Integrating Photovoltaics and Battery Energy Storage Systems under Corporate Power Purchase Agreements and Market Exposure

The integration of photovoltaic with Battery Energy Storage Systems under corporate Power Purchase Agreements presents opportunities for renewable energy producers to enhance their financial and operational performance. This paper investigates the economic viability and strategic benefits of such integration, emphasizing the importance of optimal Battery Energy Storage Systems sizing and advanced market participation strategies. By employing probabilistic Bayesian Long Short-Term Memory network for long-term photovoltaic power output forecasting, we enable the Renewable Energy Producer to manage risk and secure stable power supply contracts. Our analysis demonstrates that maximum profitability is achieved with a safety level of z = 2 and battery duration of two hours, with annual profit of 1.08 million euros in non-congested market conditions. In congested markets, the strategy proves resilient, maintaining substantial profitability. The study underscores the critical role of accurate forecasting, robust market analysis, and strategic decision-making in optimizing the financial outcomes of co-located installations.

Authors

Institutions

Publication Details

Published
2024-10-21
DOI
https://doi.org/10.1109/synergymed62435.2024.10799322
Citations
2
Primary Topic
Electric Vehicles and Infrastructure
Type
article
Field-Weighted Citation Impact
0.42
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Integrating Photovoltaics and Battery Energy Storage Systems under Corporate Power Purchase Agreements and Market Exposure

Georgios Gousis, Georgios C. Christoforidis, Konstantinos O. Oureilidis, Nikolaos E. Koltsaklis
2 citations
Electric Vehicles and Infrastructure
0.42
article

Integrating Photovoltaics and Battery Energy Storage Systems under Corporate Power Purchase Agreements and Market Exposure

Georgios Gousis, Georgios C. Christoforidis, Konstantinos O. Oureilidis, Nikolaos E. Koltsaklis
article en
2 citations

Abstract

The integration of photovoltaic with Battery Energy Storage Systems under corporate Power Purchase Agreements presents opportunities for renewable energy producers to enhance their financial and operational performance. This paper investigates the economic viability and strategic benefits of such integration, emphasizing the importance of optimal Battery Energy Storage Systems sizing and advanced market participation strategies. By employing probabilistic Bayesian Long Short-Term Memory network for long-term photovoltaic power output forecasting, we enable the Renewable Energy Producer to manage risk and secure stable power supply contracts. Our analysis demonstrates that maximum profitability is achieved with a safety level of z = 2 and battery duration of two hours, with annual profit of 1.08 million euros in non-congested market conditions. In congested markets, the strategy proves resilient, maintaining substantial profitability. The study underscores the critical role of accurate forecasting, robust market analysis, and strategic decision-making in optimizing the financial outcomes of co-located installations.

Sabancı Üniversitesi (TR), University of Western Macedonia (GR)
Affordable and clean energy
Openalex Percentile: Top 36%
Electric Vehicles and Infrastructure
0.42
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Integrating Photovoltaics and Battery Energy Storage Systems under Corporate Power Purchase Agreements and Market Exposure — Georgios Gousis, Georgios C. Christoforidis, et al. · (2024) | TGRS Research Map | TGRS