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Publications (6 of 6) Show all publications
Song, M., Amelin, M., Wang, X. & Saleem, A. (2019). Planning and operation models for an EV sharing community in spot and balancing market. IEEE Transactions on Smart Grid
Open this publication in new window or tab >>Planning and operation models for an EV sharing community in spot and balancing market
2019 (English)In: IEEE Transactions on Smart Grid, ISSN 1949-3053, E-ISSN 1949-3061Article in journal, News item (Refereed) Published
Abstract [en]

An EV sharing scheme is emerging in residential and business sector. It enables community members to share EVs and make reservations when they plan to use a car. The paper proposes a framework for planning and operation of a shared EV fleet. The framework coordinates charging and reservation assignment, and supports the community to participate in wholesale electricity market. It includes two stochastic programming models for day-ahead planning and real-time operation management. Bids on spot market are determined in the day-ahead planning. A preliminary plan for the bids on balancing market, the charging schedule of each EV and the assignment of each reservation are also determined in this phase. The preliminary plan is further refined during the real-time operation management. A numerical study based on Swedish driving behaviours and Nordic electricity market rules is performed to demonstrate an application of the proposed framework. Examples of the bidding curves on spot and balancing market are illustrated. Results also show a dynamic assignment for reservations during the planning horizon, while the eventual assignment is determined during the real-time operation management. Comparison with a base case shows that the proposed models enable the community to benefit from participating in the wholesale electricity market.

National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:kth:diva-248293 (URN)10.1109/TSG.2019.2900085 (DOI)
Note

QC 20190520

Available from: 2019-04-04 Created: 2019-04-04 Last updated: 2019-05-20Bibliographically approved
Song, M., Amelin, M., Wang, X. & Saleem, A. (2019). Planning and operation models for an EV sharing community in spot and balancing market. IEEE Transactions on Smart Grid
Open this publication in new window or tab >>Planning and operation models for an EV sharing community in spot and balancing market
2019 (English)In: IEEE Transactions on Smart Grid, ISSN 1949-3053, E-ISSN 1949-3061Article in journal (Refereed) Published
Abstract [en]

An EV sharing scheme is emerging in residential and business sector. It enables community members to share EVs and make reservations when they plan to use a car. The paper proposes a framework for planning and operation of a shared EV fleet. The framework coordinates charging and reservation assignment, and supports the community to participate in wholesale electricity market. It includes two stochastic programming models for day-ahead planning and real-time operation management. Bids on spot market are determined in the day-ahead planning. A preliminary plan for the bids on balancing market, the charging schedule of each EV and the assignment of each reservation are also determined in this phase. The preliminary plan is further refined during the real-time operation management. A numerical study based on Swedish driving behaviours and Nordic electricity market rules is performed to demonstrate an application of the proposed framework. Examples of the bidding curves on spot and balancing market are illustrated. Results also show a dynamic assignment for reservations during the planning horizon, while the eventual assignment is determined during the real-time operation management. Comparison with a base case shows that the proposed models enable the community to benefit from participating in the wholesale electricity market.

National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:kth:diva-250467 (URN)10.1109/TSG.2019.2900085 (DOI)
Note

QC 20190520

Available from: 2019-04-30 Created: 2019-04-30 Last updated: 2019-05-20Bibliographically approved
Song, M., Amelin, M., Shayesteh, E. & Hilber, P. (2018). Impacts of flexible demand on the reliability of power systems. In: : . Paper presented at 2018 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT).
Open this publication in new window or tab >>Impacts of flexible demand on the reliability of power systems
2018 (English)Conference paper, Published paper (Refereed)
Abstract [en]

Demand response provides flexibility to power systems through adjusting the power consumption. This study investigates the impact of flexible demands on the system reliability with real-time price-based demand response. It assumes that the power demand is sensitive to nodal price and the price is communicated to consumers as soon as it is cleared on market. The uncertainties of nodal price and potential flexibility are considered. Models are proposed for the optimal operation of a power system with and without demand response, respectively. The proposed models are evaluated through application to a 6-bus system using Monte Carlo simulation. The result shows that the reliability indices LOLP and EENS are improved for the system and for each bus when the demand is sensitive to nodal price. Moreover, the nodal prices decrease, reflecting a more efficient operation and a lower electricity price charged on consumers.

