Short answer

When designing standalone offshore DC microgrids, leverage advanced optimisation techniques to select and configure hybrid energy storage systems, focusing on battery-supercapacitor combinations for the lowest levelised cost of electricity.

Field
Commercial Production
Source
Journal of Energy Storage (2025)
Method
Simulation and optimisation
Evidence
Strong effect

A hybrid battery-supercapacitor energy storage system, optimised using an enhanced Particle Swarm Optimisation algorithm, significantly reduces the levelised cost of electricity in standalone offshore DC microgrids. This commercial production research insight is drawn from a 2025 study published in Journal of Energy Storage. Using Simulation and optimisation, researchers explored how this design variable affects real-world outcomes. The key design takeaway: When designing standalone offshore DC microgrids, leverage advanced optimisation techniques to select and configure hybrid energy storage systems, focusing on battery-supercapacitor combinations for the lowest levelised cost of electricity.

Study
Commercial ProductionNew This WeekStrong effect

Optimised Hybrid Energy Storage Slashes LCOE by 19.63 US Cents/kWh in Offshore Microgrids

A hybrid battery-supercapacitor energy storage system, optimised using an enhanced Particle Swarm Optimisation algorithm, significantly reduces the levelised cost of electricity in standalone offshore DC microgrids.

Journal of Energy Storage · 2025

01

Key Findings

  • 01A battery-supercapacitor hybrid energy storage system achieved the lowest levelised cost of electricity (LCOE) at 19.63 US Cents/kWh.
  • 02The enhanced PSO algorithm demonstrated superior performance over standard PSO, Genetic Algorithm, and Ant Colony Optimisation.
  • 03Wave energy integration was found to be financially unviable for current offshore microgrid applications.
  • 04The proposed ESS degradation algorithm is more accurate and computationally efficient than the Rainflow counting method.
02

Application

Design takeaway

When designing standalone offshore DC microgrids, leverage advanced optimisation techniques to select and configure hybrid energy storage systems, focusing on battery-supercapacitor combinations for the lowest levelised cost of electricity.

How to apply

When designing or evaluating energy systems for remote or offshore applications relying on intermittent renewables, simulate and optimise hybrid storage solutions using advanced algorithms to identify the most economically viable and resilient configurations.

Project actions

  • 01Consider using optimisation algorithms to find the best combination of components for your design.
  • 02When evaluating renewable energy sources, perform thorough cost-benefit analyses specific to your project's context.
03

Method & Evidence

AimTo determine the most cost-effective and reliable energy storage configuration for standalone DC microgrids in offshore industries, considering renewable energy intermittency and operational resilience.
MethodSimulation and optimisation
ProcedureAn enhanced Particle Swarm Optimisation (PSO) algorithm, incorporating quadratic interpolation and extended local search, was used to compare various energy storage system (ESS) configurations (including battery-supercapacitor hybrid systems) for a standalone DC microgrid powered by solar PV, wind, and wave energy. A probabilistic model was developed to validate resilience, and an ESS degradation algorithm was introduced and compared to the Rainflow counting method. The levelised cost of electricity (LCOE) was calculated for each configuration.
ContextOffshore maritime operations and renewable energy integration

Variables

IV["Energy storage configuration (e.g., battery-supercapacitor hybrid, battery only, supercapacitor only)","Optimisation algorithm (e.g., enhanced PSO, standard PSO, GA, ACO)","Inclusion of different renewable energy sources (PV, wind, wave)"]
DV["Levelised Cost of Electricity (LCOE)","Microgrid reliability/resilience","ESS degradation rate","Computational efficiency of optimisation and degradation algorithms"]
CV["Offshore microgrid architecture (standalone DC)","Renewable energy intermittency profiles (weather conditions)","Operational lifespan of components","Cost of energy generation and storage components"]
04

Strengths & Limitations

Strengths

  • +Utilisation of an advanced, enhanced optimisation algorithm.
  • +Inclusion of probabilistic modelling for resilience validation.
  • +Comparison of multiple energy storage configurations and optimisation methods.

