Optimal Operation and Bidding Strategy of a Virtual Power Plant Integrated with Energy Storage Systems and Elasticity Demand Response

Wenjun Tang, Hong-Tzer Yang

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

As an aggregator involved in various renewable energy sources, energy storage systems, and loads, a virtual power plant (VPP) plays a key role as a prosumer. A VPP may enable itself to supply energy and ancillary services to the utility grid. This paper proposes a novel scheme for optimizing the operation and bidding strategy of VPPs. By scheduling the energy storage systems, demand response, and renewable energy sources, VPPs can join bidding markets to achieve maximum benefits. The potential uncertainties caused by renewable energy sources and the demand response are considered in a robust optimization model. Moreover, the robust VPP optimization accounts for its influence on markets to ensure optimal energy and reserve capacity bidding transactions in the day-ahead market and deals balancing in the real-time market. To demonstrate the performance of the proposed scheme, markets comprising various participants and managed by the system operator are implemented using mathematical models. The proposed method is evaluated using an illustrative system and the practical Taiwan power (Taipower) system with diverse uncertainty levels. The numerical results demonstrate the promising performance and the efficiency of the proposed method. The results also verify the effectiveness of the proposed method VPP with various combinations of renewable energy sources, energy storage systems, and loads.

Original languageEnglish
Article number8736232
Pages (from-to)79798-79809
Number of pages12
JournalIEEE Access
Volume7
DOIs
Publication statusPublished - 2019 Jan 1

Fingerprint

Energy storage
Elasticity
Power plants
Mathematical operators
Scheduling
Mathematical models
Uncertainty

All Science Journal Classification (ASJC) codes

  • Computer Science(all)
  • Materials Science(all)
  • Engineering(all)

Cite this

@article{62771ccc699a4557aaed683fb932821f,
title = "Optimal Operation and Bidding Strategy of a Virtual Power Plant Integrated with Energy Storage Systems and Elasticity Demand Response",
abstract = "As an aggregator involved in various renewable energy sources, energy storage systems, and loads, a virtual power plant (VPP) plays a key role as a prosumer. A VPP may enable itself to supply energy and ancillary services to the utility grid. This paper proposes a novel scheme for optimizing the operation and bidding strategy of VPPs. By scheduling the energy storage systems, demand response, and renewable energy sources, VPPs can join bidding markets to achieve maximum benefits. The potential uncertainties caused by renewable energy sources and the demand response are considered in a robust optimization model. Moreover, the robust VPP optimization accounts for its influence on markets to ensure optimal energy and reserve capacity bidding transactions in the day-ahead market and deals balancing in the real-time market. To demonstrate the performance of the proposed scheme, markets comprising various participants and managed by the system operator are implemented using mathematical models. The proposed method is evaluated using an illustrative system and the practical Taiwan power (Taipower) system with diverse uncertainty levels. The numerical results demonstrate the promising performance and the efficiency of the proposed method. The results also verify the effectiveness of the proposed method VPP with various combinations of renewable energy sources, energy storage systems, and loads.",
author = "Wenjun Tang and Hong-Tzer Yang",
year = "2019",
month = "1",
day = "1",
doi = "10.1109/ACCESS.2019.2922700",
language = "English",
volume = "7",
pages = "79798--79809",
journal = "IEEE Access",
issn = "2169-3536",
publisher = "Institute of Electrical and Electronics Engineers Inc.",

}

Optimal Operation and Bidding Strategy of a Virtual Power Plant Integrated with Energy Storage Systems and Elasticity Demand Response. / Tang, Wenjun; Yang, Hong-Tzer.

In: IEEE Access, Vol. 7, 8736232, 01.01.2019, p. 79798-79809.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Optimal Operation and Bidding Strategy of a Virtual Power Plant Integrated with Energy Storage Systems and Elasticity Demand Response

AU - Tang, Wenjun

AU - Yang, Hong-Tzer

PY - 2019/1/1

Y1 - 2019/1/1

N2 - As an aggregator involved in various renewable energy sources, energy storage systems, and loads, a virtual power plant (VPP) plays a key role as a prosumer. A VPP may enable itself to supply energy and ancillary services to the utility grid. This paper proposes a novel scheme for optimizing the operation and bidding strategy of VPPs. By scheduling the energy storage systems, demand response, and renewable energy sources, VPPs can join bidding markets to achieve maximum benefits. The potential uncertainties caused by renewable energy sources and the demand response are considered in a robust optimization model. Moreover, the robust VPP optimization accounts for its influence on markets to ensure optimal energy and reserve capacity bidding transactions in the day-ahead market and deals balancing in the real-time market. To demonstrate the performance of the proposed scheme, markets comprising various participants and managed by the system operator are implemented using mathematical models. The proposed method is evaluated using an illustrative system and the practical Taiwan power (Taipower) system with diverse uncertainty levels. The numerical results demonstrate the promising performance and the efficiency of the proposed method. The results also verify the effectiveness of the proposed method VPP with various combinations of renewable energy sources, energy storage systems, and loads.

AB - As an aggregator involved in various renewable energy sources, energy storage systems, and loads, a virtual power plant (VPP) plays a key role as a prosumer. A VPP may enable itself to supply energy and ancillary services to the utility grid. This paper proposes a novel scheme for optimizing the operation and bidding strategy of VPPs. By scheduling the energy storage systems, demand response, and renewable energy sources, VPPs can join bidding markets to achieve maximum benefits. The potential uncertainties caused by renewable energy sources and the demand response are considered in a robust optimization model. Moreover, the robust VPP optimization accounts for its influence on markets to ensure optimal energy and reserve capacity bidding transactions in the day-ahead market and deals balancing in the real-time market. To demonstrate the performance of the proposed scheme, markets comprising various participants and managed by the system operator are implemented using mathematical models. The proposed method is evaluated using an illustrative system and the practical Taiwan power (Taipower) system with diverse uncertainty levels. The numerical results demonstrate the promising performance and the efficiency of the proposed method. The results also verify the effectiveness of the proposed method VPP with various combinations of renewable energy sources, energy storage systems, and loads.

UR - http://www.scopus.com/inward/record.url?scp=85068981284&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85068981284&partnerID=8YFLogxK

U2 - 10.1109/ACCESS.2019.2922700

DO - 10.1109/ACCESS.2019.2922700

M3 - Article

AN - SCOPUS:85068981284

VL - 7

SP - 79798

EP - 79809

JO - IEEE Access

JF - IEEE Access

SN - 2169-3536

M1 - 8736232

ER -