National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:kth:diva-250468 (URN)10.1109/ISGT.2018.8403357 (DOI)2-s2.0-85050701617 (Scopus ID)
Conference
2018 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT)
Note

QC 20190520

Available from: 2019-04-30 Created: 2019-04-30 Last updated: 2019-05-20Bibliographically approved
Song, M., Amelin, M., Wang, X. & Saleem, A. (2018). Optimized Operational Management of an EV Sharing Community Integrated with Battery Energy Storage and PV Generation. In: International Conference on the European Energy Market, EEM: . Paper presented at 2018 15th International Conference on the European Energy Market (EEM). IEEE conference proceedings
Open this publication in new window or tab >>Optimized Operational Management of an EV Sharing Community Integrated with Battery Energy Storage and PV Generation
2018 (English)In: International Conference on the European Energy Market, EEM, IEEE conference proceedings, 2018Conference paper, Published paper (Refereed)
Abstract [en]

Sharing schemes are emerging in residential and business sectors to reduce the purchase and operation cost of individuals. This paper proposes a framework to support the operational management of a shared EV fleet. An optimization algorithm is developed to coordinate the charging and reservation assignment using mixed integer programming. The integration with local PV production and battery storage is taken into account. A booking algorithm is also developed to determine whether a reservation can be accepted or not. Monte Carlo simulation is performed in the case study to demonstrate an application of the proposed framework with the Swedish travel patterns. The result provides an overview about the utilization rate of the fleet with different number of EVs, which can support the investment decision of an EV sharing community. The result also shows that the EVs and battery are effectively coordinated to minimize the total cost, satisfy the reservations and comply with grid limits.

Place, publisher, year, edition, pages
IEEE conference proceedings, 2018
Keywords
Optimization; Power generation dispatch; Power systems; Renewable energy sources
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:kth:diva-250466 (URN)10.1109/EEM.2018.8469821 (DOI)2-s2.0-85055572394 (Scopus ID)
Conference
2018 15th International Conference on the European Energy Market (EEM)
Note

QC 20190507

Available from: 2019-04-30 Created: 2019-04-30 Last updated: 2019-05-07Bibliographically approved
Song, M., Amelin, M., Wang, X. & Saleem, A. (2018). Optimized operational management of an EVsharing community integrated with battery energystorage and PV generation. In: International Conference on the European Energy Market, EEM 2018: . Paper presented at 15th International Conference on the European Energy Market, EEM 2018; Lodz; Poland; 27 June 2018 through 29 June 2018. IEEE Computer Society, Article ID 8469821.
Open this publication in new window or tab >>Optimized operational management of an EVsharing community integrated with battery energystorage and PV generation
2018 (English)In: International Conference on the European Energy Market, EEM 2018, IEEE Computer Society, 2018, article id 8469821Conference paper, Published paper (Refereed)
Abstract [en]

Sharing schemes are emerging in residential and business sectors to reduce the purchase and operation cost of individuals. This paper proposes a framework to support the operational management of a shared EV fleet. An optimization algorithm is developed to coordinate the charging and reservation assignment using mixed integer programming. The integration with local PV production and battery storage is taken into account. A booking algorithm is also developed to determine whether a reservation can be accepted or not. Monte Carlo simulation is performed in the case study to demonstrate an application of the proposed framework with the Swedish travel patterns. The result provides an overview about the utilization rate of the fleet with different number of EVs, which can support the investment decision of an EV sharing community. The result also shows that the EVs and battery are effectively coordinated to minimize the total cost, satisfy the reservations and comply with grid limits.

Place, publisher, year, edition, pages
IEEE Computer Society, 2018
Series
International Conference on the European Energy Market, EEM, ISSN 2165-4077
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:kth:diva-248294 (URN)10.1109/EEM.2018.8469821 (DOI)2-s2.0-85055572394 (Scopus ID)9781538614884 (ISBN)
Conference
15th International Conference on the European Energy Market, EEM 2018; Lodz; Poland; 27 June 2018 through 29 June 2018
Note

QC 20190520

Available from: 2019-04-04 Created: 2019-04-04 Last updated: 2019-08-21Bibliographically approved
Song, M. & Amelin, M. (2018). Price-Maker Bidding in Day-Ahead Electricity Market for a Retailer With Flexible Demands. IEEE Transactions on Power Systems, 33(2), 1948-1958
Open this publication in new window or tab >>Price-Maker Bidding in Day-Ahead Electricity Market for a Retailer With Flexible Demands
2018 (English)In: IEEE Transactions on Power Systems, ISSN 0885-8950, E-ISSN 1558-0679, Vol. 33, no 2, p. 1948-1958Article in journal (Refereed) Published
Abstract [en]

This study develops a short-term planning model to determine the bidding curves on a day-ahead market for a price-maker retailer with flexible power demand. It concerns the interactions between the spot price and the flexible demand. Both conditional value-at-risk and volume deviation risk are taken into account. A numerical study using the data from the Nordic electricity market is performed to investigate the influence of risk factors on the retailer's profit, risk levels, average spot price, and total consumption. Three types of price elasticity are compared to show that the retailer can benefit from the flexibility in demand side in some cases. The flexibility also leads to lower spot prices so that the customers in real-time price-based demand response can face a lower electricity price for per-unit power consumption.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2018
Keywords
Bidding curve, demand response, price elasticity, price-maker, retailer, risk
National Category
Economics Energy Systems
Identifiers
urn:nbn:se:kth:diva-224017 (URN)10.1109/TPWRS.2017.2741000 (DOI)000425530300070 ()2-s2.0-85028448673 (Scopus ID)
Note

QC 20180323

Available from: 2018-03-23 Created: 2018-03-23 Last updated: 2018-05-24Bibliographically approved
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0001-6870-6104

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