S. Vemuri

Fuel Resource Scheduling -The Long-Term Problem

Long-term fuel scheduling addresses the problem of optimum allocation of fuels to various generating units using mixed and shared fuels subject to yearly and monthly constraints, inventory constraints, generation availability constraints and load require ments (both energy and capacity). This problem is formulated as a network flow optimization problem. Feasibility of the resulting fuel consumption plan with respect to fuel constraints and its optimality with respect to cost of fuel purchases are assured by the network flow algorithm. Feasibility with respect to the load duration and generation availability are assured by defining appropriate fictitious branches in the network. The limits on these branches are calculated by the method of cumulants. The unit priorities in each month are modified by an iterative procedure, on the basis of both fuel price and fuel availability as seen by the network flow algorithm. Results for a 17 unit/17 contract test system over one year are presented to illustrate various aspects of the long-term fuel resource scheduling problem.

Fuel Resource Scheduling, Part III-The Short-Term Problem

The paper presents a method for optimum scheduling of fuels over a few days, subject to fuel supply limits, spanning different time periods, and unit operating constraints. Constraints over mixed and shared fuels, are also considered. Results for a 17 unit/17 contract test system over a two day study period are presented and discussed. Scheduling fuel resources, in the short term, to satisfy fuel supply and consumption constraints is a nontrivial task for planning and operating engineers of an electric utility. The complexity of the problem increases when one has to consider the fuel constraints over different time periods (hour, day, combination of days, etc.) simultaneously. When the (linear) fuel constraints are coupled with the linear and nonlinear operating constraints of the system the complexity of the scheduling problem becomes a mathematical challenge for the operation researchers and is beyond the reach of intuitive methods. The current techniques for planning the operation of generating units in a power system subject to operating and fuel supply constraints share the following common features. 1) Daily (or study period) fuel supply limits are either too broad to be constraining or so narrow that they can be specified as fixed amounts that must be consumed. Either daily limits or study period limits (but not both) can be specified in a given study. 2) All hourly fuel supply constraints are translated as hourly constraints on the capacity of individual units. 3) Price of the fuel to be used by a unit is known apriori.

Fuel Resource Scheduling, Part I-Overview of an Energy Management Problem

This paper at an overview level discusses the probiems of Fuel and Resource Scheduling (FRS) in an Energy Management System (EMS). For a computer-based FRS, a hierarchical scheduling scheme is proposed so that long-term fuel strategy over a year can be meaningfully translated into real-time decisions for loading the units. In this process FRS has been decomposed into individual problems of Resource Budgeting for long-term fuel scheduling, Resource Scheduling for short-term fuel scheduling, and real-time fuel scheduling functions of Real-Time Resource Scheduling and Resource Constrained Economic Dispatch.

Fuel Resource Scheduling The Daily Scheduling Problem

This paper addresses the daily fuel scheduling problem of optimum allocation of fuels to various generating units to meet the hourly load requirementeemnt subject to hourly. and daily constraints. The hourly constraints consist of maximum and minimum limits on unit capacities, fuel consumption by a single unit or combination of units, and fuel supply from each contract. The daily maximum and minimum limits on fuel supply from each contract constitute the set of daily constraints. In addition, units with shared and mixed fuels and contracts supplying to different units are considered simultaneously.