Treffer: Smart Force Optimization (SFO) and its application for determining optimal component configurations for flexible biogas plants based using a modified exhaustive search method

Title:
Smart Force Optimization (SFO) and its application for determining optimal component configurations for flexible biogas plants based using a modified exhaustive search method
Contributors:
Dotzauer, Martin
Publisher Information:
Zenodo
Publication Year:
2024
Collection:
Zenodo
Document Type:
E-Ressource software
Language:
English
ISSN:
0960-1481
DOI:
10.5281/zenodo.13822865
Rights:
Creative Commons Attribution 4.0 International ; cc-by-4.0 ; https://creativecommons.org/licenses/by/4.0/legalcode
Accession Number:
edsbas.708D8EFE
Database:
BASE

Weitere Informationen

Smart Force Optimisation (SFO) This repository contain the SFO building blocks and an examplary applied relating to the paper "Determining optimal component configurations for flexible biogas plants based on power prices of 2020 – 2022 and the legislation framework in Germany" The paper was published in Renewable Energy and is open accessible.DOI: https://doi.org/10.1016/j.renene.2024.121252 Abstract of the paper The aim of this study is to find optimal component configurations for flexible biogas plants considering electricity prices in Germany, for maximum annuities considering costs and revenues. Cases for solely power-price driven operation and cogeneration-led operation were investigated for electricity prices in 2020, 2021, and 2022 in hourly resolution.Additional revenue from flexible operation increases as price volatility increased from 2020 to 2022. Interestingly, the choice of capacity for the combined heat and power unit (CHPU) is determined by the expected service life of the CHPU. Irrespective of electricity market signals, power quotients (PQ) of at least PQ = 4 avoid reinvestment for the CHPU within 20 years.Another result is that the optimality region for CHPU capacity flattens for 2022 and shift to capacities above PQ = 4. Thus, high price volatility will allow plant operators to amortise even larger CHPUs, which could stimulate the installation of peak load by flexible biogas plants. Considering the day-ahead market can provide clear recommendations for optimal component configurations. The presented Smart-Force-Optimisation (SFO) combines a prefiltering of schedules matching given constraints and a brute force optimisation to the filtered subset. Thus, SFO has an improved performance comparing to bare brute force approaches. Smart Force Optimization (SFO) SFO in a nutshell:The innovative aspect about the sfo approach is the combination of a data base for storing all possible schedules and their corresponding constraints in advance and the subsequently selection of those schedules which are in ...