Module prices 

Code for calculating commodity prices used by the simulation.

Structs

CommodityPrices

A map relating commodity ID + region + time slice to current price (endogenous)

WeightedAverageAccumulator 🔒

Weighted average accumulator for MoneyPerFlow prices.

WeightedAverageBackupAccumulator 🔒

Weighted average accumulator with a backup weighting path for MoneyPerFlow prices.

Functions

add_full_cost_average_prices 🔒

Calculate full cost prices for a set of commodities using a load-weighted average across assets and add to an existing prices map.

add_full_cost_prices 🔒

Calculate full cost prices for a set of commodities and add to an existing prices map.

add_marginal_cost_average_prices 🔒

Calculate marginal cost prices for a set of commodities using a load-weighted average across assets and add to an existing prices map.

add_marginal_cost_prices 🔒

Calculate marginal cost prices for a set of commodities and add to an existing prices map.

add_scarcity_adjusted_prices 🔒

Calculate scarcity-adjusted prices for a set of commodities and add to an existing prices map.

calculate_annual_activities 🔒

Calculate annual activities for each asset by summing across all time slices

calculate_prices

Calculate commodity prices.

iter_candidate_asset_min_prices 🔒

Calculate prices as the minimum cost across candidate assets, using either a marginal cost or full cost strategy (depending on pricing_strategy). Prices are given for each commodity in the granularity of the commodity’s time slice level. For seasonal/annual commodities, this involves taking a weighted average across time slices for each asset according to potential activity (i.e. the upper activity limit), omitting prices in the extreme case of zero potential activity (Note: this should NOT happen as validation should ensure there is at least one candidate that can provide a price in each time slice for which a price could be required). Costs for candidates are calculated assuming full utilisation.

iter_existing_asset_average_prices 🔒

Calculate prices as the load-weighted average cost across existing assets, using either a marginal cost or full cost strategy (depending on pricing_strategy). Prices are given for each commodity in the granularity of the commodity’s time slice level. For seasonal/annual commodities, this involves taking a weighted average across time slices for each asset according to activity (with a backup weight based on potential activity if there is zero activity across the selection, and omitting prices in the extreme case of zero potential activity).

iter_existing_asset_max_prices 🔒

Calculate prices as the maximum cost across existing assets, using either a marginal cost or full cost strategy (depending on pricing_strategy). Prices are given for each commodity in the granularity of the commodity’s time slice level. For seasonal/annual commodities, this involves taking a weighted average across time slices for each asset according to activity (with a backup weight based on potential activity if there is zero activity across the selection, and omitting prices in the extreme case of zero potential activity).