2nd IEEE International Conference on Industrial Electronics for Sustainable Energy Systems - IESES 2020, Cagliari (Italy). 01-03 September 2020
Summary:
Microgrid (MG) or Local Energy Communities (LEC) management systems aim at coordinating their local resources for minimizing the operation costs of their network. Excessive voltage reductions due to heavy demand or over voltage conditions due to production that exceed the local demand can be solved by exploiting control actions as the load shedding or the generation curtailment. The cost of these services, offered by players connected to the MG/LEC, have to be included in the total operational MG/LEC cost. Forecasting in advance, i.e. one day ahead, the state of the network, and the possible contingencies that may happen during the real time, can result in significant savings for the MG/LEC management system, because it is generally assumed that these services are more expensive in the real time than if purchased/planned in advance. Thus, one of the requirements of an optimal MG/LEC management system is to accurately model the local production and demand for making proper decisions in advance, that at least may be slightly changed if the forecasting does not happen in real time. Typical day load profiles that reproduce, in the best possible way, the behavior of the customers can be used for making this task more accurate. This paper compares the impact of using different sets of typical load profiles on the optimization performed by an Energy Management System (EMS), that controls the local MG/LEC resources for solving contingencies. The proposed case study is constituted by a LV MG/ LEC, derived from a real network and it is managed by an EMS based on a multi agent system.
DOI: 
https://doi.org/10.1109/IESES45645.2020.9210703
Published in IEEE IESES 2020, pp: 1-6, ISBN: 978-1-7281-4018-6
Publication date: 2020-09-01.
Citation:
G. Pisano, F. Pilo, S. Ruggeri, M. Troncia, LV customers modeling impact on microgrid optimal management, 2nd IEEE International Conference on Industrial Electronics for Sustainable Energy Systems - IESES 2020, Cagliari (Italy). 01-03 September 2020. In: IEEE IESES 2020: Conference proceedings, ISBN: 978-1-7281-4018-6
