Abstract
The objective of this study is to investigate the expenditure of different kinds of energy storage systems (ESSs) for the economical dispatching of solar power at one-hour increments for an entire day for megawatt-scale grid-connected photovoltaic (PV) arrays. Accurate forecasting of PV power is vital for generation scheduling and cost-effective operation. A multilayer perceptron Artificial Neural Network (ANN) is utilized to predict PV irradiance one hour ahead of time, which performs well with good convergence mapping between input and target output data. Moreover, this research proposes a state of charge (SOC) control algorithm based on an adaptive neuro-fuzzy inference system (ANFIS) that can accurately estimate the grid reference power for each one-hour dispatching period, which is necessary for ensuring the ESS completes each dispatching period with its starting SOC and has sufficient capacity for next-day operation. Finally, an economic comparison is presented utilizing the Hybrid Optimization of Multiple Energy Resources (HOMER Pro) software to develop a cost-effective ESS for an hourly PV power dispatching scenario.
Original language | English |
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Title of host publication | 2022 IEEE Energy Conversion Congress and Exposition, ECCE 2022 |
ISBN (Electronic) | 9781728193878 |
DOIs | |
State | Published - 2022 |
Event | 2022 IEEE Energy Conversion Congress and Exposition, ECCE 2022 - Detroit, United States Duration: Oct 9 2022 → Oct 13 2022 |
Publication series
Name | 2022 IEEE Energy Conversion Congress and Exposition, ECCE 2022 |
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Conference
Conference | 2022 IEEE Energy Conversion Congress and Exposition, ECCE 2022 |
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Country/Territory | United States |
City | Detroit |
Period | 10/9/22 → 10/13/22 |
Bibliographical note
Publisher Copyright:© 2022 IEEE.
Keywords
- HOMER Pro
- Solar PV power
- cost analysis
- energy storage system
- power dispatch
- solar power forecasting
- state of charge (SOC) controller
ASJC Scopus subject areas
- Electrical and Electronic Engineering
- Mechanical Engineering
- Safety, Risk, Reliability and Quality
- Energy Engineering and Power Technology
- Renewable Energy, Sustainability and the Environment
- Control and Optimization