RENEWCONNECT - All about renewables & power sector

Utility‑scale battery capex clusters around $125/kWh all‑in (global auctions as of Oct’25), translating to LCOS ≈ $65/MWh for 4‑hour systems; standalone LCOS ranges in the US are still triple digits in many cases, although sharply down in 2025. Pack costs average $108/kWh (global) and $70/kWh for stationary storage in China‑linked segments. Long‑duration chemistries (iron‑air) target ~$20/kWh for energy capacity; sodium‑ion could plausibly reach $40/kWh at cell level with scale. Pumped storage is scaling rapidly in India. All of that sets the baseline before we explore a $10/kWh world. If fully installed energy storage (not just cell cost) fell below $10/kWh , the cost of shifting electricity would become negligible relative to generation. Solar and wind could be overbuilt and time‑shifted ubiquitously; thermal peakers and new gas CCGTs would be replaced by solar+storage, wind+storage, and hybrid portfolios; transmission expansion would focus on strategic corridors , while d...

Solar Street Lighting Systems (SSLs) have moved from pilot deployments in rural India to mainstream public infrastructure. India’s Ministry of New & Renewable Energy (MNRE) has codified technical standards—favoring high‑efficacy white LEDs , LiFePO₄ batteries, dusk‑to‑dawn automation—and layered financing via Central Financial Assistance (CFA) and targeted schemes like PM JANMAN for PVTG habitations. State nodal agencies (e.g., ANERT in Kerala, HAREDA in Haryana, PEDA in Punjab) translate MNRE guidance into actionable tenders and rate contracts. Globally, the EU/IEC framework and US UL/ANSI standards converge on high safety and performance baselines, while market momentum—smart controls, lithium batteries, integral PV—drives costs down and reliability up. [mnre.gov.in] , [anert.gov.in] , [anert.gov.in] , [hareda.gov.in] India’s next leap will hinge on decentralized and hybrid models, lifecycle‑driven procurement, and robust field data. This article synthesizes current polic...

Imagine an electricity system where every impending asset failure is known in advance with perfect precision —time, location, cause, and cascading effects—across transmission, distribution, generation, and behind‑the‑meter devices. In such a world, outages from equipment defects disappear, capital plans re‑optimize around true residual life , spares and crews arrive “just in time,” and regulators recalibrate reliability incentives from SAIDI/SAIFI to assurance of supply under probabilistic risk that excludes random equipment faults. The International Energy Agency (IEA) already frames digitalization as essential to grid reliability and cost control; with perfect prediction, the gains would multiply—reducing outage minutes, deferring capex, and accelerating the clean‑energy transition by unlocking grid headroom without overbuilding . [iea.org] , [iea.org] Evidence from real utilities shows that even non‑perfect predictive analytics deliver 10–20% OPEX savings and 40–60% capex optim...