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Sustainable AI distributed data centers with wind/solar power?
@mckartha @stan – how can we begin planning this?
Concept architecture: community-owned, renewable-first distributed data centers
Open Gannt Timeline PDF (contact us about adapting this for your community)
Below is a practical, modular design you can use for Community Internet–style deployments that prioritize wind/solar, cut grid draw, and keep value local.
1) Big-picture layout
┌───────────────────────────────────────────────┐ │ Regional Orchestrator │ │ (multi-cluster scheduler + carbon-aware API) │ └───────────────┬───────────────┬───────────────┘ │ │ ┌───────────────┘ └───────────────┐ ┌───────────────────┐ ┌───────────────────┐ │ Micro Data Hub A │ │ Micro Data Hub B │ │ (50–200 kW) │ │ (20–100 kW) │ │ • Solar + BESS │ │ • Wind + BESS │ │ • Microgrid Ctrl │ │ • Microgrid Ctrl │ │ • k8s cluster │ │ • k8s cluster │ └─────────┬─────────┘ └─────────┬─────────┘ │ │ │ │ ┌────────▼────────┐ ┌────────▼────────┐ │ Community Edge │ │ Community Edge │ │ (1–10 kW pods) │ │ (1–10 kW pods) │ │ Wi-Fi / FWA POP │ │ Wi-Fi / FWA POP │ └────────┬────────┘ └────────┬────────┘ │ │ ┌────────▼────────┐ ┌────────▼────────┐ │ End-user Apps │ │ End-user Apps │ │ LMS, portals, │ │ telco core, VOD │ │ telehealth, AI │ │ AI inference │ └─────────────────┘ └─────────────────┘Key idea: Run as much compute as possible where renewables are abundant right now; backfill from battery, then grid only as a last resort.
2) Core building blocks
Power & microgrid
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Generation: Rooftop/ground-mount PV, small/medium wind (where viable).
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Storage: LFP battery (BESS) sized for 2–4 hours at rated IT load; optional second-life packs to cut cost.
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DC bus: 380V DC to reduce conversion losses; high-efficiency rectifiers if AC needed.
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Cooling: Direct-to-chip liquid or rear-door heat exchangers; free-air economization where climate allows.
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Controller: OpenEMS (or similar) for state of charge (SoC), demand response, islanding, and OpenADR participation.
Compute & platform
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Clusters: k8s (upstream), or K3s for edge pods; use node power profiles and CPU pinning for efficiency.
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Schedulers: Carbon/price-aware placement with:
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KEDA (event-driven autoscaling),
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Volcano or OpenKruise for batch & preemption,
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Descheduler to drain workloads when renewable dips.
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Storage: Ceph or Longhorn across each micro-hub; S3-compatible object for data locality.
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Observability: Prometheus + Grafana; Kepler/eBPF for per-pod energy telemetry; Kubecost for $/kWh parity tracking.
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GitOps: FluxCD/ArgoCD for drift-free ops; sealed-secrets for credentials.
Networking
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Backbone: L2/L3 over existing fiber where possible; L3 overlay/WireGuard between hubs.
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Access: CBRS/FWA and community Wi-Fi; peering at IXPs if available.
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QoS: Slice critical apps (telehealth, education) via SR-v6 or DiffServ policies.
Data governance (co-op)
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Tenancy: Namespace-per-member with network policies.
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Sovereignty: Choose data residency per cluster; keep PII near origin hub.
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Audit: OPA/Gatekeeper policies; immutable logs in object store with lifecycle policies.
3) Energy-aware workload strategy
Workload classes
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Critical low-latency (telehealth consults, LMS live sessions): pin to local edge; always-on budget from BESS + grid failover.
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Elastic online (portals, chat, ticketing): run where renewable is available; autoscale down when SoC < X%.
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Deferrable/batch (backups, analytics, AI training): schedule to hubs with surplus PV/wind or cheap off-peak; pause on SoC threshold.
Placement algorithm (simple, effective)
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Rank hubs every 5 minutes by renewable fraction = (gen + discharge) / (IT load).
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Filter by latency/SLA and data residency.
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Place or migrate pods accordingly; preempt non-critical workloads if SoC < 25%.
