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ENERGY STRATEGY / DEVELOPMENT USE CASE

The cheapest source right now may be the wrong dispatch.

Design campus energy control around tenant obligations, future peaks and reserve requirements before automating source selection.

The Texas context

Distributed-energy planning tools can optimize asset size and dispatch, while ERCOT has distinct demand-response participation routes. Neither replaces a site operating agreement or a qualified control system. The actual tariff, interconnection permissions and tenant service commitments determine what a Texas campus controller may do.

NLR: REopt campus energy-system optimization

Our view

A controller that always selects the cheapest immediate source can empty emergency storage, create tomorrow’s demand peak or consume fuel needed for a prolonged outage. The correct objective is cost within service constraints, not cost instead of service. Automation should execute an approved hierarchy of obligations.

Dispatch hierarchy to agree before commissioning

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PriorityConstraintEvidence
1. Safe operationProtection, permitted topology and equipment limitsQualified design and accepted controls
2. Contracted continuityTenant load, cooling and protected reserveOperator-approved service envelope
3. Firm external obligationQualified response or export commitmentsCompatible dispatch and settlement contracts
4. Economic optimizationAvoided cost net of losses and wearBack-tested tariff and price model

The owner’s situation

The campus battery is nearly full at noon. A price forecast suggests discharging now is profitable. A protected tenant needs a fixed reserve, afternoon cooling demand may set the month’s charge, and a second tenant has bought demand-response flexibility. The owner has three claims on one asset. A software procurement will not resolve which promise has priority.

What we need to establish

Establish the billing interval, price exposure, export limit, battery state-of-charge limits, degradation warranty, generator duty and fuel inventory. Record tenant service envelopes and market commitments. Identify communications latency, forecast errors, manual overrides, cybersecurity ownership and the mode to use if telemetry fails. The control authority must match the physical meter and contracts, including which parties can change setpoints.

The options we would test

Conservative rule-based dispatch

Use a transparent import limit and protected reserve for initial operations.

Before committing Test edge cases; simple rules still need technical approval.

Forecast-based optimization

Schedule assets over a defined forward horizon with operating constraints.

Before committing Measure forecast error and show a safe fallback before enabling autonomous changes.

Delegated asset operation

Let a specialist operator optimize an asset within campus limits.

Before committing Resolve conflicts between asset-owner revenue and campus service obligations.

What owners should do

Our proposed execution sequence for this assignment:

  1. Write the operating policy

    Define protected demand, discretionary actions and escalation authority. An economic signal cannot override an operator’s safety constraint or an unavailable export permission. Put the priority into contracts as well as software requirements.

  2. Replay difficult operating days

    Test simultaneous high demand, low solar, an asset trip, missing prices and a failed tenant reduction. Examine recovery, not only the event. The most informative result may be the value of keeping reserve unused.

  3. Commission modes and boundaries

    Qualified teams test normal, constrained and outage modes, telemetry loss, manual control and restoration. Islanding and resynchronization require specific engineered capability; they are not implied by an energy-management platform.

  4. Reconcile performance to the bill

    Compare measured imports, asset duty and settlement with the model. Sitebraid brings the operator, tenant, provider and asset-owner decisions together and closes the development interfaces. The operating team owns live control and subsequent optimization.

How we protect the decision

Define who benefits from arbitrage and who pays for battery replacement. Do not count the same dispatch twice as avoided demand and an incompatible external service. Preserve audit logs of constraints and overrides. Changes in tenant duty or import limits should trigger an operating-model review, not just a new optimization parameter.

What completion looks like

The result is a tested dispatch policy with approved authority, telemetry, fallback and commercial allocation. Report performance against a documented counterfactual and all material costs. A dashboard showing price-responsive operation is not evidence of lower total electricity cost or improved resilience.

What we would track

  • Constraint violations and unapproved dispatches.
  • Net avoided cost after losses, degradation and fees.
  • Protected reserve and recovery demand after events.
  • Forecast error, override response and telemetry availability.

Automate a resolved operating model. Do not ask software to adjudicate conflicting promises.

Source record

NLR: REopt campus energy-system optimization
ERCOT: Demand Response

The cited sources establish the public context, not a project approval, tariff quote or Sitebraid track record. The scenario, commercial tests and delivery approach are illustrative Sitebraid analysis. Confirm applicable requirements and contracts for the specific site before commitment.

Our view and proposed execution plan are Sitebraid opinions, not prescribed engineering or a promise of approval. Specialist design and regulated work belong to the appropriately qualified appointed teams. Public context was reviewed September 8, 2026.

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