Grid Optimization and Demand Side Management for Electric Vehicles Penetration in Remote Areas

Abstract

The distributed power system in remote and rural area is the main challenges of the future smart grid development. Compared with traditional gasoline pipelines and gas station construction for fossil fuel vehicles, the high demand of Electric Vehicles (EVs) will then consider breaking their products in the market of remote areas. While the EVs adoption is growing globally, remote areas present unique challenges such as limited charging infrastructure, long transmission distances, and varying energy demands under the EVs penetration. This paper firstly defines the typical Remote Areas where the grid density is low with poor cable properties, but the future power demand is growing fast. Besides, their distributed energy is abundant and can contribute to generating electricity for the EVs, including solar energy, wind energy or marine energy. Renewable energy can maximize the reduction of carbon footprint and consumption. Then the Trincomalee city is selected as the simulation object. Perform national grids simulation optimization and solar power generation management as demand side optimization. Power grid model simulation: use government data to predict that Trincomalee's electricity demand will increase from the current 40–640 MW in five years and build a grid simulation model for Sri Lanka's national high-voltage transmission lines. Optimization will target transmission cables that provide higher voltage loads while considering cable properties includes resistance and reactance for optimal power loss and voltage drop respectively, thermal capacity, and power quality. The results show that though a lower resistance and reactance can reduce the power loss and voltage drop during transmission, the relationship does not follow a linear relationship when integrating into the whole power system. The range of resistance and reactance scenarios is set with equal intervals. The optimal point with the higher drop scenario always exists. The demand side management aims to solve the Trincomalee’s intermittency and overproduction issue to keep the supply and demand in dynamic balance. Solar energy production is surveyed for its intrinsic intermittency between day and night time. Based on the climatic conditions and NCRE data in the Trincomalee in 2013, the PV generation system is simulated by MATLAB and Excel and conclude the curves of solar irradiance, temperature and demand. the optimum rated capacity of the battery is then concluded from the demand and solar curve. The case studies from Sri Land highlight successful examples of distributed grid management in remote and rural areas. The methods contribute to the broader conversation around sustainable transportation and energy systems, and to provide guidance for policymakers and industry stakeholders working towards sustainable and equitable EV adoption.