Management Consulting World 131

Find out the ratio between Curtailment_GWh and Redispatch_GWh and for the lowest average ratio of Country-Region pair, report the average Avoided Curtailment (MWh) and causes of curtailment. Represent the average Avoided Curtailment to two decimal places Present these findings on a new slide you create.

Identify the region with the highest average asset-level Total Score (defined as the sum of Criticality Score, Renewable Impact, and Risk Score), and the country within that region that has the highest average Total Score. Tell me the top ranking region, the top ranking country within that region, and the average scores for both. Reply to me with your answer here (rounded to 1 decimal).

Tell me whether or not the asset type that has the highest average adjusted failure probability per outage is also responsible for the highest average Value of Lost Load (VOLL) per asset. VOLL is defined as the product of SAIDI, number of customers affected, and assumed € per Customer-Minute. If it doesn't, which asset type does have the highest VOLL per asset? And for that asset type, what is the average adjusted failure probability per outage and the average VOLL per asset? Write your answer to me in here, rounding the output dollar values to the nearest 0.1 million and the output percentages to the nearest 0.01%.

Calculate the NPV from the 12-year cash flow on renewable enablement benefits, considering the following assumptions: - The steady-state annual benefits from renewable enablement mentioned in the business case represent the annual renewables revenue for year 1, which then grows at a rate of 10% during each of the next 11 years. - The OPEX is provided in the attached slide deck. - Assume an 8% annual discount rate, and no discount in the 1st year. State the final NPV in billions with two decimal places here as a message here

Investigate whether EuroGrid should consider increasing staffing. Determine if the number of working people per impacted asset is correlated with the expected economic impact of unforeseen downtime in each Country-Region combination. Assume that downtime also includes emergency repairs. Let's conduct 2 regression analyses using data in each country-region pair: - [Workers Per Asset] vs [Economic Cost Per Worker Per Weather Event] for weather related outages - [Workers Per Asset] vs [AVG Emergency Repair Cost]. Provide the R² value for each relationship to the nearest 2 decimal places. More investigation is warranted so long as both models have R² value > 0.5. Based on the models, recommend whether to proceed with this investigation or not. Keep this in mind: - For each analysis, use unique asset counts that correspond to the underlying dataset used when calculating workers per asset. - For both assessments we can assume that all workers in the workforce are supporting responses to unforeseen downtime and that workforce size has not changed in the past 5 years. - For emergency repair costs, use the simple average of the annual repair cost over the full 5 year history (2020 - 2024) for each country-region pair. - For each individual regression analysis only use the data present in both sets of data needed for that regression (e.g., if Austria Alpine has workforce data and weather data but no emergency data then it will be used in the 1st regression but removed from the 2nd regression analysis). -Use the EuroGrid's maintenance CapEx/OpEx 5-yr summary file to get the emergency repair cost figures for each country-region pair. Use the Grid workforce and maintenance productivity file to get workforce size. Use the extreme weather and climate stress dataset to get the number of impacted assets and total weather events per year. Write out the answer for me here in a brief message.

Can you calculate the annual EU implied revenue for each Eastern European TSO? Use the midpoint of their implied market share ranges and 40 billion euros as the total market size. Using the implied revenue, calculate the EU renewable revenue for each TSO and for EuroGrid. Please refer to the attached file for the % share of renewables. As an output, create a *NEW SLIDE DECK*, containing a) EU renewables revenue for top two TSOs by renewable revenue and for EuroGrid (in $B, rounded to nearest $0.1B), and b) a statement of the amount of EU renewables revenue required for EuroGrid to achieve 60% market share in a market composed only of EuroGrid and the Eastern European TSOs (in $B, rounded to the nearest $0.1B). Do not round calculation steps. Use 1 Euro = 1.2 USD for currency conversion.

Identify the Phase 1 Assets from the 10 Year Roadmap, assuming that SAIFI / SAIDI hotspots can be defined as assets having SAIFI > 1.0 and SAIDI > 60. Ignore the key criteria for substations and the note on rising corrective maintenance trends. Utilizing the registry, asset financial model, and risk matrix, provide (1) the total count of identified assets and (2) the total NPV. Report total NPV in millions rounded to 2 decimals. Reply straight here only.

