USER STORIES & ACCEPTANCE CRITERIA

Project: US Energy Market Performance Analytics

EPIC 1: Portfolio Performance Visibility

US-01: Portfolio KPI Overview

Field	Detail
User Story	As a Portfolio Manager, I want a single-view summary of total revenue, demand, avg price, outage events, and renewable share so that I can assess portfolio health in one glance.
Priority	High
Story Points	3
Sprint	Sprint 1

Acceptance Criteria:

• Portfolio overview query returns 8 KPIs in a single row: total_records, total_demand_gwh, total_revenue_m, avg_price_mwh, renewable_share_pct, outage_events, outage_cost_m, total_co2_tons

• Renewable share % = SUM(demand where source_type=Renewable) / SUM(demand) * 100

• Power BI Page 1 shows 4 KPI cards matching SQL output values within 0.5%

• KPI cards update dynamically when Year or Region slicer is applied

US-02: Energy Source Revenue Comparison

Field	Detail
User Story	As a Capital Allocation Committee member, I want to compare revenue, price, and utilization across all 6 energy sources so that I can make informed investment prioritization decisions.
Priority	High
Story Points	5
Sprint	Sprint 1

Acceptance Criteria:

• Query returns all 6 sources with: demand_gwh, avg_price_mwh, total_revenue_m, avg_capacity_util_pct, total_co2_tons

• Ordered by total_revenue_m descending

• Excel "Source Analysis" tab includes a horizontal bar chart of revenue by source

• Power BI Page 2 scatter plot shows price_per_mwh on X-axis vs co2_intensity on Y-axis

EPIC 2: Renewable Transition Tracking

US-03: Quarterly Renewable Share Tracker

Field	Detail
User Story	As an ESG Lead, I want to track the renewable demand share percentage by quarter across both years so that I can report on our transition progress against the 30% target in ESG disclosures.
Priority	High
Story Points	5
Sprint	Sprint 2

Acceptance Criteria:

• v_renewable_transition view returns: year, quarter, source_type, demand_share_pct, avg_price_mwh, co2_tons

• 8 rows total: 2 years × 4 quarters, each with Renewable and Non-Renewable rows

• demand_share_pct for Renewable + Non-Renewable sums to 100% per quarter

• Power BI Page 3 line chart shows renewable % trend across all 8 quarters

• A reference line at 30% is visible on the chart to show target gap

US-04: Carbon-Adjusted Cost Analysis

Field	Detail
User Story	As a Portfolio Manager, I want to see the true cost per MWh for each source after applying a carbon price of $50/ton so that I can reframe the dispatch optimization model on real economics.
Priority	High
Story Points	5
Sprint	Sprint 2

Acceptance Criteria:

• CO2 intensity query returns co2_per_gwh and revenue_per_co2_ton for all 6 sources

• Coal co2_per_gwh > 800; all renewable sources = 0

• Carbon-adjusted cost insight is documented in Executive Summary and README recommendation

• Dashboard Page 2 allows filtering to compare sources side-by-side on CO2 vs price

EPIC 3: Operational Risk

US-05: Regional Outage Risk Quantification

Field	Detail
User Story	As a Grid Operations Manager, I want to identify which region-source combinations have the highest outage rates and cost impact so that I can prioritize maintenance and predictive monitoring investments.
Priority	High
Story Points	5
Sprint	Sprint 2

Acceptance Criteria:

• Outage analysis query returns top 15 region-source combos with: total_records, outage_events, outage_rate_pct, avg_outage_hours, total_outage_cost_k

• Only rows with at least 1 outage event are returned (HAVING SUM(outage_flag) > 0)

• Power BI Page 4 includes a US map visual with state-level outage density

• Map visual updates when the Source slicer is applied

US-06: Seasonal Capacity Gap Analysis

Field	Detail
User Story	As a Portfolio Manager, I want to understand which quarters have the highest demand vs baseline so that I can identify capacity gaps and evaluate demand response or storage contracts.
Priority	Medium
Story Points	3
Sprint	Sprint 3

Acceptance Criteria:

• Seasonal query returns Q1–Q4 with: avg_demand_mwh, avg_price_mwh, total_outages, total_revenue_m, co2_tons

• Q1 and Q3 avg_demand_mwh is higher than Q2 and Q4 (seasonal validation)

• Excel "Seasonal Analysis" tab includes a column chart of avg demand by quarter

• Strategic insight on Q1/Q3 capacity gap is documented in Executive Summary finding

DEFINITION OF DONE

• SQL query executes without errors; output matches acceptance criteria exactly

• Excel tab renders with correct data, chart visible, and color formatting applied

• Power BI visual cross-filters correctly when slicers are applied

• All acceptance criteria reviewed and checked by BA (Priyanka Chaudhari)

• File committed to correct GitHub folder (/sql, /excel, /powerbi, /docs)

• RTM status updated to Complete for corresponding requirement