Multi-Objective Operational Cost Management with Minimum Net Emission of a Smart Microgrid

Abstract

This research article considers a microgrid (MG) with various distributed generation sources (DGs) such as microturbine (MT), fuel cell (FC), wind turbine (WT), and solar cell (PV) along with the battery storage system. This article aims to simultaneously minimize operational costs and emissions for a daily schedule, while considering uncertainties such as load demand, market prices, and electricity generated by different renewable energy sources (RESs). This article proposes the slime mould algorithm (SMA) to solve this complex optimization problem. Initially, SMA is tested for three scenarios considering the minimization of operational cost and emission, respectively, as two single objectives. In Scenario A, a reduction of 1.95% in operational cost and 4.57% in emissions is observed compared to the Grasshopper Optimization Algorithm (GOA). In scenarios B and C, SMA reduces operational cost by 0.78% and 2.65%, respectively, while also reducing emissions by 6.27% and 0.28%, respectively, when compared to GOA. The results obtained by other algorithms are worse than those obtained by GOA. This study also showed that SMA effectively considers multi-objective functions by using the weighted sum method and the fuzzy decision-maker to approach the Pareto-optimal solution, achieving a good tradeoff between operational cost and emissions in each scenario.

Keywords:

• battery energy storage system
• energy management
• distributed generation
• microgrid
• net emission
• optimization techniques
• operational cost

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Notes on contributors

Amit Chakraborty

Amit Chakraborty earned his B.Tech. in Electrical Engineering from the National Institute of Technology Agartala, India in 2017. Subsequently, he completed his M.Tech. in the Instrumentation specialization of the Electrical department at the same institute in 2020. During his M.Tech. studies, he was granted the MHRD (Government of India) fellowship. Currently, Amit is pursuing his Ph.D. degree at the National Institute of Technology Silchar, Assam, India. He holds the position of a regular Ph.D. Research Scholar and receives a fellowship from the MOE (Government of India). His primary research focuses on energy management of a microgrid and wireless communication with the aim of minimizing potential disruptions in a system.

Saheli Ray

Saheli Ray was born in Udaipur, Tripura in 1984. She graduated in Electrical Engineering from NIT Agartala (formerly Tripura Engineering College) in 2006. She completed her M. Tech from NIT Silchar in 2009. After that, she joined NIT Agartala as Assistant Professor (contractual) and worked there till June 2018. She also pursued her PhD from NIT Agartala and obtained PhD degree in 2017. In June 2018, she joined Electrical Engineering Department of NIT Silchar as Assistant Professor. The primary focus of her research lies in power system reliability, power distribution systems, microgrid operation and economics, the application of soft computing techniques in power systems, zero net energy buildings, etc.