Sai Teja Nakka

Coordinated cross-functional teams across engineering, execution, and quality functions, using milestone tracking and structured communication protocols, resulting in on-time delivery across all project phases. Conducted energy efficiency programme evaluations and scenario analysis for investment decisions, using techno-economic analysis aligned with CSRD frameworks, resulting in data-driven sustainability reporting ready for senior stakeholder review.

Conducted feasibility assessments for 150+ urban residential solar PV and BESS projects, using early-stage site analysis under German EEG and grid connection guidelines, resulting in investment-ready project recommendations across a large residential portfolio. Built reproducible energy system models for utility-scale and residential projects, using Python (OEMOF-SOLPH, pvlib) and PV*SOL with BDEW load profiles and regional weather data, resulting in 30% improvement in yield accuracy

Led a multidisciplinary team of 10+ through a campus-wide renewable energy feasibility study, managing all phases from data acquisition through stakeholder reporting, resulting in a validated concept identifying up to 40% reduction in fossil energy demand. Delivered an integrated PV and storage design concept for 8+ buildings and solar car parking structures, using LCA-based sustainability assessments and CO₂ reduction modelling, resulting in infrastructure recommendations with over €2M CAPEX relevance.

Led full project lifecycle development of Battery Manufacturing, utility-scale ground-mounted / rooftop solar PV projects, managing permitting coordination, site evaluation, consultant supervision, grid connection studies, and commissioning, resulting in a fully operational asset delivered within budget and regulatory compliance. Delivered a 50 MWp utility-scale groundmounted industrial solar PV project end-to-end, using structured planning approvals, SLD design, and EPC coordination.

Techno-economic and environmental evaluation of residential Solar PV and BESS systems using Python (OEMOF-SOLPH, pvlib) and PV*SOL. Modelled self-consumption, grid export, and LCOE scenarios across multiple building typologies to identify optimal system configurations for decentralised energy supply. Relevant modules: Energy System Modelling · Grid Integration · Techno-Economic Evaluation · Sustainable Building Energy · Renewable Energy Policy (EEG/EED)