Optimal non-zero Price Bids for EVs in Energy and Reserves Markets using Stochastic Optimization

Koos van der Linden; Mathijs de Weerdt; German Morales-Espana

doi:10.1109/EEM.2018.8470023

Optimal non-zero Price Bids for EVs in Energy and Reserves Markets using Stochastic Optimization

Koos van der Linden, Mathijs de Weerdt, German Morales-Espana

Algorithmics

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

8 Citations (Scopus)

78 Downloads (Pure)

Abstract

In power systems, demand and supply always have to be balanced. This is becoming more challenging due to the sustained penetration of renewable energy sources. Because of the increasing amount of electrical vehicles (EVs), and the high capacity and flexibility of their charging process, EVs are a good candidate for providing balancing services to electric systems. We propose a stochastic optimization method for an EV aggregator that models the uncertainty of the imbalance price, the reserve prices and the probability of acceptance and deployment of reserves. The model results in an optimal charging and discharging strategy considering day-ahead purchase, imbalance trading and reserve bids. Unlike previous studies, the reserve bids consists of both a quantity and an optimal price. Experimental evaluation shows that the proposed stochastic optimization method results in lower costs than deterministic and quantity-only bid solutions.

Original language	English
Title of host publication	2018 15th International Conference on the European Energy Market (EEM)
Subtitle of host publication	Proceedings
Place of Publication	Danvers
Publisher	IEEE
Pages	1-5
Number of pages	5
ISBN (Electronic)	978-1-5386-1488-4
ISBN (Print)	978-1-5386-1489-1
DOIs	https://doi.org/10.1109/EEM.2018.8470023
Publication status	Published - 2018
Event	15th International Conference on the European Energy Market, EEM 2018 - Lodz, Poland Duration: 27 Jun 2018 → 29 Jun 2018

Conference

Conference	15th International Conference on the European Energy Market, EEM 2018
Country/Territory	Poland
City	Lodz
Period	27/06/18 → 29/06/18

Bibliographical note

Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care

Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

Keywords

Electrical vehicles
stochastic opti-mization
reserve markets
day-ahead markets
mixed integer programming

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1109/EEM.2018.8470023

08470023Final published version, 4.69 MB

FFC: Future Proof Flexible Charging: Dealing with uncertain prices and network constraints
de Weerdt, M. M., Spaan, M. T. J., Lane, N. R., Morales Espana, G. A. & van der Linden, J. G. M.
1/02/17 → 15/09/19
Project: Research

Cite this

@inproceedings{5e06c64e60ba41f38ebfabb3e1a83c48,

title = "Optimal non-zero Price Bids for EVs in Energy and Reserves Markets using Stochastic Optimization",

abstract = "In power systems, demand and supply always have to be balanced. This is becoming more challenging due to the sustained penetration of renewable energy sources. Because of the increasing amount of electrical vehicles (EVs), and the high capacity and flexibility of their charging process, EVs are a good candidate for providing balancing services to electric systems. We propose a stochastic optimization method for an EV aggregator that models the uncertainty of the imbalance price, the reserve prices and the probability of acceptance and deployment of reserves. The model results in an optimal charging and discharging strategy considering day-ahead purchase, imbalance trading and reserve bids. Unlike previous studies, the reserve bids consists of both a quantity and an optimal price. Experimental evaluation shows that the proposed stochastic optimization method results in lower costs than deterministic and quantity-only bid solutions.",

keywords = " Electrical vehicles, stochastic opti-mization, reserve markets, day-ahead markets, mixed integer programming",

author = "{van der Linden}, Koos and {de Weerdt}, Mathijs and German Morales-Espana",

note = "Green Open Access added to TU Delft Institutional Repository {\textquoteleft}You share, we take care!{\textquoteright} – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.; 15th International Conference on the European Energy Market, EEM 2018 ; Conference date: 27-06-2018 Through 29-06-2018",

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doi = "10.1109/EEM.2018.8470023",

language = "English",

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publisher = "IEEE",

address = "United States",

}

van der Linden, K , de Weerdt, M & Morales-Espana, G 2018, Optimal non-zero Price Bids for EVs in Energy and Reserves Markets using Stochastic Optimization. in 2018 15th International Conference on the European Energy Market (EEM): Proceedings. IEEE, Danvers, pp. 1-5, 15th International Conference on the European Energy Market, EEM 2018, Lodz, Poland, 27/06/18. https://doi.org/10.1109/EEM.2018.8470023

Optimal non-zero Price Bids for EVs in Energy and Reserves Markets using Stochastic Optimization. / van der Linden, Koos ; de Weerdt, Mathijs; Morales-Espana, German.
2018 15th International Conference on the European Energy Market (EEM): Proceedings. Danvers: IEEE, 2018. p. 1-5.

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

TY - GEN

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AU - de Weerdt, Mathijs

AU - Morales-Espana, German

N1 - Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

PY - 2018

Y1 - 2018

N2 - In power systems, demand and supply always have to be balanced. This is becoming more challenging due to the sustained penetration of renewable energy sources. Because of the increasing amount of electrical vehicles (EVs), and the high capacity and flexibility of their charging process, EVs are a good candidate for providing balancing services to electric systems. We propose a stochastic optimization method for an EV aggregator that models the uncertainty of the imbalance price, the reserve prices and the probability of acceptance and deployment of reserves. The model results in an optimal charging and discharging strategy considering day-ahead purchase, imbalance trading and reserve bids. Unlike previous studies, the reserve bids consists of both a quantity and an optimal price. Experimental evaluation shows that the proposed stochastic optimization method results in lower costs than deterministic and quantity-only bid solutions.

AB - In power systems, demand and supply always have to be balanced. This is becoming more challenging due to the sustained penetration of renewable energy sources. Because of the increasing amount of electrical vehicles (EVs), and the high capacity and flexibility of their charging process, EVs are a good candidate for providing balancing services to electric systems. We propose a stochastic optimization method for an EV aggregator that models the uncertainty of the imbalance price, the reserve prices and the probability of acceptance and deployment of reserves. The model results in an optimal charging and discharging strategy considering day-ahead purchase, imbalance trading and reserve bids. Unlike previous studies, the reserve bids consists of both a quantity and an optimal price. Experimental evaluation shows that the proposed stochastic optimization method results in lower costs than deterministic and quantity-only bid solutions.

KW - Electrical vehicles

KW - stochastic opti-mization

KW - reserve markets

KW - day-ahead markets

KW - mixed integer programming

U2 - 10.1109/EEM.2018.8470023

DO - 10.1109/EEM.2018.8470023

M3 - Conference contribution

SN - 978-1-5386-1489-1

SP - 1

EP - 5

BT - 2018 15th International Conference on the European Energy Market (EEM)

PB - IEEE

CY - Danvers

T2 - 15th International Conference on the European Energy Market, EEM 2018

Y2 - 27 June 2018 through 29 June 2018

ER -

Optimal non-zero Price Bids for EVs in Energy and Reserves Markets using Stochastic Optimization

Abstract

Conference

Bibliographical note

Keywords

UN SDGs

Access to Document

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Projects

FFC: Future Proof Flexible Charging: Dealing with uncertain prices and network constraints

Cite this