Distributed chance-constrained optimal power flow based on primary frequency control

Autor: Nicolas Retière, Meritxell Vinyals, Yvon Besanger, Maxime Velay
Přispěvatelé: Laboratoire d'analyse des données et d'intelligence des systèmes (LADIS), Département Métrologie Instrumentation & Information (DM2I), Laboratoire d'Intégration des Systèmes et des Technologies (LIST), Direction de Recherche Technologique (CEA) (DRT (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Direction de Recherche Technologique (CEA) (DRT (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Laboratoire d'Intégration des Systèmes et des Technologies (LIST), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay, Laboratoire de Génie Electrique de Grenoble (G2ELab), Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), European Project: 619682,EC:FP7:ICT,FP7-ICT-2013-11,MAS2TERING(2014), European Project: H2020 774431,DRIvE, Laboratoire d'Intégration des Systèmes et des Technologies (LIST (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Laboratoire d'Intégration des Systèmes et des Technologies (LIST (CEA))
Jazyk: angličtina
Rok vydání: 2018
Předmět:
0209 industrial biotechnology
Schedule
Mathematical optimization
Chance-constrained
Computer science
020209 energy
Gaussian
Automatic frequency control
wind farm
forecast
02 engineering and technology
7. Clean energy
reserves
Computing methodologies
symbols.namesake
020901 industrial engineering & automation
0202 electrical engineering
electronic engineering
information engineering
[INFO.INFO-SY]Computer Science [cs]/Systems and Control [cs.SY]
power system reliability
Sensitivity (control systems)
electricity
optimal power flow
uncertainty
generator
Primary Frequency Control (PFC)
Multi-agent systems
[SPI.NRJ]Engineering Sciences [physics]/Electric power
Probabilistic logic
Open access
alternating direction multiplier method
Power flow
Distribution (mathematics)
wind forecast
Distributed algorithm
[INFO.INFO-MA]Computer Science [cs]/Multiagent Systems [cs.MA]
Optimal Power Flow (OPF)
symbols
ADMM
Zdroj: ACM digital library
9th ACM International Conference on Future Energy Systems (ACM e-Energy)
9th ACM International Conference on Future Energy Systems (ACM e-Energy), Jun 2018, Karlsruhe, Germany. pp.366-374, ⟨10.1145/3208903.3208921⟩
e-Energy
DOI: 10.1145/3208903.3208921⟩
Popis: International audience; We propose a fully distributed algorithm to solve the Chance Constrained Optimal Power Flow (CCOPF), with the advantages of ensuring the privacy and autonomy of the different operators and actors of the system. We present, in this paper, a two-step algorithm that, first, carries out a distributed sensitivity analysis to obtain the generalized generation distribution factors. With these sensitivity factors, the second step solves a distributed CCOPF based on an analytical formulation relying on the Primary Frequency Control (PFC) of generators and on wind farms, whose forecast errors are assumed to be Gaussian. This algorithm allows us to schedule margins and reserves to ensure the security of the system regarding wind farms deviation from forecast with probabilistic guarantees, and to assess the cost of this uncertainty. The proposed method has been implemented and tested on a two-bus test system with one wind farm, and on the IEEE 14-bus test system, with two wind farms. Simulation results showed that the proposed algorithm can efficiently solve the CCOPF in a fully distributed manner.
Databáze: OpenAIRE
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