skip to main content
OSTI.GOV title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: Day-Ahead Optimal Operation for Multi-Energy Residential Systems with Renewables

Journal Article · · IEEE Transactions on Sustainable Energy
 [1];  [2];  [1];  [3]
  1. Univ. of Saskatchewan, Saskatoon, SK (Canada). Dept. of Electrical and Computer Engineering
  2. Univ. of Saskatchewan, Saskatoon, SK (Canada). Dept. of Electrical and Computer Engineering; Brookhaven National Lab. (BNL), Upton, NY (United States). Sustainable Energy Technologies Dept.
  3. Zhejiang Univ., Hangzhou (China). School of Electrical Engineering
+ Show Author Affiliations

The intermittency and stochasticity nature of distributed renewable energy sources has introduced great challenges to the efficiency and security of energy distribution system operations. To address the negative impacts of intermittent renewable energy sources, this paper proposes here a day-ahead optimal operation strategy utilizing distributed energy resources based on the framework of the interconnected multi-energy system. First, a framework and mathematical models of multi-energy residential systems (MERS) are proposed. Based on the characteristics of residential energy distribution networks, the complex MERS models are reformulated to relieve the computational burden. Furthermore, the uncertainty factors such as renewable energy generation fluctuations and demand variations are handled by a reformulated chance con-strained programming technique. The feasibility and effectiveness of the proposed method are validated through a combined electric power and natural gas test system. Compared to similar models and methods in the existing literature, the proposed method performs better in terms of solution time, model scalability, and robustness in handling uncertainties.

Research Organization:
Brookhaven National Lab. (BNL), Upton, NY (United States); Univ. of Saskatchewan, Saskatoon, SK (Canada)
Sponsoring Organization:
USDOE
Grant/Contract Number:
SC0012704
OSTI ID:
1501583
Report Number(s):
BNL-211393-2019-JAAM
Journal Information:
IEEE Transactions on Sustainable Energy, Vol. 10, Issue 4; ISSN 1949-3029
Publisher:
IEEECopyright Statement
Country of Publication:
United States
Language:
English
Citation Metrics:
Cited by: 21 works
Citation information provided by
Web of Science

Figures / Tables (12)

Fig. 1(p. 4)figure Fig. 1
Fig. 2(p. 9)figure Fig. 2
Fig. 3.(p. 9)figure Fig. 3.
TABLE I(p. 9)table TABLE I
TABLE II(p. 9)table TABLE II
TABLE III(p. 9)table TABLE III
Fig. 4(p. 10)figure Fig. 4
TABLE IV(p. 10)table TABLE IV
TABLE V(p. 10)table TABLE V
TABLE VI(p. 10)table TABLE VI
TABLE VII(p. 11)table TABLE VII
TABLE VIII(p. 11)table TABLE VIII

Similar Records

Chance-Constrained AC Optimal Power Flow for Distribution Systems With Renewables
Journal Article · Fri Sep 01 00:00:00 EDT 2017 · IEEE Transactions on Power Systems · OSTI ID:1501583
Operation of a High Renewable Penetrated Power System With CSP Plants: A Look-Ahead Stochastic Unit Commitment Model
Journal Article · Tue Jan 01 00:00:00 EST 2019 · IEEE Transactions on Power Systems · OSTI ID:1501583
+5 more
Arbitrage and Capacity Firming in Coordination with Day-Ahead Bidding of a Hybrid PV Plant: Preprint
Conference · Wed Oct 05 00:00:00 EDT 2022 · OSTI ID:1501583
+1 more

Related Subjects

24 POWER TRANSMISSION AND DISTRIBUTION
distributed energy resources
energy storage
multi-energy system
renewable energy