Abstract: Techniques to determine settings for an electrical distribution network are described. Some embodiments are particularly directed to techniques to determine settings for an electrical distribution network using power flow heuristics. In one embodiment, for example, an apparatus may comprise a model reception component, a forecast component, and an optimization component. The model reception component may be operative to receive a model of an electrical distribution network having multiple capacitor banks and multiple voltage regulators, each of the multiple capacitor banks represented in the model by a model capacitor bank, each of the multiple voltage regulators represented in the model by a model voltage regulator, the electrical distribution network having a radial layout in which power flows from a source to multiple nodes in which each node is associated with one voltage regulator. The forecast reception component may be operative to receive a forecast for demand on the electrical distribution network.

Abstract: Computer-implemented systems and methods are provided for determining an action item from a global set of action items for a plurality of customers based on an objective function, a plurality of individual constraints, and a plurality of aggregate constraints. A plurality of offer sets is generated for each customer. An approximate highest reduced adjusted objective for each of the offer sets for each customer is calculated, and the customers are bucketed based on the highest adjusted objective value associated with each customer. The buckets are collapsed into a single bucket record containing a plurality of aggregate offer set columns, and an aggregate offer set column is selected from each bucket record for each bucket. Each bucket associated with a selected offer set is disaggregated, and the action item included in the selected offer set is stored in a computer-readable memory.

Abstract: Computer-implemented systems and methods are provided for determining an action item from a global set of action items for a plurality of customers based on an objective function, a plurality of individual constraints, and a plurality of aggregate constraints. A plurality of offer sets is generated for each customer. An approximate highest reduced adjusted objective for each of the offer sets for each customer is calculated, and the customers are bucketed based on the highest adjusted objective value associated with each customer. The buckets are collapsed into a single bucket record containing a plurality of aggregate offer set columns, and an aggregate offer set column is selected from each bucket record for each bucket. Each bucket associated with a selected offer set is disaggregated, and the action item included in the selected offer set is stored in a computer-readable memory.