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Energies 2012, 5(4), 1116-1134; doi:10.3390/en5041116
Article

Look-Ahead Energy Management of a Grid-Connected Residential PV System with Energy Storage under Time-Based Rate Programs

1
, 1
, 1
, 2
, 2
, 1,*  and 3
1 School of Electrical and Electronic Engineering, Yonsei University, Seoul 120-749, South Korea 2 Saudi Aramco Chair in Electrical Power, Department of Electrical Engineering, King Saud University, Riyadh 11421, Saudi Arabia 3 Department of Nuclear & Quantum Engineering, Korea Advanced Institute of Science and Technology, Daejeon 305-701, South Korea
* Author to whom correspondence should be addressed.
Received: 5 March 2012 / Revised: 10 April 2012 / Accepted: 10 April 2012 / Published: 19 April 2012
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Abstract

This paper presents look-ahead energy management system for a grid-connected residential photovoltaic (PV) system with battery under critical peak pricing for electricity, enabling effective and proactive participation of consumers in the Smart Grid’s demand response. In the proposed system, the PV is the primary energy source with the battery for storing (or retrieving) excessive (or stored) energy to pursue the lowest possible electricity bill but it is grid-tied to secure electric power delivery. Premise energy management scheme with an accurate yet practical load forecasting capability based on a Kalman filter is designed to increase the predictability in controlling the power flows among these power system components and the controllable electric appliances in the premise. The case studies with various operating scenarios demonstrate the validity of the proposed system and significant cost savings through operating the energy management scheme.
Keywords: photovoltaic (PV); energy storage system; smart grid; load forecasting; critical peak pricing (CPP) photovoltaic (PV); energy storage system; smart grid; load forecasting; critical peak pricing (CPP)
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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MDPI and ACS Style

Yoo, J.; Park, B.; An, K.; Al-Ammar, E.A.; Khan, Y.; Hur, K.; Kim, J.H. Look-Ahead Energy Management of a Grid-Connected Residential PV System with Energy Storage under Time-Based Rate Programs. Energies 2012, 5, 1116-1134.

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