A cost-emission trade-offs in hybrid energy systems using a multi-objective approach with demand response integration
Abstract
In the past, there was little emphasis on the types of energy sources used to supply power to loads. The grid upstream was the sole energy resource relied upon to meet electrical demand. Operators are now encouraged to incorporate innovative energy technologies into the primary power grid. This approach helps ensure a reliable electricity supply while reducing dependence on the main grid to meet demand. This chapter examines the integration of various energy forms, including photovoltaic solar power (PV), hydrogen fuel cells (FCs), and battery capacity (BAT), into an on-grid hybrid energy system (HES). This study introduces a multi-objective optimization model to address the cost-emission challenges of a PV-FC-BAT HES, incorporating the effects of a demand response program (DRP). The proposed model aims to reduce the overall cost of the HES and decrease CO2 emissions simultaneously. The framework is resolved through a weighted sum strategy, and an optimal response is determined by implementing a fuzzy constraint satisfaction approach. DRP redistributes a portion of the energy demand from high-demand periods to other periods, resulting in a more even load distribution and reducing the overall cost of the system. The HES’s cost-emission operating problem is formulated as a mixed-integer linear (MILP) program and solved using a software called GAMS. Two distinct examples were analyzed to illustrate the impacts of DRP, and the findings were contrasted.
Document Type
Book Chapter
Date of Publication
1-1-2025
Volume
Part F958
Publication Title
Sustainable Energy Resources in Smart Cities
Publisher
Springer
School
School of Engineering
RAS ID
84804
Copyright
subscription content
First Page
151
Last Page
173
Comments
Ghahramani, M., Ghahramani, M., & Abapour, M. (2025). A cost-emission trade-offs in hybrid energy systems using a multi-objective approach with demand response integration. In Sustainable energy resources in smart cities (pp. 151–173). Springer Nature. https://doi.org/10.1007/978-3-031-91516-1_6