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Mixed Integer Quadratic Programming Based Scheduling Methods for Day-Ahead Bidding and Intra-Day Operation of Virtual Power Plant

Authors
Ko, RakkyungKang, DaeyoungJoo, Sung-Kwan
Issue Date
2-4월-2019
Publisher
MDPI
Keywords
virtual power plant (VPP); energy storage system (ESS); VPP schedule; schedule revising; mixed integer programming
Citation
ENERGIES, v.12, no.8
Indexed
SCIE
SCOPUS
Journal Title
ENERGIES
Volume
12
Number
8
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/66057
DOI
10.3390/en12081410
ISSN
1996-1073
Abstract
As distributed energy resources (DERs) proliferate power systems, power grids face new challenges stemming from the variability and uncertainty of DERs. To address these problems, virtual power plants (VPPs) are established to aggregate DERs and manage them as single dispatchable and reliable resources. VPPs can participate in the day-ahead (DA) market and therefore require a bidding method that maximizes profits. It is also important to minimize the variability of VPP output during intra-day (ID) operations. This paper presents mixed integer quadratic programming-based scheduling methods for both DA market bidding and ID operation of VPPs, thus serving as a complete scheme for bidding-operation scheduling. Hourly bids are determined based on VPP revenue in the DA market bidding step, and the schedule of DERs is revised in the ID operation to minimize the impact of forecasting errors and maximize the incentives, thus reducing the variability and uncertainty of VPP output. The simulation results verify the effectiveness of the proposed methods through a comparison of daily revenue.
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