A multi-objective optimization framework for integrated electricity and natural gas networks considering smart homes in downward under uncertainties. (15th January 2022)

• Record Type: Journal Article
• Authors: Safaie, Amir Abbas; Alizadeh Bidgoli, Mohsen; Javadi, Saeid
• Is Part Of: Energy. Volume 239:Part C(2022)
• Publication Date: 2022-01-15
• Subjects: Integrated electricity and natural gas networks -- Smart homes -- Multi-objective optimization -- Emissions -- User comfort -- Uncertainties; Power resources -- Periodicals; Power (Mechanics) -- Periodicals; Energy consumption -- Periodicals; 333.7905
• DOI: 10.1016/j.energy.2021.122214
• Languages: English
• ISSNs: 0360-5442

Abstract

Abstract: This paper presents a multi-objective optimization framework for day-ahead scheduling of integrated electricity and natural gas networks in the presence of five sets of smart homes. The study system includes a 69-bus electricity distribution network and a 14-node natural gas network, equipped with gas turbines, wind turbines, photovoltaic (PV) panels, electrical energy storage (EES) systems and power-to-gas (P2G) technologies. The scheduling problem is modeled as a two-objective optimization problem and its objectives include minimizing the operation cost and CO2 emissions. In order to model the two-objective optimization problem, the epsilon-constraint method has been adopted. Finally, the proposed model has been solved in the form of 3 case studies by CPLEX solver in general algebraic modeling system (GAMS) software. The simulation results demonstrate that the two-objective modeling of the scheduling problem leads to a 2.87% reduction in CO2 emissions despite a 0.75% increase in operating costs. The results also illustrate that a 21.93% increase in the customer's comfort index leads to a 41% increase in annual operating costs. Finally, the results substantiate that the installation of P2G technologies along with wind turbines prevents wind power curtailment in some hours. Graphical abstract: Image 1 Highlights: Providing a stochastic multi-objective model for power and gas networks scheduling. Considering the security constraints of power and gas networks. Considering smart homes and their comfort index in the model. Solving the operation problem for four seasons with different load demand pattern. Analyzing the effect of uncertainties and the comfort index on the operating cost.