Least cost combination of renewable generators, storage devices and transmission system in the NEM

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Abstract

There are differing views on how to achieve a high penetration renewable power system in the Australian National Electricity Market (NEM). The limited hydro resource in Australia makes it more challenging to achieve a 100% renewable power system than other hydro resource-rich countries, as pumped-hydro plants could act as peaking power plants and provide relatively cheap energy storage. Given the variability and diverse location of wind and solar resources, augmentation of the transmission network and placement of energy storage devices may be key considerations under a high penetration renewable power system. The model in this paper estimates the least cost combination of renewable technologies, storage devices and transmission infrastructure to meet the projected demand in the NEM in the year 2030. The simulation uses historical data of NEM demand, regional interconnector capacity limits, weather data for wind and solar resources, and monthly hydro plant generation data as a benchmark. Genetic Algorithm (GA) is used as the optimization algorithm to seek the least cost combination of renewable generators, storage devices (existing pumped hydro and new grid-scale batteries) and transmission network upgrades to meet the electricity demand for all NEM regions at hourly temporal resolution. The results in this paper suggest that the electricity cost of a 100% renewable power system in the NEM would be ranged from $100/MWh to $163/MWh. Significant flows of power between regions may occur frequently and this will require significant investment in the transmission system. Deployment of battery storage devices along with investment in transmission infrastructure greatly increases the utilization of wind farms and solar power systems.

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APA

Wu, Y., & Reedman, L. (2015). Least cost combination of renewable generators, storage devices and transmission system in the NEM. In Proceedings - 21st International Congress on Modelling and Simulation, MODSIM 2015 (pp. 1133–1139). Modelling and Simulation Society of Australia and New Zealand Inc. (MSSANZ). https://doi.org/10.36334/modsim.2015.m1.wu

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