In my previous role at a regional utility, I regularly evaluated generation portfolios for reliability.

I needed to clearly articulate the characteristics of each generation type to senior planners.

I described baseload as continuous, low‑cost generation (e.g., nuclear, coal) that runs 24/7; intermediate as mid‑range capacity (e.g., combined cycle gas) that fills the gap between baseload and peak; and peak load as fast‑ramping, high‑cost resources (e.g., gas turbines, batteries) used only during demand spikes. I highlighted how baseload provides grid inertia, intermediate offers flexibility, and peak resources manage short‑term variability, especially with renewables.

The planners adopted a more balanced dispatch schedule, reducing peak‑hour costs by 5% and improving reliability metrics.

While conducting a portfolio analysis for a private equity fund, I needed to rank potential investments.

Calculate LCOE for solar PV and natural‑gas combined‑cycle projects to support investment decisions.

I gathered capital expenditures, O&M costs, fuel prices, capacity factors, and project lifetimes. Using the LCOE formula, I discounted cash flows at the fund’s hurdle rate and derived $45/MWh for solar PV and $55/MWh for natural gas. I also performed sensitivity analysis on fuel price volatility and capacity factor assumptions.

The analysis showed solar PV offered a lower LCOE under most scenarios, leading the fund to allocate 60% of the capital to solar projects.

A state regulator announced a $30/ton CO₂ carbon tax effective next year, affecting our client’s generation mix.

Develop a cost model to quantify the tax’s impact on each fuel type and overall portfolio economics.

I built a spreadsheet model that added the tax cost (tax rate × emission factor) to variable O&M for coal, gas, and oil plants. I updated fuel price forecasts, recalculated marginal costs, and ran a dispatch simulation to see changes in unit commitment. I also evaluated potential shifts toward lower‑emission resources and calculated the net increase in wholesale electricity price.

The model showed a $4/MWh increase for coal, $2.5/MWh for gas, and a negligible effect on renewables, leading the client to consider retiring two older coal units within five years.

During a feasibility study for a new wind farm, the initial budget excluded transmission upgrade costs.

Identify any overlooked expenses and propose a solution to keep the project financially viable.

I performed a GIS analysis of the proposed site, discovered that the nearest substation was 30 km away, requiring a new 115 kV line. I quantified the line construction cost, added it to the cash flow model, and re‑ran the NPV analysis. To offset the added expense, I negotiated a power purchase agreement with a higher price per MWh and applied for a state grant covering 30% of the transmission cost.

The revised model showed a still‑positive NPV, and the project secured financing with the adjusted PPA terms.

My team was tasked with updating the 5‑year demand forecast for a mid‑size utility undergoing rapid industrial growth.

Create a robust forecasting model that captures seasonal, economic, and policy drivers for both customer segments.

I segmented the load profile into residential and industrial components. For residential, I used weather‑adjusted regression models based on temperature and historical usage. For industrial, I incorporated GDP growth forecasts, sector‑specific production indices, and planned capacity expansions. I applied a Monte‑Carlo simulation to capture uncertainty and generated confidence intervals. The model was validated against the last three years of actual load data, achieving a mean absolute percentage error of 2.3%.

The utility adopted the forecast for its Integrated Resource Plan, enabling timely investment decisions in new generation and demand‑side resources.

I needed to present the results of a renewable integration study to the city council, many of whom had limited technical background.

Create clear visualizations that convey the key findings and recommended actions.

I built an interactive Tableau dashboard featuring a simple stacked‑area chart showing hourly generation mix, a heat map of congestion events, and a scenario comparison slider for CO₂ emissions. I used color‑coding and concise annotations to highlight peak‑load periods and the impact of adding battery storage. I also prepared a one‑page executive summary with key metrics.

The council quickly approved funding for a 10 MW battery project, citing the clarity of the visual evidence.

During a strategic planning workshop, senior management asked about DER impacts on our grid operations.

Summarize key challenges and opportunities to inform the 2025 grid modernization roadmap.

I identified challenges: voltage regulation, two‑way power flows, and limited visibility. I highlighted opportunities: peak shaving, ancillary service provision, and increased resilience. I referenced recent FERC orders on DER aggregation and noted state incentives driving adoption. I suggested pilot projects for advanced inverter controls and a DER management platform.

Management approved a $2 M pilot for a DER aggregation platform, positioning the utility to capture new revenue streams.

I was part of a cross‑functional team evaluating long‑term decarbonization pathways for a utility with significant natural‑gas assets.

Assess whether investing in green hydrogen production aligns with the utility’s net‑zero goals.

I described green hydrogen as hydrogen produced via electrolysis powered by renewable electricity. I outlined its applications: sector coupling (e.g., steel, chemicals), long‑duration storage, and balancing renewable intermittency. I analyzed cost trajectories, noting current electrolyzer CAPEX of $1,200/kW and projected declines to $600/kW by 2030. I referenced the EU’s Hydrogen Strategy and potential tax credits. I performed a levelized cost of hydrogen (LCOH) comparison against gray hydrogen, showing competitiveness under a $50/ton CO₂ price.

The analysis supported a decision to allocate $10 M to a pilot green hydrogen electrolyzer, positioning the utility for future market participation.

Our market analysis team needed to forecast price volatility in the PJM market with increasing battery storage penetration.

Develop a methodology to quantify storage’s effect on price spreads and ancillary service revenues.

I built a unit‑commitment model that incorporated storage as a dispatchable resource with state‑of‑charge constraints. I ran simulations for scenarios with 0 GW, 2 GW, and 5 GW of battery capacity. I measured changes in the day‑ahead price spread, frequency of negative prices, and revenue from frequency regulation. I also performed sensitivity analysis on battery round‑trip efficiency and degradation costs.

The model showed that 5 GW of storage could reduce peak‑hour price spikes by 15% and increase regulation revenue by 20%, informing stakeholders about the economic value of storage investments.

Our utility planned to defer a planned coal plant retirement based on legacy assumptions about future demand.

Present a data‑driven analysis showing that early retirement would not jeopardize reliability and would yield cost savings.

I compiled a multi‑year demand forecast, incorporated recent energy‑efficiency program impacts, and ran reliability simulations. I prepared a concise slide deck highlighting the risk of stranded assets and the financial upside. I scheduled a meeting with the CFO and VP of Operations, addressed their concerns about reliability, and offered a phased retirement plan with contingency reserves.

Leadership approved the early retirement, resulting in $30 M in avoided O&M costs over the next five years.

I was tasked with delivering a cost‑benefit analysis for a new solar project within two weeks, but underestimated data collection time.

Complete the analysis and communicate the delay to the project manager.

I realized the delay early, informed the manager, and provided a revised timeline. I then prioritized data sources, delegated data cleaning to a junior analyst, and set daily check‑ins. After delivering the analysis, I documented the bottleneck and instituted a standard data‑request checklist for future projects.

The revised analysis was accepted, and the new checklist reduced data‑gathering time by 30% on subsequent projects.

Our company needed to develop a strategy for participating in a new capacity market, requiring input from finance, operations, and regulatory teams.

Facilitate a collaborative process to produce a unified market entry plan.

I organized a series of workshops, defined clear objectives, and created a shared project workspace. I gathered operational data on plant availability, financial models of revenue streams, and regulatory compliance requirements. I synthesized inputs into a decision matrix, highlighted trade‑offs, and drafted a recommendation document. I ensured each team’s concerns were addressed and secured consensus through iterative reviews.

The final plan was approved by senior leadership, leading to a successful bid that secured 1,200 MW of capacity credits and projected $15 M in annual revenue.