This paper proposes an innovative exhaustive search method for the optimal placement of wind turbines (WTs) in electrical distribution systems taking into account wind speed and load demand uncertainty, and the variability of electrical energy prices within a distribution network operator (DNO) acquisition market environment. The method combines Monte Carlo simulation (MCS) and market-based optimal power flow (OPF) to maximize the net present value (NPV) related to the investment made by WTs' developers over a planning horizon. In particular, the MCS data feed the market-based OPF problem with inter-temporal constraints in order to find the most convenient WTs allocation and priority on the network, based on distribution-locational marginal prices (D-LMPs) in a competitive electricity market. The effectiveness of the proposed method is demonstrated with an 84-bus 11.4-kV radial distribution system.

A Model for Wind Turbines Placement Within a Distribution Network Acquisition Market

SARNO, DEBORA;SIANO, PIERLUIGI;ROMANO, ROBERTO
2015

Abstract

This paper proposes an innovative exhaustive search method for the optimal placement of wind turbines (WTs) in electrical distribution systems taking into account wind speed and load demand uncertainty, and the variability of electrical energy prices within a distribution network operator (DNO) acquisition market environment. The method combines Monte Carlo simulation (MCS) and market-based optimal power flow (OPF) to maximize the net present value (NPV) related to the investment made by WTs' developers over a planning horizon. In particular, the MCS data feed the market-based OPF problem with inter-temporal constraints in order to find the most convenient WTs allocation and priority on the network, based on distribution-locational marginal prices (D-LMPs) in a competitive electricity market. The effectiveness of the proposed method is demonstrated with an 84-bus 11.4-kV radial distribution system.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11386/4650666
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