🇺🇸United States

Excessive Fuel Consumption from Suboptimal Economic Dispatch

1 verified sources

Definition

In fossil fuel combined cycle power plants, traditional dispatch methods fail to optimally allocate fuel to gas turbines, leading to higher fuel use than necessary while meeting demand constraints. Optimization models demonstrate weekly fuel reductions of 2-4% are achievable, implying ongoing overruns in standard operations. This stems from simplistic aggregated or pseudo-unit models that ignore unit interactions and limits.

Key Findings

  • Financial Impact: $Unknown (2-4% weekly fuel savings potential)
  • Frequency: Weekly
  • Root Cause: Use of approximate models in economic dispatch ignoring physical unit constraints and interactions

Why This Matters

This pain point represents a significant opportunity for B2B solutions targeting Fossil Fuel Electric Power Generation.

Affected Stakeholders

Dispatch operators, Plant engineers, Unit commitment planners

Deep Analysis (Premium)

Financial Impact

$2-4M annually per 1000 MW fleet (2-4% weekly fuel waste × ~52 weeks × average thermal generation revenue) • $Unknown (2-4% excess fuel erodes margins) • $Unknown (2-4% weekly fuel cost overrun)

Unlock to reveal

Current Workarounds

Excel-based pseudo-unit modeling and manual overrides • Financial spreadsheets tracking suboptimal fuel costs manually • Manual adjustments using simplistic aggregated models in spreadsheets

Unlock to reveal

Get Solutions for This Problem

Full report with actionable solutions

$99$39
  • Solutions for this specific pain
  • Solutions for all 15 industry pains
  • Where to find first clients
  • Pricing & launch costs
Get Solutions Report

Methodology & Sources

Data collected via OSINT from regulatory filings, industry audits, and verified case studies.

Evidence Sources:

Related Business Risks

Idle Equipment and Suboptimal Unit Utilization During Dispatch

$Unknown (tied to 2-4% fuel efficiency gain)

Suboptimal Unit Commitment from Deterministic Dispatch Models

$Reduced by stochastic model (exact baseline overrun not quantified)

Increased Cycling Costs from Inefficient Load Following

$Unknown (efficiency drop significant)

Coal Ash Disposal Compliance Violations and Cleanup Mandates

$Billions in industry-wide remediation (e.g., clean closure costs exceed cap-in-place by multiples)

Excessive Costs from Inefficient Wet Ash Disposal and Pond Management

$Millions per plant in lifecycle handling and closure (wet vs. dry systems)

Outage Cost Overruns from Inaccurate Planning and Estimation

$Millions per outage cycle

Request Deep Analysis

🇺🇸 Be first to access this market's intelligence