Assuming Eurogrid goes through with the labor reallocation efforts described in the operational efficiency analysis, calculate both the % of total staff that is a manager and the average span of control across all departments (excluding IT & Digital Systems). Use the following pre-allocation manager shares: Grid Operations & Control Center (20%), Field Maintenance & Construction (15%), Asset Management & Planning (15%), Tech (10%), and Other corporate functions (25%). Assume % of managers is the same in both the department that is being re-allocated and the proportion of FTE being re-allocated. Assume all FTE reallocation goes into the IT & Digital Systems department. Round all headcount figures down to the nearest integer in your calculations. Round responses to two decimal places. Provide all your answers directly in here.

EuroGrid wants to understand whether the root cause of its asset failures can be explained by age, load, and/or frequency of weather events. Identify the 3 manufacturers with the highest total failures over the past 5 years across all asset types and then run a multivariate regression on SAIDI for each manufacturer using the asset registry and the extreme weather dataset (filtering out sensors, breakers, and substations, as these assets' failure patterns and/or shorter operational lifespans would skew the regression results). Use the attached file to map countries and regions between the Asset Registry and the weather dataset. For each manufacturer, tell me the R Square of the regression. Round all final answers to 2 decimals. Return your answer directly in here

Please use EuroGrid's headcount per department and the attached benchmarks to calculate the estimated total cost of each of the departments' headcount. Round all final amounts to full USD. Provide your answer as a message here, listing the departments and the total cost in USD for each.

Looking only at projects in the Connection Queue that have a status of "Approved" or "Connected", calculate the percentage of the Total Forecasted Demand for the years 2026, 2027, and 2028 that could be covered by these renewable energy projects. Our focus here is only the Netherlands. Use the data from the renewables and load forecast. Assume the percentages will be cumulative year over year and that renewables capacity is available in the full connection year and in all subsequent years (ignore 2025 connections and use 2026 as the base year). Round your final answers to whole percentages. Print your response to me here.

What is the net aggregate annual benefit (i.e., total annual savings minus total annual opex) of all of the use cases in the digital use case sizing analysis? According to the new transmission technologies deck, which technology discussed therein has the most annual savings? How much is expected in yearly savings and annual opex for that technology? What would be the new net aggregate annual benefit if all you did was incorporate the savings and annual opex numbers you just identified? Give your answers in EUR millions, rounded to one decimal place. Do not round intermediary calculations. Provide your answers directly to me here.

Take a look at our workforce distribution in the country where we've spent the most on OPEX from 2020-24. Knowing we need 2 line technicians per transmission line, 1 substation technician for each substation and transformer, 1 protection engineer for each sensor and breaker, and 1 maintenance planner who can split their time among 5 different assets. What's the total headcount we need for each role in that country? Put together a table with the country, the roles, current headcount, and total headcount needed. Round headcounts to the nearest whole number. Reply to me here.

Please calculate how much Germany's and Netherlands' renewables pipelines (will be only 95%) will cover out of their total yearly loads in 2027 and 2028 in % terms. You can use their average historical total load data as the estimate for future needs. Output the year and coverage percentage. Return it as a short message to me here. Round the final percentage values to 0.01%.

Can you state the total simple average of the average implementation cost values, across the various technologies? Use the attached implementation cost deck. Also, state how many technologies have a typical cost more than the average calculated above. Give the final monetary values in millions ($ USD) and round final values to 1 decimal place. Print your answer out here.

Can you please evaluate the outage causes that affect each country the most, in terms of total outage duration? Categorize hazards relating to flooding or storms as the "Weather - Storm" cause and those relating to heat or wildfire as the "Weather - Heat" cause. For France and the Netherlands, state the top weather cause by outage duration, the total events per year in that cause, and the average outage minutes per event in that cause. Note that the Outage ID doesn't reflect individual events; it can be a single event or multiple events combined. Final answers should be rounded to two decimal places. Please report your answers directly to me in here.

Using the Digital Twin Input and Additional bus datasets, identify the Bus IDs associated with renewable energy generation. For each of these Bus IDs, calculate the average (in GW) of their three highest load values. Based on these averages, shortlist the top 2. Round to 3 places. Give the answers here.