TY - GEN
T1 - Increasing Renewable Generation Feed-In Capacity Leveraging Smart Meters
AU - Caprolu, Maurantonio
AU - Fernandez, Javier Hernandez
AU - Alassi, Abdulrahman
AU - Di Pietro, Roberto
N1 - Generated from Scopus record by KAUST IRTS on 2023-09-20
PY - 2020/11/2
Y1 - 2020/11/2
N2 - The amount of energy that can be fed into a network is limited by the physical capacity of the components that form the grid and the load it serves. Electrical utilities use Hosting Capacity (HC) methodologies to analyze and calculate the level of generation that a network can accommodate. Currently, HC analyses are based on conservative static models with the objective of ensuring that technical limitations are not exceeded, hence curbing the optimal network capacity. Demand Response (DR) programs seek to optimize energy resources by lowering or deferring consumption. As a result, technical solutions have focused on reducing demand. These solutions are efficient when there is no local generation of energy, or to reduce individual consumption, but they hamper with feed-in programs. To solve the above introduced issues, in this paper we propose a system with the objective to maximize the limit of the HC of each customer while ensuring stability of the grid. Each customer is assigned a nominal HC value, calculated using the existing methodologies, but has the option of requesting a temporary increase in the feed-in limit. The utility provider will grant or reject the request based on the current conditions of the grid by utilizing the existing smart meter infrastructure and the energy-balancing metering at the transformer substation. The architecture supporting the cited objectives is detailed, a PoC rooted on real experiments is showed, and future directions are also highlighted. Finally, the achieved experimental results show the viability of our proposal.
AB - The amount of energy that can be fed into a network is limited by the physical capacity of the components that form the grid and the load it serves. Electrical utilities use Hosting Capacity (HC) methodologies to analyze and calculate the level of generation that a network can accommodate. Currently, HC analyses are based on conservative static models with the objective of ensuring that technical limitations are not exceeded, hence curbing the optimal network capacity. Demand Response (DR) programs seek to optimize energy resources by lowering or deferring consumption. As a result, technical solutions have focused on reducing demand. These solutions are efficient when there is no local generation of energy, or to reduce individual consumption, but they hamper with feed-in programs. To solve the above introduced issues, in this paper we propose a system with the objective to maximize the limit of the HC of each customer while ensuring stability of the grid. Each customer is assigned a nominal HC value, calculated using the existing methodologies, but has the option of requesting a temporary increase in the feed-in limit. The utility provider will grant or reject the request based on the current conditions of the grid by utilizing the existing smart meter infrastructure and the energy-balancing metering at the transformer substation. The architecture supporting the cited objectives is detailed, a PoC rooted on real experiments is showed, and future directions are also highlighted. Finally, the achieved experimental results show the viability of our proposal.
UR - https://ieeexplore.ieee.org/document/9285082/
UR - http://www.scopus.com/inward/record.url?scp=85099378488&partnerID=8YFLogxK
U2 - 10.1109/IGESSC50231.2020.9285082
DO - 10.1109/IGESSC50231.2020.9285082
M3 - Conference contribution
SN - 9781728187440
BT - 2020 IEEE Green Energy and Smart Systems Conference, IGESSC 2020
PB - Institute of Electrical and Electronics Engineers Inc.
ER -