Multi‐stage coordinated operation of a multi‐energy microgrid with residential demand response under diverse uncertainties
Abstract This paper presents a two‐stage stochastic operation method for a multi‐energy microgrid (MEMG). The method can optimally schedule distributed generators, electric boilers, electrical chillers, and storage devices under the system technical constraints. Various uncertainties from renewable...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2020-09-01
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| Series: | Energy Conversion and Economics |
| Subjects: | |
| Online Access: | https://doi.org/10.1049/enc2.12002 |
| _version_ | 1819120469563932672 |
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| author | Yumin Chen Xue Feng Zhengmao Li Yan Xu Amir Miragha |
| author_facet | Yumin Chen Xue Feng Zhengmao Li Yan Xu Amir Miragha |
| author_sort | Yumin Chen |
| collection | DOAJ |
| description | Abstract This paper presents a two‐stage stochastic operation method for a multi‐energy microgrid (MEMG). The method can optimally schedule distributed generators, electric boilers, electrical chillers, and storage devices under the system technical constraints. Various uncertainties from renewable energy generation, electricity tariff, and load demands are handled by this method. At the same time, the indoor temperature is controlled to guarantee the thermal comfort of customers. At the first stage, the unit commitment of all generators and charging/discharging power of energy storage devices are obtained. At the second stage, real‐time generation outputs from the generators are optimized given the uncertainty realization. The developed model is formulated as a mixed‐integer linear programming (MILP) problem with the objective of minimizing the daily operating cost. Several case studies are carried out to examine the effectiveness and performance of the proposed method. Simulation results show that the proposed method can effectively save the operational cost and, at the same time, maintain the robustness of the MEMG and customers’ thermal comfort. |
| first_indexed | 2024-12-22T06:21:10Z |
| format | Article |
| id | doaj.art-a8f4dc2fca5e42a5b6625b91a393c372 |
| institution | Directory Open Access Journal |
| issn | 2634-1581 |
| language | English |
| last_indexed | 2024-12-22T06:21:10Z |
| publishDate | 2020-09-01 |
| publisher | Wiley |
| record_format | Article |
| series | Energy Conversion and Economics |
| spelling | doaj.art-a8f4dc2fca5e42a5b6625b91a393c3722022-12-21T18:35:58ZengWileyEnergy Conversion and Economics2634-15812020-09-0111203310.1049/enc2.12002Multi‐stage coordinated operation of a multi‐energy microgrid with residential demand response under diverse uncertaintiesYumin Chen0Xue Feng1Zhengmao Li2Yan Xu3Amir Miragha4School of Electrical and Electronics Engineering Nanyang Technological University SingaporeSingapore Institute of Technology SingaporeSchool of Electrical and Electronics Engineering Nanyang Technological University SingaporeSchool of Electrical and Electronics Engineering Nanyang Technological University SingaporeEnergy Research Institute Nanyang Technological University SingaporeAbstract This paper presents a two‐stage stochastic operation method for a multi‐energy microgrid (MEMG). The method can optimally schedule distributed generators, electric boilers, electrical chillers, and storage devices under the system technical constraints. Various uncertainties from renewable energy generation, electricity tariff, and load demands are handled by this method. At the same time, the indoor temperature is controlled to guarantee the thermal comfort of customers. At the first stage, the unit commitment of all generators and charging/discharging power of energy storage devices are obtained. At the second stage, real‐time generation outputs from the generators are optimized given the uncertainty realization. The developed model is formulated as a mixed‐integer linear programming (MILP) problem with the objective of minimizing the daily operating cost. Several case studies are carried out to examine the effectiveness and performance of the proposed method. Simulation results show that the proposed method can effectively save the operational cost and, at the same time, maintain the robustness of the MEMG and customers’ thermal comfort.https://doi.org/10.1049/enc2.12002diverse uncertaintiesmulti‐energy microgrid (MEMG)residential demand responsetwo‐stage stochastic operation |
| spellingShingle | Yumin Chen Xue Feng Zhengmao Li Yan Xu Amir Miragha Multi‐stage coordinated operation of a multi‐energy microgrid with residential demand response under diverse uncertainties Energy Conversion and Economics diverse uncertainties multi‐energy microgrid (MEMG) residential demand response two‐stage stochastic operation |
| title | Multi‐stage coordinated operation of a multi‐energy microgrid with residential demand response under diverse uncertainties |
| title_full | Multi‐stage coordinated operation of a multi‐energy microgrid with residential demand response under diverse uncertainties |
| title_fullStr | Multi‐stage coordinated operation of a multi‐energy microgrid with residential demand response under diverse uncertainties |
| title_full_unstemmed | Multi‐stage coordinated operation of a multi‐energy microgrid with residential demand response under diverse uncertainties |
| title_short | Multi‐stage coordinated operation of a multi‐energy microgrid with residential demand response under diverse uncertainties |
| title_sort | multi stage coordinated operation of a multi energy microgrid with residential demand response under diverse uncertainties |
| topic | diverse uncertainties multi‐energy microgrid (MEMG) residential demand response two‐stage stochastic operation |
| url | https://doi.org/10.1049/enc2.12002 |
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