msotocalvo/evrex: EVreX v0.1.0

EVreX v0.1.0 — Initial Release A Python library for electric vehicle fleet electrification assessment, adoption modeling, V2G potential analysis, battery degradation modeling, and grid impact assessment. Features Adoption Models Logistic regression with transport-specific drivers (GDP, fuel price, infrastructure) Bass diffusion (innovation/imitation dynamics) TCO-parity (total cost of ownership EV vs ICE comparison) Policy-driven (ICE bans, emission targets, scrappage model) Charging Demand 3 scenarios: uncontrolled, time-of-use shifted, optimized (valley filling) Empirical 24h profiles for 4 vehicle categories (light, medium, heavy, buses) V2G & Battery Degradation Hourly V2G capacity and energy availability assessment Wöhler-type degradation model with NMC and LFP chemistry parameters Break-even compensation rate calculation ($/MWh) Grid Impact Peak shaving and valley filling quantification Arbitrage revenue and avoided grid reinforcement economics Net V2G program value assessment Bundled Data IEA Global EV Data Explorer: 20 countries, 2010–2024 BNEF battery pack costs: 2013–2024 + projections to 2050 Data Fetchers (optional [fetch] extra) OpenStreetMap: charging stations and road density World Bank: GDP, urbanization, population IMF: GDP growth, inflation Installation pip install evrex pip install evrex[fetch] # with OSM/WB/IMF fetchers Requirements Python ≥ 3.9 numpy ≥ 1.22 scipy ≥ 1.8