Load Forecasting & Energy Scheduling Flashcards

Which weather variable is MOST influential for day‑ahead electric load forecasting in temperate climates?

Answer: Ambient temperature

Ambient temperature is the most influential weather variable for day-ahead electric load forecasting because it directly drives heating and cooling demands. In temperate climates, a significant portion of electricity consumption is attributed to HVAC systems, which respond strongly to temperature fluctuations. High temperatures increase air conditioning usage, while low temperatures increase heating, making temperature the primary determinant of daily load shapes.

The load duration curve plots:

Answer: Ranked load levels versus percent of time

The load duration curve is a graphical representation that plots all observed load levels over a specific period, sorted from highest to lowest, against the percentage of time each load level was met or exceeded. This curve is crucial for generation planning, as it illustrates how long different magnitudes of demand persist, aiding in the optimal selection and scheduling of various types of generating units.

Which statistical technique is commonly applied to model linear relationships between load and explanatory variables?

Answer: Multiple linear regression

Multiple linear regression is a statistical technique widely used in load forecasting to model the linear relationship between electric load (the dependent variable) and several explanatory variables, such as temperature, time of day, and historical load data. It allows forecasters to quantify how changes in these independent variables impact electricity demand, providing a robust and interpretable model for prediction.

Unit commitment in energy scheduling primarily determines:

Answer: Which generators are started or shut down to meet forecasted demand

Unit commitment is a critical optimization problem in power system operations that determines which generating units should be started up, shut down, or kept online over a future period (e.g., 24-48 hours). Its primary goal is to meet the forecasted electricity demand reliably and economically, considering operational constraints and startup/shutdown costs.

Spinning reserve is scheduled to:

Answer: Respond to sudden contingencies

Spinning reserve refers to generating capacity that is synchronized to the grid and ready to increase its output immediately. It is specifically scheduled to quickly respond to sudden, unexpected events like the trip of a large generator or a sudden increase in load, thus maintaining system frequency and reliability.

A SARIMA model is MOST suitable for forecasting:

Answer: Monthly energy demand with seasonality

SARIMA (Seasonal Autoregressive Integrated Moving Average) models are specifically designed for time series data that exhibit both non-stationarity and seasonal patterns. Monthly energy demand often displays strong annual seasonality (e.g., higher in summer/winter) in addition to trends, making SARIMA an ideal choice for accurate forecasting in such scenarios.

The morning ramp in a daily load curve usually occurs during which period?

Answer: 05:00–09:00

The morning ramp refers to the rapid increase in electricity demand that occurs as people wake up, start their daily routines, and businesses open. This typically happens between 5:00 AM and 9:00 AM, driven by increased lighting, appliance use, and commercial/industrial activity.

Demand‑side management programs that shift consumption from peak to off‑peak hours will ____ the forecasted peak load.

Answer: Reduce

Demand-side management (DSM) programs aim to influence customer electricity consumption patterns. By encouraging consumers to shift their usage from periods of high demand (peak hours) to periods of lower demand (off-peak hours), these programs directly reduce the overall peak load that the system needs to supply, improving efficiency and reliability.

In economic dispatch, the marginal cost curve intersects the system demand curve to determine:

Answer: System lambda (incremental cost) and dispatched outputs

In economic dispatch, the system lambda represents the marginal cost of supplying an additional unit of electricity to the system. The intersection of the system's aggregate marginal cost curve (from all dispatched generators) with the total system demand curve determines this system lambda and the optimal power output for each committed generator to meet the demand most economically.