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Optimal Stochastic Planning of a Green Hydrogen Production System via LP and Scenarios Reduction

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Author(s):
Terada, Lucas Zenichi ; Cortez, Juan Carlos ; Santos, Luiza Higino S. ; Silva, Jessica Alice A. ; Gomes, Francisca Dulcindia C. ; Lopez, Juan Camilo ; Rider, Marcos J.
Total Authors: 7
Document type: Journal article
Source: 2024 IEEE POWER & ENERGY SOCIETY GENERAL MEETING, PESGM 2024; v. N/A, p. 5-pg., 2024-01-01.
Abstract

An electrolyzer produces green hydrogen (H-2) using water and electricity from the main grid and local renewable energy sources (RESs). Hence, this study presents a stochastic linear programming (LP) model to efficiently sizing of distributed energy resources (DERs) for green producing and selling H-2. The proposed methodology involves a two-stage scenario reduction process, which manages computational complexities in handling numerous scenarios. The objective function aims to minimize the total average capital expenditure (CAPEX) and operating expenses (OPEX) for the project lifetime. A comprehensive test case incorporating wind, photovoltaic (PV), and battery energy storage system (BESS) is utilized to evaluate the efficacy of the model. The outcomes revealed that, for realistic investment costs and production prices, the BESS is not installed due to its high CAPEX and OPEX. (AU)

FAPESP's process: 20/13002-5 - Smart Recharge Algorithm for Electric Vehicles Considering the Integration of Distributed Electrical Resources: Microservice for IoT Electromobility Platforms
Grantee:Lucas Zenichi Terada
Support Opportunities: Scholarships in Brazil - Master
FAPESP's process: 22/09171-1 - Design of a predictive model for electric vehicle smart charging based on cloud data
Grantee:Lucas Zenichi Terada
Support Opportunities: Scholarships abroad - Research Internship - Master's degree
FAPESP's process: 21/11380-5 - CPTEn - São Paulo Center for the Study of Energy Transition
Grantee:Luiz Carlos Pereira da Silva
Support Opportunities: Research Grants - Science Centers for Development