Yaml

Why PV Self-Consumption Matters Right Now

A 7.4 kW wall box pulling a flat 32A through a sunny afternoon is the worst load profile for a house with rooftop solar. It ignores what the panels do. It drags power from the grid during the cheapest hours of the day. It forces the inverter to dump the surplus at whatever feed-in rate your utility feels like paying that month. Since the post-2023 collapse of feed-in tariffs across Europe, that rate is painful. Export rates in Germany, the Netherlands, and the UK now sit around 6-8 cents per kWh. Retail import hovers between 28 and 35 cents. Every exported watt is a 20-cent loss. Every imported watt while the sun is up costs the same.

Dagger lets you write CI/CD pipelines in Go, Python, or TypeScript instead of YAML. Your pipelines run inside containers, execute identically on your laptop and in CI, and get type-checked by your compiler or linter before they ever touch a remote runner. If you’ve spent hours pushing commits just to debug a GitHub Actions workflow, Dagger is the fix.

The core idea: pipeline steps are function calls in a real programming language. Each function call builds a directed acyclic graph (DAG) of container operations. The Dagger Engine (built on BuildKit ) executes this graph with automatic parallelization and layer caching. You run dagger call ci --source . locally, get the same result in GitHub Actions, GitLab CI, or CircleCI, and never write vendor-specific YAML again.

Home Assistant pulls hourly spot prices through the Tibber integration or the Nordpool HACS add-on. It then schedules EV chargers, water heaters, heat pumps, and dishwashers during the cheapest hours. On a 2026 Nordic tariff with 3-8x daily price swings, shifting 10-15 kWh of flexible load each day cuts the bill by 20-40% with no comfort cost.

Why Dynamic Pricing Pays Off in 2026

The Nordpool day-ahead auction closes around noon CET. By 13:00, prices for all 24 hours of the next day are out for every bidding zone. That window is exactly what Home Assistant needs: a once-a-day drop of 24 hourly prices that your automations can plan against overnight.

AppDaemon 4.5.14 is a Python runtime that runs next to Home Assistant . It lets you write rules as full Python classes. You get state machines, scheduling, outside API calls, and logic that YAML can’t handle. Install it as a Home Assistant add-on, drop a Python file in the apps folder, define a class that inherits from hass.Hass, and use callbacks like listen_state() and run_daily() to drive multi-step flows, saved values, and live data.

Home Assistant Blueprints are reusable automation templates. They split the logic from the per-device bits. You define a pattern once, say a motion light with a timeout, then spin it up for every room by filling in a form. No YAML to copy. No ten near-twin automations to babysit. In Home Assistant 2026.4, blueprints span three domains: automation, script, and template. They ship dozens of selector types for clean input forms and tidy collapsible sections for bigger setups. They’re the fastest way to keep smart home behavior the same across many devices.

Yes, Home Assistant ships a built-in conditional card. It shows or hides any dashboard card based on live state: entity value, time of day, who is home, screen size, and more. Add template sensors and a few HACS cards, and you can build dashboards where morning shows weather and coffee buttons, evening shows media and light scenes, and an empty house shows cameras and alarm controls. Cards pop in and out without leaving blank gaps, all through the stock Lovelace frontend. No custom code needed.