Optimal energy scheduling for residential consumers with demand management strategies

ABSTRACT

The enhancement of energy networks and cost reduction can be achieved through the implementation of solutions like optimal energy scheduling for residential consumers. This paper proposes day-ahead electrical and thermal energy scheduling for residential sections in energy networks as a bi-criteria optimization approach. The bi-criteria optimization approach is modeled to minimize the operation cost and maximize the reliability of the energy system. Demand management strategies such as demand reduction and demand shifting are considered for residential consumers. The participation of residential consumers in demand management is presented considering electricity prices in the energy markets. The solving bi-criteria optimization approach is done via the weight sum method and LINMAP procedure-based-fuzzy approach. The proposed modeling is implemented in GAMS optimization software for verifying the demand management strategies in optimal energy scheduling in two case studies.

GRAPHICAL ABSTRACT

KEYWORDS:

• Residential consumers
• bi-criteria optimization approach
• demand management strategies
• weight sum method
• LINMAP procedure

Nomenclature

$\mathit{t}.\mathit{T}$	=	Time Index
$\mathit{ds}.\mathit{DS}$	=	Index of Consumers with Demand Shifting Program
$\mathit{U}.\mathit{u}$	=	Generator unit (GU) Index
$\mathit{E}{D}_{\mathit{DS}}$	=	Electrical demand with Demand shifting program
$\mathrm{\Theta }$	=	Demand shifting rate
α,β,χ	=	Cost factors of GUs for electrical generation
ω, ξ, ψ	=	Cost factors of GUs for thermal generation
P,T	=	Electrical and thermal generation by GUs
DDR,ϒ(k)	=	Value of the demand reduction and bide price in interval k
CEM, PEM	=	Electricity price and power generation by the electrical market
DE, DT	=	Total electrical and thermal demand
DNS	=	Value of the non-supply electrical demand
ure	=	Binary variable for reliability index

Disclosure statement

No potential conflict of interest was reported by the author(s).

Supplementary Material

Supplemental data for this article can be accessed online at https://doi.org/10.1080/23080477.2024.2355767

Additional information

Funding

This work was supported by Key Courses Construction Project of Xi’an Eurasia University (2019KC026); Project of Shaanxi Provincial Sports Bureau (2022307); The Innovation Team of Eurasia University (2021XJTD08); Xi’an Social Science Foundation Project (23JX116); Xi’an Social Science Foundation Project (23JX118).