Dynamic Cost-Optimal Assessment of Complementary Diurnal Electricity Storage Capacity in High PV Penetration Grid

Samuel Matthew G Dumlao,Keiichi N Ishihara

doi:10.3390/en14154496

Abstract

Solar Photovoltaics (PV) is seen as one of the renewable energy technologies that could help reduce the world’s dependence on fossil fuels. However, since it is dependent on the sun, it can only generate electricity in the daytime, and this restriction is exacerbated in electricity grids with high PV penetration, where solar energy must be curtailed due to the mismatch between supply and demand. This study conducts a techno-economic analysis to present the cost-optimal storage growth trajectory that could support the dynamic integration of solar PV within a planning horizon. A methodology for cost-optimal assessment that incorporates hourly simulation, Monte Carlo random sampling, and a proposed financial assessment is presented. This approach was tested in Japan’s southernmost region since it is continuously increasing its solar capacity and is at the precipice of high PV curtailment scenario. The results show the existence of a cost-optimal storage capacity growth trajectory that balances the cost penalty from curtailment and the additional investment cost from storage. This optimal trajectory reduces the impact of curtailment on the energy generation cost to manageable levels and utilizes more solar energy potential that further reduces CO2 emissions. The results also show that the solar capacity growth rate and storage cost significantly impact the optimal trajectory. The incorporation of the Monte Carlo method significantly reduced the computational requirement of the analysis enabling the exploration of several growth trajectories, and the proposed financial assessment enabled the time-bound optimization of these trajectories. The approach could be used to calculate the optimal growth trajectories in other nations or regions, provided that historical hourly temperature, irradiance, and demand data are available.

Highlights

By separating the optimization process into a two-step process, the first step ensured that the optimization is technically viable, while the second step identified the ESS growth trajectory with the lowest generation cost
The cost-optimal ESS growth trajectory has the lowest Levelized Cost of Generation (LCOG) within the planning horizon
The proposed LCOG calculation was able to incorporate the gradual growth of PV capacity and the changes in the cost, which enabled the optimization within the planning horizon

Summary

Introduction

In October 2016, the conditions for the entry into force of the Paris Agreement were met, and it entered into force on 4 November 2016. One of the United Nations Sustainable Development Goals, established in 2015, is focused on affordable and clean energy These two global initiatives helped promote renewable energy, such as wind, solar, and biomass, in the energy mix of several nations. Countries such as Germany and Denmark and subnational jurisdictions such as California, Scotland, and South Australia, developed and promoted their “green energy transition” initiatives [1]. Aside from these major players, more than 150 countries have national targets for renewable energy in the power sector [2]

Methods

Results

Discussion

Conclusion