Power System Stochastic Dual Dynamic Programming

The main goal of this library is to provide support for studies regarding the optimal dispatch of power systems, majorly comprised of Thermoelectric and Hydroelectric Generators.

Note 1 This is an under development library.

A special thank should be given to professor André Marcato. This project does not intend to substitute the similar library PySDDP.

Note 1 This project is being developed alongside the masters course: Planejamento de Sistemas Elétricos, as part of the masters program in Energy Systems at the Electrical Engineering Graduate Program from the Universidade Federal de Juiz de Fora - Brazil

Note 2 The code will evolve alongside the video lectures provided by professor Marcato at: Curso de Planejamento de Sistemas Elétricos

Installation

pip install powersddp

Example

There are two ways of initializing a Power System. Either by providing a .yml file, or by passing a dictionary as an initialization data. Both are depicted bellow:

Note: When using the file input method (.yml format) check the example of how to declare the parameters.

Initializing a PowerSystem

import powersddp as psddp

system = psddp.PowerSystem(path='system.yml')

print("System Load: {}\n"
      "Number of HGUs: {}\n"
      "Number of TGUs: {}".format(system.data['load'],
                                  len(system.data['hydro_units']),
                                  len(system.data['thermal_units'])))

import powersddp as psddp

data = {'load': [50, 50, 50],
        'discretizations': 3,
        'stages': 3,
        'scenarios': 2,
        'outage_cost': 500,
        'hydro_units': [{'name': 'HU1',
                         'v_max': 100,
                         'v_min': 20,
                         'v_ini': 100,
                         'prod': 0.95,
                         'flow_max': 60,
                         'inflow_scenarios': [[23, 16], [19, 14], [15, 11]]}],
        'thermal_units': [{'name': 'GT1', 'capacity': 15, 'cost': 10},
                          {'name': 'GT2', 'capacity': 10, 'cost': 25}]}

PowerSystem = psddp.PowerSystem(data=data)

print("System Load: {}\n"
      "Number of HGUs: {}\n"
      "Number of TGUs: {}".format(PowerSystem.data['load'],
                                  len(PowerSystem.data['hydro_units']),
                                  len(PowerSystem.data['thermal_units'])))

Dispatching a PowerSystem

dispatch() accepts the following arguments:

• solver : str, optional defaults to 'sdp'

  • Selects the solver option for the minimization objective function.

• scenario : int, optional defaults to 0

  • Chooses either a specific scenario to investigate (scenario>1) or all scenarios to evaluate (scenario= 0). Starting from 0 to the number of declared scenarios in the hydro_units['inflow_scenarios'] parameter.

• verbose : bool, optional defaults to False

  • Displays the PDDE solution for every stage of the execution. Use with care, solutions of complex systems with too many stages and scenarios might overflow the console.

• plot : bool, optional, defaults to False

  • Displays a sequence of plots showing the future cost function for every stage of the execution.

The following example executes the Power System dispatch using the Unique Linear Programming method for the first scenario (id = 1) and outputs the optimization steps.

import powersddp as psddp

data = {'load': [50, 50, 50],
        'discretizations': 3,
        'stages': 3,
        'scenarios': 2,
        'outage_cost': 500,
        'hydro_units': [{'name': 'HU1',
                         'v_max': 100,
                         'v_min': 20,
                         'v_ini': 100,
                         'prod': 0.95,
                         'flow_max': 60,
                         'inflow_scenarios': [[23, 16], [19, 14], [15, 11]]}],
        'thermal_units': [{'name': 'GT1', 'capacity': 15, 'cost': 10},
                          {'name': 'GT2', 'capacity': 10, 'cost': 25}]}

PowerSystem = psddp.PowerSystem(data=data)
operation = PowerSystem.dispatch(solver='ulp', scenario=1, verbose=True)

print(operation)