4) Control loops (who talks to whom)
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Energy loop: OpenEMS → exposes SoC, forecast PV/wind, grid price; notifies orchestrator via Prometheus metrics or a small Carbon/SoC API.
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Scheduler loop: Orchestrator (custom controller) updates k8s node taints/labels (“green=high/med/low”), drives KEDA/HPA targets.
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DR loop: When grid sends OpenADR event, orchestrator scales down class-3 workloads and caps class-2 replicas; microgrid exports if safe.
5) Sizing a starter hub (illustrative)
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IT load: 60 kW nameplate; 35 kW typical.
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PV: 250 kWdc (roof + carport) → ~1.1–1.3 MWh/day (climate-dependent).
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Wind (optional site): 50–100 kW small turbines → 200–400 kWh/night in good wind regimes.
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BESS: 140 kWh / 70 kW (2-hour) to shave peaks + ride-through.
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PUE target: 1.10–1.20 with liquid cooling & economization.
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Outcome: On a sunny/windy day, >80% of compute energy off-grid; grid draw limited to mornings/evenings and foul weather.
6) Integration with a community microgrid
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Priority stack: (1) On-site renewables → (2) BESS discharge → (3) Import from grid (off-peak preferred).
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Export policy: When SoC > 80% and IT load < threshold, export to adjacent community buildings; monetize via tariff or behind-the-meter offset.
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Heat reuse: Hydronic loop to a nearby school/pool/greenhouse (5–20% of IT load captured as useful heat).
7) Security & resilience
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Zero-trust: Mutual TLS (SPIFFE/SPIRE), WireGuard site tunnels; short-lived certs.
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Backups: Immutable object snapshots to a different hub; quarterly restore drills.
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Failover: Anycast VIPs or DNS-based traffic steering; minimum N+1 hubs for critical apps.
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Incident response: Runbooks + ChatOps; automated node quarantine on power/cooling alarms.
8) Minimal Viable Pilot (90–120 days)
Sites (2–3 small hubs + 3–5 edges)
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Hub A (solar-heavy) at a school/civic center: 20–40 kW PV, 40–80 kWh BESS, 6–12 compute nodes (1U liquid-ready).
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Hub B (wind-helped) at a municipal site: 10–20 kW wind + 10–20 kW PV, 40–80 kWh BESS, 4–8 nodes.
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Edges at community Wi-Fi POPs: 1–2 kW micro-pods (K3s) hosting cached content and real-time apps.
Workloads
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Community Internet LMS/portals, messaging, ticketing.
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Batch: nightly analytics, backups, lightweight model fine-tuning.
Deliverables
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Carbon/SoC API + scheduler controller,
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Dashboards (renewable fraction per app; $/kWh avoided),
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Policy pack (OPA) + residency profiles.
9) KPIs to prove impact
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Renewable fraction of compute (% of IT kWh from on-site gen + BESS).
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Grid peak demand reduction (kW shaved vs. baseline).
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Cost per served user/session (with and without DR participation).
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Local value retained ($ spent on local energy/services vs. external).
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Latency SLA adherence for critical apps.
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PUE and water usage (target near-zero WUE).
10) Bill of materials (pilot scale, indicative)
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PV 30–40 kW + inverters; BESS 40–80 kWh LFP + PCS + EMS.
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Racks (liquid-ready) + CDU, rear-door HEX or direct-to-chip blocks.
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Compute nodes: 8–20 energy-efficient servers (AMD EPYC/Intel E-cores), 1–2 GPU nodes if needed (L40S/MI300 efficiency class).
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Networking: 25/100 GbE in-rack, 10 GbE edge, outdoor radios (CBRS/FWA).
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Controls: OpenEMS controller, smart meters, weather/irradiance sensors.
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Software: k8s + FluxCD, KEDA, Prometheus/Grafana, OPA, Ceph/Longhorn, WireGuard, SPIFFE.
11) Funding & governance (co-op lens)
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Capex via community bonds/green grants; repay from (a) avoided grid costs, (b) DR revenue, (c) platform subscriptions.
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Member tiers map to namespaces/quotas; democratic control over data residency and export policies.
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Open reporting: monthly energy + KPI dashboards to members.
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