OASIS Basics

Computer Aided Negotiations of Water Resources Disputes

OASIS Basics

Computer Aided Negotiations of Water Resources Disputes

2

What is OASIS ?What is OASIS ?

Operational Analysis and Simulation of Integrated Systems

Program for modeling the operations of water resources systems

3

What does OASIS do ?…….. and How?

What does OASIS do ?…….. and How?

Simulates the routing of water through a system represented by: Nodes (points of interest)

Demand Junction Reservoirs

Arcs (convey water from node to node) Inflows (positive or negative, fixed by the user)

Routing accounts for human control and physical constraints

Terminal

120110 130100 140

Reservoir JunctionJunction

Arc Arc Arc Arc

Inflow

135

Demand

Reservoir

4

Examples of Human Control Water is moved from node to node according to “operating criteria”. Water is allocated to demand nodes based on pre-established criteria

Examples of Physical Constraints Storage Area Elevation (SAE) tables: Storage volume available at each water

level in a reservoir Maximum flow: restriction on the arc flow imposed by a maximum gate

opening Head - Flow relationships to describe the hydraulics of a canal or canal capacity Evapotranspiration: “Demand” applied to each node to account for

evapotranspiration losses in a reservoir MASS BALANCE : Main constraint that is accounted for during each time step

of the routing

5

What does OASIS do ?…….. and How?

What does OASIS do ?…….. and How?

Water is routed (moved) through the system by calculating: Flow through arcs (arcflows) , Volume stored in each node and Volume allocated to each demand node

these calculations are made for every time step during a pre-established period of simulation,

using a Linear Programming solver which is called every time step

6

Use of Linear Programming in OASISUse of Linear Programming in OASIS

OASIS automatically constructs the LP each time step, solves it, and then turns that mathematical solution into a simulated record of flows and storages

The LP is internal – hidden, unless you request it

Every time step, flow, storage and delivery are decision variables whose values are solved by LP.

7

Routing with a linear programRouting with a linear program

You specify what to do but do not have to tell OASIS how to do it

Constraints: rules that OASIS must obeyGoal: rule that OASIS tries to meet

Written to an objective function which the solver optimizes – determines the solution which best meets the goals within the constraints

Think of the solver as a “smart operator” who obeys the laws of physics (and other specified constraints)

8

Decision Variables and State Variables

Decision Variables and State Variables

Decision variable: A variable whose value is decided by the LP solver. OCL Rules are written with the values of the decision variables

unknown.

State variable: Any variable whose value is known. Some state variables represent decision variables from previous

time steps that the LP solver has already solved. Other state variables represent external conditions (e.g. inflow,

rainfall, date, time-step number)

9

GoalsGoals

Goal: a rule that OASIS tries to satisfy

In any time step, OASIS might not be able to satisfy all or any of a given operating goal

By their nature, operating goals are in competition with each other

OASIS chooses between competing goals by weights that you assign

Example: “Try to deliver 45 mgd to demand node 472”.

10

Balancing GoalsBalancing Goals

The modeler assigns a weight value to every operating goal in the model to construct the objective function

The LP solution scores points by multiplying the weight value by the value of the associated decision variable

In every time step, OASIS determines the values of the decision variables by solving the LP The solution obeys every constraint The solution is the set of decision variable values that

gets the maximum number of points from the set of goals

11

WeightsWeights

Every goal should be assigned a weight value

Positive weights encourage actions while negative weights (penalties) discourage them.

Zero weight is the same as if the goal did not exist.

12

More About WeightsMore About Weights

Assigning weights is usually simple—assign lowest to highest in hierarchical order

Weights do not represent a quantity that you can measure in the real-world system

Weights do represent the relative importance of the different priorities of the operators of the real-world system

It gets easier with experience

13

An analogy to moneyAn analogy to money

Water is like money

Weights are your spending/saving priorities

The lp will allocate your money based on your spending/saving priorities When money is scarce, which bills do you pay first

(should you satisfy a minimum flow requirement or keep water in a lake)?

When money is plentiful, where should you put the extra (should you put it on the floodplain or in a lake)?

14

Example of Using Weights - 1Example of Using Weights - 1

No benefit for moving water downstream; storage remains in node 100 and node 130

wt = 100

wt = 0 wt = 0wt = 0terminal

wt = 0120110

130100

wt = 200

140

15

Example of Using Weights - 2Example of Using Weights - 2

No benefit for moving water between reservoirs, but weight on terminal arc pulls from node 130 until it empties.

wt = 100

wt = 0 wt = 150wt = 0terminal

wt = 0120110

130100

wt = 200

140

16

Example of Using Weights - 3Example of Using Weights - 3

No benefit for moving water between reservoirs, but weight onterminal arc pulls from node 130 until it empties, thenpulls from node 100.

wt = 100

wt = 0 wt = 250wt = 0terminal

wt = 0120110

130100

wt = 200

140

17

Example of Using Weights - 4Example of Using Weights - 4

Water released from node 100 gets 300 weight points, plus 100 points for being stored in node 130,so water is transferred from node 100 to node 130.

wt = 100

wt = 100 wt = 0wt = 100terminal

wt = 100120110

130100

wt = 200

140

18

Example of Using Weights - 5Example of Using Weights - 5

Weight on terminal arc causes the system to be drained.

Moral: use weights on arcs only where necessary.

wt = 100

wt = 100 wt = 250wt = 100terminal

wt = 100120110

130100

wt = 200

140

19

Example of Using Weights - 6Example of Using Weights - 6

OASIS gets the same number of points whether it keeps water in the upstream reservoir or sends it to the downstream reservoir

This is called alternate optima, and it should be avoided

wt = 200

wt = 0 wt = 0wt = 0terminal

wt = 0120110

130100

wt = 200

140

20

Building an OASIS modelBuilding an OASIS model

Basedata: timeseries data

GUI: much of what you need to specify can be done here

OCL (Operations Control Language): provides flexibility “set” the value of a variable Define new constraints and goals for the lp Create new variables, enter new data, exchange information

with other programs

Output: Quickview, Onevar, output.dss