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OptFlow
This computational tool determines the optimal operation of a generation/transmission system, with an integrated representation of both the AC electrical network constraints (bus voltage limits, reactive power limits, etc.) and the hydrothermal system modeling (water balance of plants in cascade, turbining limits, limits on thermal generation, etc.)
OptFlow can be used in short and middle term planning operation studies; in the optimization of reactive sources (e.g., the dimensioning and location of capacitors); and for determining the tariffs of ancillary services such as reactive support and others.
OptFlow problem is formulated as a non-linear optimization model, whose constraints include:
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Kirchoff laws: nonlinear active and reactive power balance equations for each node of the electrical network; |
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Network operating limits: bus voltage, active and reactive power flow in circuits, transformer taps and others; |
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Hydrothermal generation system constraints. |
The objective functions represented by the model vary with the the application:
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Short-term dispatch problem: minimize the total operating cost, which includes the variable operating cost of thermal plants and the opportunity cost of hydro plants (“water values”), which come from the stochastic dispatch model for middle-term; |
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Operational planning studies: maximize load level for a given set of buses for voltage collapse studies; maximize active power transfer between areas; minimize active power losses through reactive control re-scheduling; minimize load shedding, etc; |
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Reactive support planning studies: minimize the reactive power injection. |
The decision variables are:
Active power generation of each generation unit; terminal voltage level for each generation unit, synchronous condenser and static VAr compensator; tap control for controllable transformers; switch control for controllable banks, etc.
OptFlow output comprises
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active/reactive generation in each generation unit |
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active/reactive flow in each circuit |
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bus voltage level |
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transformer tap for each controllable transformer |
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level of losses |
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amount of power transfer between areas |
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marginal costs associated to the active/reactive balance equations in each bus and to line flow limits |
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depending on the objective function, amount of load curtailment, bus final load level, etc |
Solution Methodology
The nonlinear optimization problem is solved by an interior point method.
Tela 1.1.3
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