Limitations

The computational resources required for advanced optimisation can be significant. Real-world offshore conditions may introduce variables not fully captured in simulations.

Reliability & validity

The study's validity is supported by the use of established metrics like LCOE and probabilistic modelling. Reliability is enhanced by comparing multiple optimisation algorithms and introducing a novel degradation algorithm.

Think critically

How might the 'current market dynamics' rendering wave energy unviable change in the future, and what technological or economic shifts would be necessary to alter this conclusion?

05

Design Principles

"Optimise hybrid energy storage configurations using advanced algorithms to minimise the levelised cost of electricity in renewable-dependent microgrids."

This research offers a data-driven approach to selecting and optimising energy storage solutions for complex, renewable-dependent power systems. By quantifying cost-effectiveness and resilience, it provides a framework for making informed investment decisions in sustainable offshore energy infrastructure.

06

What This Means for Your Design

This research shows that using a mix of batteries and supercapacitors, fine-tuned by a smart computer program, is the cheapest way to power offshore operations with renewable energy, and it's better than older methods.

How to use in your project

  • 1.Reference this study when justifying the selection of specific energy storage technologies or optimisation methods in your design project.
  • 2.Use the LCOE metric as a benchmark for evaluating the economic feasibility of your proposed energy solutions.
07

Add to My Project

08

Quick Cite

Paragraph starter

This research highlights the critical role of optimised hybrid energy storage systems in achieving economic viability for standalone offshore DC microgrids. The study's findings, demonstrating that a battery-supercapacitor configuration yields the lowest levelised cost of electricity (19.63 US Cents/kWh) when optimised via an enhanced Particle Swarm Optimisation algorithm, provide a strong precedent for selecting energy solutions in similar design projects. Furthermore, the comparative analysis of optimisation methods underscores the importance of employing sophisticated techniques to ensure cost-effectiveness and system reliability.

09

Source

Journal of Energy Storage

Enhanced PSO-based optimisation with probabilistic analysis for standalone DC microgrid design

journal · 2025

View source

Questions About This Research

What does the research say about optimised hybrid energy storage slashes lcoe by 19.63 us cents/kwh in offshore microgrids?
When designing standalone offshore DC microgrids, leverage advanced optimisation techniques to select and configure hybrid energy storage systems, focusing on battery-supercapacitor combinations for the lowest levelised cost of electricity. Evidence: Journal of Energy Storage (2025).
Why does "Optimised Hybrid Energy Storage Slashes LCOE by 19.63 US Cents/kWh in Offshore Microgrids" matter for design?
This research offers a data-driven approach to selecting and optimising energy storage solutions for complex, renewable-dependent power systems. By quantifying cost-effectiveness and resilience, it provides a framework for making informed investment decisions in sustainable offshore energy infrastructure.
How can designers apply this research?
When designing standalone offshore DC microgrids, leverage advanced optimisation techniques to select and configure hybrid energy storage systems, focusing on battery-supercapacitor combinations for the lowest levelised cost of electricity.
What were the main findings?
A battery-supercapacitor hybrid energy storage system achieved the lowest levelised cost of electricity (LCOE) at 19.63 US Cents/kWh.. The enhanced PSO algorithm demonstrated superior performance over standard PSO, Genetic Algorithm, and Ant Colony Optimisation.. Wave energy integration was found to be financially unviable for current offshore microgrid applications.. The proposed ESS degradation algorithm is more accurate and computationally efficient than the Rainflow counting method.
What research method was used?
Simulation and optimisation.
How strong is the evidence?
Evidence strength is rated Strong effect, based on a 2025 journal from Journal of Energy Storage.
What should I do differently in my next project?
When designing or evaluating energy systems for remote or offshore applications relying on intermittent renewables, simulate and optimise hybrid storage solutions using advanced algorithms to identify the most economically viable and resilient configurations.
What are the limitations?
The study's findings on wave energy viability are specific to current market dynamics and may change with technological advancements or shifts in economic conditions. The performance of the ESS degradation algorithm was primarily evaluated against partial charge-discharge cycles.