A non-linear convex cost model for economic dispatch in microgrids. (15th July 2018)

• Record Type: Journal Article
• Authors: Bhattacharjee, Vikram; Khan, Irfan
• Is Part Of: Applied energy. Volume 222(2018)
• Page Start: 637
• Page End: 648
• Publication Date: 2018-07-15
• Subjects: Capacity fade -- Charging/discharging efficiency -- Fuel savings -- Economic dispatch; Power (Mechanics) -- Periodicals; Energy conservation -- Periodicals; Energy conversion -- Periodicals; 621.042
• DOI: 10.1016/j.apenergy.2018.04.001
• Languages: English
• ISSNs: 0306-2619

Abstract

Highlights: A cost model for a microgrid has been presented. It incorporates the effects of battery pack degradation and intermittent DGs. The model takes into account load demand and generation balance. The non-linear cost model has been proved to be convex. Cost savings is more when compared to generic models of economic dispatch. Abstract: This paper proposes a convex non-linear cost saving model for optimal economic dispatch in a microgrid. The model incorporates energy storage degradation cost and intermittent renewable generation. Cell degradation cost being a non-linear model, its incorporation in an objective function alters the convexity of the optimization problem and stochastic algorithms are required for its solution. This paper builds on the scope for usage of macroscopically semi-empirical models for degradation cost in economic dispatch problems and proves that these cost models derived from the existing semi-empirical capacity fade equations for LiFePO4 cells are convex under some operating conditions. The proposed non-linear model was tested on two data sets of varying size which portray different trends of seasonality. The results show that the model reflects the trends of seasonality existing in the data sets and it minimizes the total fuel cost globally when compared to conventional systems of economic dispatch. The results thus indicate that the model achieves a more accurate estimate of fuel cost in the system and can be effectively utilized for cost analysis in power system applications.