Optimal air-conditioning load control in distribution network with intermittent renewables
The coordinated operation of controllable loads, such as air-conditioning load, and distributed generation sources in a smart grid environment has drawn significant attention in recent years. To improve the wind power utilization level in the distribution network and minimize the total system operat...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2017-01-01
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| Series: | Journal of Modern Power Systems and Clean Energy |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/8944241/ |
| _version_ | 1818386715549630464 |
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| author | Dongxiao Wang Ke Meng Xiaodan Gao Colin Coates Zhaoyang Dong |
| author_facet | Dongxiao Wang Ke Meng Xiaodan Gao Colin Coates Zhaoyang Dong |
| author_sort | Dongxiao Wang |
| collection | DOAJ |
| description | The coordinated operation of controllable loads, such as air-conditioning load, and distributed generation sources in a smart grid environment has drawn significant attention in recent years. To improve the wind power utilization level in the distribution network and minimize the total system operation costs, this paper proposes a MILP (mixed integer linear programming) based approach to schedule the interruptible air-conditioning loads. In order to mitigate the uncertainties of the stochastic variables including wind power generation, ambient temperature change, and electricity retail price, the rolling horizon optimization (RHO) strategy is employed to continuously update the real-time information and proceed the control window. Moreover, to ensure the thermal comfort of customers, a novel two-parameter thermal model is introduced to calculate the indoor temperature variation more precisely. Simulations on a five node radial distribution network validate the efficiency of the proposed method. |
| first_indexed | 2024-12-14T03:58:27Z |
| format | Article |
| id | doaj.art-d195eeba5a1e4b2f9c0ee563ad5cb03b |
| institution | Directory Open Access Journal |
| issn | 2196-5420 |
| language | English |
| last_indexed | 2024-12-14T03:58:27Z |
| publishDate | 2017-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | Journal of Modern Power Systems and Clean Energy |
| spelling | doaj.art-d195eeba5a1e4b2f9c0ee563ad5cb03b2022-12-21T23:18:01ZengIEEEJournal of Modern Power Systems and Clean Energy2196-54202017-01-0151556510.1007/s40565-016-0254-z8944241Optimal air-conditioning load control in distribution network with intermittent renewablesDongxiao Wang0Ke Meng1Xiaodan Gao2Colin Coates3Zhaoyang Dong4Centre for Intelligent Electricity Networks, The University of Newcastle,Callaghan,NSW,Australia,2308School of Electrical and Information Engineering, The University of Sydney,Sydney,NSW,Australia,2006Centre for Intelligent Electricity Networks, The University of Newcastle,Callaghan,NSW,Australia,2308School of Electrical Engineering and Computer Science, The University of Newcastle,Callaghan,NSW,Australia,2308School of Electrical and Information Engineering, The University of Sydney,Sydney,NSW,Australia,2006The coordinated operation of controllable loads, such as air-conditioning load, and distributed generation sources in a smart grid environment has drawn significant attention in recent years. To improve the wind power utilization level in the distribution network and minimize the total system operation costs, this paper proposes a MILP (mixed integer linear programming) based approach to schedule the interruptible air-conditioning loads. In order to mitigate the uncertainties of the stochastic variables including wind power generation, ambient temperature change, and electricity retail price, the rolling horizon optimization (RHO) strategy is employed to continuously update the real-time information and proceed the control window. Moreover, to ensure the thermal comfort of customers, a novel two-parameter thermal model is introduced to calculate the indoor temperature variation more precisely. Simulations on a five node radial distribution network validate the efficiency of the proposed method.https://ieeexplore.ieee.org/document/8944241/Demand side managementAir-conditioning loadBattery energy storage systemRolling horizon optimization |
| spellingShingle | Dongxiao Wang Ke Meng Xiaodan Gao Colin Coates Zhaoyang Dong Optimal air-conditioning load control in distribution network with intermittent renewables Journal of Modern Power Systems and Clean Energy Demand side management Air-conditioning load Battery energy storage system Rolling horizon optimization |
| title | Optimal air-conditioning load control in distribution network with intermittent renewables |
| title_full | Optimal air-conditioning load control in distribution network with intermittent renewables |
| title_fullStr | Optimal air-conditioning load control in distribution network with intermittent renewables |
| title_full_unstemmed | Optimal air-conditioning load control in distribution network with intermittent renewables |
| title_short | Optimal air-conditioning load control in distribution network with intermittent renewables |
| title_sort | optimal air conditioning load control in distribution network with intermittent renewables |
| topic | Demand side management Air-conditioning load Battery energy storage system Rolling horizon optimization |
| url | https://ieeexplore.ieee.org/document/8944241/ |
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