Gridcog Modeller

The Recruitment Crowd (Yorkshire) Limited; Stoke-on-Trent; On-site; GBP 40,000 - 60,000; Full time

Job summary

A leading renewable energy consultancy in the United Kingdom is seeking a highly analytical Gridcog Modeller to enhance their commercial solar engineering team. The role focuses on using Gridcog and other tools for modelling and optimising energy systems, with responsibilities including scenario simulation, data analysis, and collaboration with engineering and commercial teams. Ideal candidates have experience in energy modelling and hold a degree in relevant fields, ensuring impactful contributions to renewable energy projects.

Qualifications

• Proven experience in energy system modelling, grid analysis, or simulation within renewables, utilities, or engineering sectors.
• Hands-on experience with Gridcog or similar modelling platforms.
• Ability to interpret and manipulate complex datasets, including time-series energy data.

Responsibilities

• Build, refine, and optimise Gridcog models for energy systems.
• Analyse site-specific and grid-related datasets.
• Conduct scenario simulations to evaluate energy generation and performance.
• Collaborate with teams to integrate modelling outputs.

Skills

Energy system modelling

Grid analysis

Strong analytical skills

Attention to detail

Team collaboration

Education

Degree in engineering, renewable energy, data science

Tools

Gridcog

PVSyst

HOMER

MATLAB

Python-based modelling tools

Job description

Job Description

Our client are seeking a highly analytical and innovative Gridcog Modeller to join their commercial solar engineering and design team. In this role, you will use Gridcog and other modelling tools to simulate, analyse, and optimise commercial solar, battery storage, and energy system performance. Your work will play a critical part in evaluating grid constraints, forecasting system behaviour, and supporting feasibility studies to guide strategic project decisions.

This is an exciting opportunity for an individual passionate about renewable energy modelling, system optimisation, and data-driven design. You will work closely with technical, development, and commercial teams to produce accurate, reliable, and actionable modelling insights that directly influence project development and client proposals.

Responsibilities

• Build, refine, and optimise Gridcog models for commercial solar PV, battery storage, EV charging, and hybrid energy systems.
• Analyse site-specific and grid-related datasets including load profiles, export constraints, and DNO information to inform modelling assumptions.
• Conduct scenario simulations to evaluate energy generation, storage behaviour, grid export limits, financial outcomes, and system performance.
• Work collaboratively with engineering, design, commercial, and development teams to integrate modelling outputs into proposals, feasibility studies, and client presentations.
• Validate modelling results, ensuring accuracy, real-world relevance, and compliance with industry practices and grid regulations.
• Maintain clear and detailed documentation for modelling methodologies, parameters, and results.
• Continuously improve modelling workflows based on new Gridcog features, industry standards, system technology updates, and regulatory changes.
• Present modelling findings in a clear and accessible way to both technical and non-technical stakeholders, including clients.

Qualifications & Experience

• Proven experience in energy system modelling, grid analysis, or simulation within renewables, utilities, or engineering sectors.
• Hands-on experience with Gridcog or similar modelling platforms (e.g., PVSyst, HOMER, MATLAB, Python-based modelling tools).
• Strong analytical skills with the ability to interpret and manipulate complex datasets, including time-series energy data.
• Strong organisational skills and meticulous attention to detail.
• Ability to work independently and collaboratively across multidisciplinary teams.
• A degree in engineering, renewable energy, data science, or a related field is preferred.
• Desirable experience includes:
  • optimisation algorithms and system performance modelling
  • commercial solar or battery storage project experience
  • familiarity with IEC/IEEE energy standards and UK grid connection processes
  • understanding of DNO/DSO grid requirements and constraints