TY - JOUR
T1 - Modeling demand flexibility impact on the long-term adequacy of generation systems
AU - Alves, Inês M.
AU - Carvalho, Leonel M.
AU - Peças Lopes, J. A.
N1 - Publisher Copyright:
© 2023 Elsevier Ltd
PY - 2023/9
Y1 - 2023/9
N2 - This paper proposes a novel probabilistic model for quantifying the impact of demand flexibility (DF) on the long-term generation system adequacy via Sequential Monte Carlo Simulation (SMCS) method. Unlike load shedding, DF can be considered an important instrument to postpone bulk consumption from periods with limited reserves to periods with more generating capacity available, avoiding load shedding and increasing the integration of variable renewable generation, such as wind power. DF has been widely studied in terms of its contribution to the system's social welfare, resulting in numerous innovative approaches ranging from the flexibility modeling of individual electric loads to the definition of aggregation strategies for optimally deploying this lever in competitive markets. To add to the current state-of-the-art, a new model is proposed to quantify DF impact on the traditional reliability indices, such as the Loss of Load Expectation (LOLE) and the Expected Energy Not Supplied (EENS), enabling a new perspective for the DF value. Given the diverse mechanisms associated with DF of different consumer types, the model considers the uncertainties associated with the demand flexibility available in each hour of the year and with the rebound effect, i.e., the subsequent change of consumption patterns following a DF mobilization event. Case studies based on a configuration of the IEEE-RTS 79 test system with wind power demonstrate that the DF can substantially improve the reliability indices of the static and operational reserve while decreasing the curtailment of variable generation cause by unit scheduling priorities or by short-term generation/demand imbalances.
AB - This paper proposes a novel probabilistic model for quantifying the impact of demand flexibility (DF) on the long-term generation system adequacy via Sequential Monte Carlo Simulation (SMCS) method. Unlike load shedding, DF can be considered an important instrument to postpone bulk consumption from periods with limited reserves to periods with more generating capacity available, avoiding load shedding and increasing the integration of variable renewable generation, such as wind power. DF has been widely studied in terms of its contribution to the system's social welfare, resulting in numerous innovative approaches ranging from the flexibility modeling of individual electric loads to the definition of aggregation strategies for optimally deploying this lever in competitive markets. To add to the current state-of-the-art, a new model is proposed to quantify DF impact on the traditional reliability indices, such as the Loss of Load Expectation (LOLE) and the Expected Energy Not Supplied (EENS), enabling a new perspective for the DF value. Given the diverse mechanisms associated with DF of different consumer types, the model considers the uncertainties associated with the demand flexibility available in each hour of the year and with the rebound effect, i.e., the subsequent change of consumption patterns following a DF mobilization event. Case studies based on a configuration of the IEEE-RTS 79 test system with wind power demonstrate that the DF can substantially improve the reliability indices of the static and operational reserve while decreasing the curtailment of variable generation cause by unit scheduling priorities or by short-term generation/demand imbalances.
KW - Demand flexibility
KW - Generation system adequacy assessment
KW - Sequential Monte Carlo simulation
UR - http://www.scopus.com/inward/record.url?scp=85153504151&partnerID=8YFLogxK
U2 - 10.1016/j.ijepes.2023.109169
DO - 10.1016/j.ijepes.2023.109169
M3 - Article
AN - SCOPUS:85153504151
SN - 0142-0615
VL - 151
JO - International Journal of Electrical Power and Energy Systems
JF - International Journal of Electrical Power and Energy Systems
M1 - 109169
ER -