PV energy sharing cloud: Towards automatic pricing and energy management

Nian Liu; Cheng Wang; Xinghuo Yu; Jiangxia Zhong; Chaojie Li

doi:10.1109/PESGM.2016.7741865

PV energy sharing cloud: Towards automatic pricing and energy management

Nian Liu, Cheng Wang, Xinghuo Yu, Jiangxia Zhong, Chaojie Li

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

5 Citations (Scopus)

Abstract

According to the energy policy for encouraging local consumption of photovoltaic (PV) energy, the energy sharing among PV prosumers could be more beneficial than the independent operation of PV prosumers. In order to improve the energy sharing at the community level, a concept of PV energy sharing cloud is proposed, which consists of self-organizing, auto-pricing and distributed optimization. Based on the physical access point of PV prosumers on the utility grid, the PV prosumers can be separated into a number of clusters. A day-ahead auto-pricing of shared PV energy is proposed for different clusters. A cost model for PV prosumers is proposed, which enables the PV prosumers participate in the Demand Response (DR). In order to implement the interaction between the cloud and prosumers, a distributed optimization algorithm is utilized. Finally, via a practical example, the effectiveness of the method is verified in terms of saving PV prosumers' cost and improve the sharing of the PV energy. © 2016 IEEE.

Original language	English
Title of host publication	2016 IEEE Power and Energy Society General Meeting, PESGM 2016
Publisher	IEEE Computer Society
Volume	2016-November
ISBN (Print)	9781509041688
DOIs	https://doi.org/10.1109/PESGM.2016.7741865
Publication status	Published - 10 Nov 2016
Externally published	Yes
Event	2016 IEEE Power and Energy Society General Meeting, PESGM 2016 - Boston, United States Duration: 17 Jul 2016 → 21 Jul 2016

Publication series

Name	IEEE Power and Energy Society General Meeting
Volume	2016-November
ISSN (Print)	1944-9925
ISSN (Electronic)	1944-9933

Conference

Conference	2016 IEEE Power and Energy Society General Meeting, PESGM 2016
Place	United States
City	Boston
Period	17/07/16 → 21/07/16

Bibliographical note

Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to <a href="mailto:[email protected]">[email protected]</a>.

UN SDGs

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

SDG 7 Affordable and Clean Energy

Research Keywords

Cloud
Distributed optimization demand response
Pricing

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10.1109/PESGM.2016.7741865

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title = "PV energy sharing cloud: Towards automatic pricing and energy management",

abstract = "According to the energy policy for encouraging local consumption of photovoltaic (PV) energy, the energy sharing among PV prosumers could be more beneficial than the independent operation of PV prosumers. In order to improve the energy sharing at the community level, a concept of PV energy sharing cloud is proposed, which consists of self-organizing, auto-pricing and distributed optimization. Based on the physical access point of PV prosumers on the utility grid, the PV prosumers can be separated into a number of clusters. A day-ahead auto-pricing of shared PV energy is proposed for different clusters. A cost model for PV prosumers is proposed, which enables the PV prosumers participate in the Demand Response (DR). In order to implement the interaction between the cloud and prosumers, a distributed optimization algorithm is utilized. Finally, via a practical example, the effectiveness of the method is verified in terms of saving PV prosumers' cost and improve the sharing of the PV energy. {\textcopyright} 2016 IEEE.",

keywords = "Cloud, Distributed optimization demand response, Pricing",

author = "Nian Liu and Cheng Wang and Xinghuo Yu and Jiangxia Zhong and Chaojie Li",

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doi = "10.1109/PESGM.2016.7741865",

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Liu, N, Wang, C, Yu, X, Zhong, J & Li, C 2016, PV energy sharing cloud: Towards automatic pricing and energy management. in 2016 IEEE Power and Energy Society General Meeting, PESGM 2016. vol. 2016-November, 7741865, IEEE Power and Energy Society General Meeting, vol. 2016-November, IEEE Computer Society, 2016 IEEE Power and Energy Society General Meeting, PESGM 2016, Boston, United States, 17/07/16. https://doi.org/10.1109/PESGM.2016.7741865

PV energy sharing cloud: Towards automatic pricing and energy management. / Liu, Nian; Wang, Cheng; Yu, Xinghuo et al.
2016 IEEE Power and Energy Society General Meeting, PESGM 2016. Vol. 2016-November IEEE Computer Society, 2016. 7741865 (IEEE Power and Energy Society General Meeting; Vol. 2016-November).

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

TY - GEN

T1 - PV energy sharing cloud

T2 - 2016 IEEE Power and Energy Society General Meeting, PESGM 2016

AU - Liu, Nian

AU - Wang, Cheng

AU - Yu, Xinghuo

AU - Zhong, Jiangxia

AU - Li, Chaojie

N1 - Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to <a href="mailto:[email protected]">[email protected]</a>.

PY - 2016/11/10

Y1 - 2016/11/10

N2 - According to the energy policy for encouraging local consumption of photovoltaic (PV) energy, the energy sharing among PV prosumers could be more beneficial than the independent operation of PV prosumers. In order to improve the energy sharing at the community level, a concept of PV energy sharing cloud is proposed, which consists of self-organizing, auto-pricing and distributed optimization. Based on the physical access point of PV prosumers on the utility grid, the PV prosumers can be separated into a number of clusters. A day-ahead auto-pricing of shared PV energy is proposed for different clusters. A cost model for PV prosumers is proposed, which enables the PV prosumers participate in the Demand Response (DR). In order to implement the interaction between the cloud and prosumers, a distributed optimization algorithm is utilized. Finally, via a practical example, the effectiveness of the method is verified in terms of saving PV prosumers' cost and improve the sharing of the PV energy. © 2016 IEEE.

AB - According to the energy policy for encouraging local consumption of photovoltaic (PV) energy, the energy sharing among PV prosumers could be more beneficial than the independent operation of PV prosumers. In order to improve the energy sharing at the community level, a concept of PV energy sharing cloud is proposed, which consists of self-organizing, auto-pricing and distributed optimization. Based on the physical access point of PV prosumers on the utility grid, the PV prosumers can be separated into a number of clusters. A day-ahead auto-pricing of shared PV energy is proposed for different clusters. A cost model for PV prosumers is proposed, which enables the PV prosumers participate in the Demand Response (DR). In order to implement the interaction between the cloud and prosumers, a distributed optimization algorithm is utilized. Finally, via a practical example, the effectiveness of the method is verified in terms of saving PV prosumers' cost and improve the sharing of the PV energy. © 2016 IEEE.

KW - Cloud

KW - Distributed optimization demand response

KW - Pricing

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DO - 10.1109/PESGM.2016.7741865

M3 - RGC 32 - Refereed conference paper (with host publication)

SN - 9781509041688

VL - 2016-November

T3 - IEEE Power and Energy Society General Meeting

BT - 2016 IEEE Power and Energy Society General Meeting, PESGM 2016

PB - IEEE Computer Society

Y2 - 17 July 2016 through 21 July 2016

ER -

PV energy sharing cloud: Towards automatic pricing and energy management

Abstract

Publication series

Conference

Bibliographical note

UN SDGs

Research Keywords

Access Output

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