Content Provider	IEEE Xplore Digital Library
Author	Dall'Anese, E. Dhople, S.V. Johnson, B.B. Giannakis, G.B.
Copyright Year	2011
Abstract	Efforts to ensure reliable operation of existing low-voltage distribution systems with high photovoltaic (PV) generation have focused on the possibility of inverters providing ancillary services such as active power curtailment and reactive power compensation. Major benefits include the possibility of averting overvoltages, which may otherwise be experienced when PV generation exceeds the demand. This paper deals with ancillary service procurement in the face of solar irradiance forecasting errors. In particular, assuming that forecasted PV irradiance can be described by a random variable with known (empirical) distribution, the proposed uncertainty-aware optimal inverter dispatch (OID) framework indicates which inverters should provide ancillary services with a guaranteed a priori risk level of PV generation surplus. To capture forecasting errors and strike a balance between risk of overvoltages and (re)active power reserves, the concept of conditional value-at-risk is advocated. Due to AC power balance equations and binary inverter selection variables, the formulated OID involves the solution of a nonconvex mixed-integer nonlinear program. However, a computationally affordable convex relaxation is derived by leveraging sparsity-promoting regularization approaches and semidefinite relaxation techniques.
Starting Page	350
Ending Page	359
Page Count	10
File Size	1215158
File Format	PDF
ISSN	21563381
Volume Number	5
Issue Number	1
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-01-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Inverters Reactive power Forecasting Vectors Photovoltaic systems Surges voltage regulation Conditional value-at-risk (CVaR) distribution networks forecasting errors inverter control microgrids optimal power flow (OPF) photovoltaic (PV) systems
Content Type	Text
Resource Type	Article
Subject	Condensed Matter Physics Electronic, Optical and Magnetic Materials Electrical and Electronic Engineering

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