Proceedings of the 5th World Conference on Climate Change and Global Warming
Year: 2025
DOI:
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Assessing the Impact of Forecast Accuracy and Battery Size on Cost and CO₂ Emissions in Distributed Energy Systems
Kiyofumi Sato, Yoshikuni Yoshida
ABSTRACT:
This study examines the impact of forecast accuracy and power source configurations on operational costs and CO₂ emissions in distributed energy systems. We utilize one-year datasets on electricity demand and solar photovoltaic (PV) generation from Tokyo, in addition to one-year market price data from the Japan Electric Power Exchange (JEPX), to generate 30-minute forecasts for the next day’s demand, PV output, and prices. Two distinct forecasting models are employed for a comprehensive comparison of performance. Based on these forecasts, we develop an optimal scheduling plan for battery storage and electricity procurement from the market, aiming to minimize purchasing costs as well as penalties resulting from imbalances between supply and demand. Our analysis reveals that improved forecast accuracy significantly contributes to cost reductions by enabling better decision-making. The integration of battery storage and PV generation has the potential to lead to considerable cost savings, although the extent of these savings is largely dependent on fluctuating market prices. Moreover, while battery storage plays a role in reducing CO₂ emissions, our findings indicate that even greater environmental benefits are realized through enhanced forecast accuracy and increased PV penetration. These results underscore the importance of adopting a balanced approach in designing and operating distributed energy systems—one that effectively combines cost-effective strategies with environmental sustainability. Our work provides practical insights for system designers and policymakers aiming to improve both the economic and environmental performance of regional energy networks.
keywords: battery sizing, cost optimization, CO₂ emissions, distributed energy systems, forecasting methods