 9.00-10.30), with correction
and final results provided before hour 12.30
•Introduction to the representation of the electrical load
• Aggregated load models for residential users
• Load models for non-residential users
• Electricity customer classification techniques and load profiling
• Notes on Direct Load Control and Demand Response
• Thermostat-controlled loads and Cold Load Pickup
• Load forecasting principles
• Artificial intelligence applications to load forecasting
Date and meeting point for the first lecture: Monday, 19 September 2016, hour
10.00 AM, Politecnico di Torino, Dipartimento Energia (Energy Department), north side (near corso Montevecchio 71), room C (underground floor).
Final test: Friday, 23 September 2016, hour 9:00-10:30 AM, with communication of the results by 12:00 AM.
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Gli studenti e le studentesse con disabilità o con Disturbi Specifici di Apprendimento (DSA), oltre alla segnalazione tramite procedura informatizzata, sono invitati a comunicare anche direttamente al/la docente titolare dell'insegnamento, con un preavviso non inferiore ad una settimana dall'avvio della sessione d'esame, gli strumenti compensativi concordati con l'Unità Special Needs, al fine di permettere al/la docente la declinazione più idonea in riferimento alla specifica tipologia di esame.
In addition to the message sent by the online system, students with disabilities or Specific Learning Disorders (SLD) are invited to directly inform the professor in charge of the course about the special arrangements for the exam that have been agreed with the Special Needs Unit. The professor has to be informed at least one week before the beginning of the examination session in order to provide students with the most suitable arrangements for each specific type of exam.