Electricity Price-Driven Renewable Energy Station Value Evaluation Model: An Analysis of Economic Impact and Decision-Making Strategies

DOI

10.2991/978-94-6463-835-6_15How to use a DOI?

Keywords

Electricity Price Volatility; Renewable Energy Projects; Station Value Evaluation; SARMA; Monte Carlo Simulation; Machine Learning; Stochastic Variable Model; Risk Management; Investment Decision-making; Market Trading Mechanism

Abstract

This paper proposes a new energy station value evaluation and optimization model driven by electricity price, which aims to more accurately reflect the impact of electricity price fluctuations on the economic value of new energy projects. By comprehensively considering meteorological factors, economic development, power consumption, power rationing and operating costs, a random variable model based on time series analysis and machine learning method is constructed, and Monte Carlo simulation technology is used for cash flow prediction and pricing analysis. The empirical research results show that this model can effectively improve the accuracy and stability of new energy project valuation, reduce the cognitive gap between investors and developers in market transactions, and promote the scientific and transparency of investment decisions. This study provides a powerful tool support for financial investment decision-making in the field of new energy and proposes that the combination of market trading mechanism and dynamic optimization model can be further studied in the future to better adapt to the complex and volatile market environment.

Copyright

© 2025 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Download article (PDF)

TY  - CONF
AU  - Ru Bai
AU  - Siyuan Sang
AU  - Linyinan Li
AU  - Haibo Li
PY  - 2025
DA  - 2025/09/17
TI  - Electricity Price-Driven Renewable Energy Station Value Evaluation Model: An Analysis of Economic Impact and Decision-Making Strategies
BT  - Proceedings of the 2025 3rd International Academic Conference on Management Innovation and Economic Development (MIED 2025)
PB  - Atlantis Press
SP  - 126
EP  - 136
SN  - 2352-5428
UR  - https://doi.org/10.2991/978-94-6463-835-6_15
DO  - 10.2991/978-94-6463-835-6_15
ID  - Bai2025
ER  -