Optimal stochastic deployment of heterogeneous energy storage in a residential multienergy microgrid with demand-side management
The optimal deployment of heterogeneous energy storage (HES), mainly consisting of electrical and thermal energy storage, is essential for increasing the holistic energy utilization efficiency of multienergy systems. Consequently, this article proposes a risk-averse method for HES deployment in a re...
| Main Authors: | , , , |
|---|---|
| Other Authors: | |
| Format: | Journal Article |
| Language: | English |
| Published: |
2022
|
| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/155299 |
| _version_ | 1811689698876194816 |
|---|---|
| author | Li, Zhengmao Xu, Yan Feng, Xue Wu, Qiuwei |
| author2 | School of Electrical and Electronic Engineering |
| author_facet | School of Electrical and Electronic Engineering Li, Zhengmao Xu, Yan Feng, Xue Wu, Qiuwei |
| author_sort | Li, Zhengmao |
| collection | NTU |
| description | The optimal deployment of heterogeneous energy storage (HES), mainly consisting of electrical and thermal energy storage, is essential for increasing the holistic energy utilization efficiency of multienergy systems. Consequently, this article proposes a risk-averse method for HES deployment in a residential multienergy microgrid (RMEMG), considering the diverse uncertainties and multienergy demand-side management (DSM). Apart from the HES size and location planning, its optimal investment phase is also determined by maximizing the system equivalent daily profit (EDP) and minimizing the risk. To handle the system uncertainties from renewable energy sources, power demands, outdoor temperature, and residential hot water needs, the multistage adaptive stochastic optimization approach is utilized. Then, through the constraint linearization and stochastic scenario sampling, the original nonlinear deployment model is converted to a mixed-integer linear programming one and tested on an IEEE 33-bus distribution network based RMEMG. The effectiveness of the proposed method is verified by comparing it with the existing practices. The comparison results indicate that the proposed risk-averse deployment method can effectively increase the system EDP and more immune to the uncertainties. Besides, this method can be practically applied for the emerging RMEMGs, such as smart buildings, intelligent homes, etc., which get long-term DSM contracts. |
| first_indexed | 2024-10-01T05:52:15Z |
| format | Journal Article |
| id | ntu-10356/155299 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T05:52:15Z |
| publishDate | 2022 |
| record_format | dspace |
| spelling | ntu-10356/1552992022-03-17T06:14:17Z Optimal stochastic deployment of heterogeneous energy storage in a residential multienergy microgrid with demand-side management Li, Zhengmao Xu, Yan Feng, Xue Wu, Qiuwei School of Electrical and Electronic Engineering Engineering::Electrical and electronic engineering Heterogeneous Energy Storage Multienergy Demand-Side Management The optimal deployment of heterogeneous energy storage (HES), mainly consisting of electrical and thermal energy storage, is essential for increasing the holistic energy utilization efficiency of multienergy systems. Consequently, this article proposes a risk-averse method for HES deployment in a residential multienergy microgrid (RMEMG), considering the diverse uncertainties and multienergy demand-side management (DSM). Apart from the HES size and location planning, its optimal investment phase is also determined by maximizing the system equivalent daily profit (EDP) and minimizing the risk. To handle the system uncertainties from renewable energy sources, power demands, outdoor temperature, and residential hot water needs, the multistage adaptive stochastic optimization approach is utilized. Then, through the constraint linearization and stochastic scenario sampling, the original nonlinear deployment model is converted to a mixed-integer linear programming one and tested on an IEEE 33-bus distribution network based RMEMG. The effectiveness of the proposed method is verified by comparing it with the existing practices. The comparison results indicate that the proposed risk-averse deployment method can effectively increase the system EDP and more immune to the uncertainties. Besides, this method can be practically applied for the emerging RMEMGs, such as smart buildings, intelligent homes, etc., which get long-term DSM contracts. Ministry of Education (MOE) Nanyang Technological University National Research Foundation (NRF) This work was supported in part by the Ministry of Education (MOE), Republic of Singapore, under Grant AcRF TIER 1 2019-T1-001- 069 (RG75/19) and in part by National Research Foundation (NRF) of Singapore under project NRF2018 -SR2001-018. The work of Yan Xu was supported by Nanyang Assistant Professorship from Nanyang Technological University, Singapore. Paper no. TII-19-4943. 2022-03-17T06:14:17Z 2022-03-17T06:14:17Z 2020 Journal Article Li, Z., Xu, Y., Feng, X. & Wu, Q. (2020). Optimal stochastic deployment of heterogeneous energy storage in a residential multienergy microgrid with demand-side management. IEEE Transactions On Industrial Informatics, 17(2), 991-1004. https://dx.doi.org/10.1109/TII.2020.2971227 1551-3203 https://hdl.handle.net/10356/155299 10.1109/TII.2020.2971227 2-s2.0-85096767127 2 17 991 1004 en 2019-T1-001- 069 (RG75/19) NRF2018 -SR2001-018 TII-19-4943 IEEE Transactions on Industrial Informatics © 2020 IEEE. All rights reserved. |
| spellingShingle | Engineering::Electrical and electronic engineering Heterogeneous Energy Storage Multienergy Demand-Side Management Li, Zhengmao Xu, Yan Feng, Xue Wu, Qiuwei Optimal stochastic deployment of heterogeneous energy storage in a residential multienergy microgrid with demand-side management |
| title | Optimal stochastic deployment of heterogeneous energy storage in a residential multienergy microgrid with demand-side management |
| title_full | Optimal stochastic deployment of heterogeneous energy storage in a residential multienergy microgrid with demand-side management |
| title_fullStr | Optimal stochastic deployment of heterogeneous energy storage in a residential multienergy microgrid with demand-side management |
| title_full_unstemmed | Optimal stochastic deployment of heterogeneous energy storage in a residential multienergy microgrid with demand-side management |
| title_short | Optimal stochastic deployment of heterogeneous energy storage in a residential multienergy microgrid with demand-side management |
| title_sort | optimal stochastic deployment of heterogeneous energy storage in a residential multienergy microgrid with demand side management |
| topic | Engineering::Electrical and electronic engineering Heterogeneous Energy Storage Multienergy Demand-Side Management |
| url | https://hdl.handle.net/10356/155299 |
| work_keys_str_mv | AT lizhengmao optimalstochasticdeploymentofheterogeneousenergystorageinaresidentialmultienergymicrogridwithdemandsidemanagement AT xuyan optimalstochasticdeploymentofheterogeneousenergystorageinaresidentialmultienergymicrogridwithdemandsidemanagement AT fengxue optimalstochasticdeploymentofheterogeneousenergystorageinaresidentialmultienergymicrogridwithdemandsidemanagement AT wuqiuwei optimalstochasticdeploymentofheterogeneousenergystorageinaresidentialmultienergymicrogridwithdemandsidemanagement |