Optimal Microgrid Sizing of Offshore Renewable Energy Sources for Offshore Platforms and Coastal Communities

TL;DR

This paper presents REMO, a tool for optimizing offshore microgrid sizes by integrating renewable sources and battery degradation modeling, aiming to minimize costs and enhance reliability for offshore communities.

Contribution

Introduction of REMO, a novel optimizer that incorporates a deep neural network for battery degradation to improve offshore microgrid design accuracy.

Findings

REMO effectively minimizes lifetime energy costs.

The DNN-BD module accurately models battery degradation.

Simulations show high reliability and sustainability in offshore microgrids.

Abstract

The global energy landscape is undergoing a transformative shift towards renewable energy and advanced storage solutions, driven by the urgent need for sustainable and resilient power systems. Isolated offshore communities, such as islands and offshore platforms, which traditionally rely on mainland grids or diesel generators, stand to gain significantly from renewable energy integration. Promising offshore renewable technologies include wind turbines, wave and tidal energy converters, and floating photovoltaic systems, paired with a storage solution like battery energy storage systems. This paper introduces a renewable energy microgrid optimizer (REMO), a tool designed to identify the optimal sizes of renewable generation and storage resources for offshore microgrids. A key challenge in such models is accurately accounting for battery degradation costs. To address this, the REMO model integrates a deep neural network-based battery degradation (DNN-BD) module, which factors in variables like ambient temperature, charge/discharge rates, state of charge, depth of discharge and battery health. Simulations on six test regions demonstrate that the REMO-DNN-BD approach minimizes lifetime energy costs while maintaining high reliability and sustainability, making it a viable design solution for offshore microgrid systems.