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Author:

Ju, Liwei (Ju, Liwei.) | Liu, Li (Liu, Li.) | Han, Yingzhu (Han, Yingzhu.) | Yang, Shenbo (Yang, Shenbo.) | Li, Gen (Li, Gen.) | Lu, Xiaolong (Lu, Xiaolong.) | Liu, Yi (Liu, Yi.) | Qiao, Huiting (Qiao, Huiting.)

Indexed by:

EI Scopus SCIE

Abstract:

To realize renewable and self-sustainable energy supply in island region, based on geographical characteristics with abundant renewable resources, an optimal model for island micro energy grid (MEG) is designed incor-porating biomass waste energy conversion system (ECS), desalination, and power-to-hydrogen (BSP-MEG) Firstly, the mathematical model is designed, including models of power generators, ECS, desalination and power -to-hydrogen (P2H) devices, etc. Next, the multi-objective scheduling optimization model is designed, containing conventional scheduling model (Scheduling optimization objectives and constraints established with minimum operation and environment costs) and stochastic scheduling model (Minimum Conditional Value-at-Risk objective specific to volatility and uncertainty of renewable generations based on robust stochastic optimiza-tion method). Then, to solve the multi-objective optimization problem (MOP), a hybrid differential evolution algorithm is proposed based on local optimal and external archiving strategies. Finally, the MEG of YongXing Island is selected as an example. The results show (1) BSP-MEG effectively realized multi-energy cooperative optimization, and promote intra-day peak shaving. (2) BSP-MEG reduced operating costs, environmental costs and Conditional Value-at-Risk (CVaR) by 78.2%, 61.8% and 77.9% respectively, while curtailment rate by 25.6 to 0.9%. (3) Whether in general scenario or worst, BSP-MEG can realize self-production and self-sale of energy and material, of which risk resistance ability is better. (4) By designing local optimal and external archiving strategies, hybrid differential evolution algorithm performs better in solving complex MOP. In general, the optimization model proposed in this paper can improve the utilization of renewable resources, alleviate the shortage of fresh water, and help realize renewable and sustainable energy supply.

Keyword:

Micro energy grid Multi -objective optimization P2H Desalination Biomass waste energy conversion Robust optimization

Author Community:

  • [ 1 ] [Ju, Liwei]North China Elect Power Univ, Sch Econ & Management, Beijing 102206, Peoples R China
  • [ 2 ] [Liu, Li]North China Elect Power Univ, Sch Econ & Management, Beijing 102206, Peoples R China
  • [ 3 ] [Han, Yingzhu]North China Elect Power Univ, Sch Econ & Management, Beijing 102206, Peoples R China
  • [ 4 ] [Lu, Xiaolong]North China Elect Power Univ, Sch Econ & Management, Beijing 102206, Peoples R China
  • [ 5 ] [Liu, Yi]North China Elect Power Univ, Sch Econ & Management, Beijing 102206, Peoples R China
  • [ 6 ] [Ju, Liwei]North China Elect Power Univ, Beijing Key Lab New Energy & Low Carbon Dev, Beijing 102206, Peoples R China
  • [ 7 ] [Liu, Li]North China Elect Power Univ, Beijing Key Lab New Energy & Low Carbon Dev, Beijing 102206, Peoples R China
  • [ 8 ] [Han, Yingzhu]North China Elect Power Univ, Beijing Key Lab New Energy & Low Carbon Dev, Beijing 102206, Peoples R China
  • [ 9 ] [Lu, Xiaolong]North China Elect Power Univ, Beijing Key Lab New Energy & Low Carbon Dev, Beijing 102206, Peoples R China
  • [ 10 ] [Liu, Yi]North China Elect Power Univ, Beijing Key Lab New Energy & Low Carbon Dev, Beijing 102206, Peoples R China
  • [ 11 ] [Yang, Shenbo]Beijing Univ Technol, Coll Econ & Management, Beijing 100124, Peoples R China
  • [ 12 ] [Li, Gen]Tech Univ Denmark DTU, Dept Engn Technol & Didact, DK-2750 Ballerup, Denmark
  • [ 13 ] [Qiao, Huiting]China Southern Power Grid Energy Dev Res Inst Co L, Tech & Econ Ctr, Guangzhou 510530, Peoples R China

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Source :

APPLIED ENERGY

ISSN: 0306-2619

Year: 2023

Volume: 343

1 1 . 2 0 0

JCR@2022

ESI Discipline: ENGINEERING;

ESI HC Threshold:19

Cited Count:

WoS CC Cited Count: 21

SCOPUS Cited Count: 22

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 3

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