TY - JOUR
T1 - Demand flexibility management for buildings-to-grid integration with uncertain generation
AU - Rostampour, Vahab
AU - Badings, Thom S.
AU - Scherpen, Jacquelien M.A.
N1 - Funding Information:
Funding: This research is supported by the incentives and algorithms for efficient, reliable, sustainable and socially acceptable energy system integration (ERSAS) research program funded by the Dutch organization for scientific research (NWO) with grant number 647-002-005.
Publisher Copyright:
© 2020 by the authors. Licensee MDPI, Basel, Switzerland.
PY - 2020/12/2
Y1 - 2020/12/2
N2 - We present a Buildings-to-Grid (BtG) integration framework with intermittent wind-power generation and demand flexibility management provided by buildings. First, we extend the existing BtG models by introducing uncertain wind-power generation and reformulating the interactions between the Transmission System Operator (TSO), Distribution System Operators (DSO), and buildings. We then develop a unified BtG control framework to deal with forecast errors in the wind power, by considering ancillary services from both reserves and demand-side flexibility. The resulting framework is formulated as a finite-horizon stochastic model predictive control (MPC) problem, which is generally hard to solve due to the unknown distribution of the wind-power generation. To overcome this limitation, we present a tractable robust reformulation, together with probabilistic feasibility guarantees. We demonstrate that the proposed demand flexibility management can substitute the traditional reserve scheduling services in power systems with high levels of uncertain generation. Moreover, we show that this change does not jeopardize the stability of the grid or violate thermal comfort constraints of buildings. We finally provide a large-scale Monte Carlo simulation study to confirm the impact of achievements.
AB - We present a Buildings-to-Grid (BtG) integration framework with intermittent wind-power generation and demand flexibility management provided by buildings. First, we extend the existing BtG models by introducing uncertain wind-power generation and reformulating the interactions between the Transmission System Operator (TSO), Distribution System Operators (DSO), and buildings. We then develop a unified BtG control framework to deal with forecast errors in the wind power, by considering ancillary services from both reserves and demand-side flexibility. The resulting framework is formulated as a finite-horizon stochastic model predictive control (MPC) problem, which is generally hard to solve due to the unknown distribution of the wind-power generation. To overcome this limitation, we present a tractable robust reformulation, together with probabilistic feasibility guarantees. We demonstrate that the proposed demand flexibility management can substitute the traditional reserve scheduling services in power systems with high levels of uncertain generation. Moreover, we show that this change does not jeopardize the stability of the grid or violate thermal comfort constraints of buildings. We finally provide a large-scale Monte Carlo simulation study to confirm the impact of achievements.
KW - Buildings-to-Grid integration
KW - Demand flexibility management
KW - Distribution System Operators (DSO)
KW - Future energy markets
KW - Power systems
KW - Stochastic model predictive control
KW - Transmission System Operator (TSO)
KW - Uncertain generation
UR - http://www.scopus.com/inward/record.url?scp=85101832817&partnerID=8YFLogxK
U2 - 10.3390/en13246532
DO - 10.3390/en13246532
M3 - Article
AN - SCOPUS:85101832817
SN - 1996-1073
VL - 13
JO - Energies
JF - Energies
IS - 24
M1 - 6532
ER -