electric-power-industry#
Bilevel Markets#
Description: A notebook that presents a comprehensive mathematical formulation of strategic bidding in electricity markets using bilevel optimization and its equivalent single-level Mathematical Program with Equilibrium Constraints (MPEC) obtained through Karush-Kuhn-Tucker (KKT) transformation.
Tags: educational, bilevel, complementarity, amplpy, gurobi, knitro, baron, mpec, energy, electric-power-industry
Capacity expansion of power generation#
Description: Models the extensive form of a deterministic multi-stage capacity expansion problem. In this model we can have multiple resources of the same type which have identical properties. The model can be further developed into a stochastic one.
Hydrothermal Scheduling Problem with Conic Programming#
Description: Hydrothermal Scheduling Problem using Second-Order Cones
Tags: amplpy, conic, second-order-cone, quadratic-cone, nonlinear-programming, scheduling, engineering, power-generation, geothermal-energy, hydropower, electric-power-industry
Author: Gleb Belov (12 notebooks) <gleb@ampl.com>
Network design with redundancy#
Description: Design of an electricity transportation network provides enough redundancy, so that a break of one component does not prevent any user from receiving electricity. The approach also works for similar distribution networks and can potentially be used in the design of military logistic networks.
Optimal Power Flow with AMPL and Python - Bus Injection Model (BIM)#
Optimal Power Flow with AMPL and Python - Bus Injection Model (BIM) with controllable-phase shifting transformers and tap-changing transformers#
Optimal Power Flow with AMPL and Python - DC Power Flow#
Optimal Power Flow with AMPL and Python - conventional Power Flow#
Optimal Power Flow with AMPL and Python - data management#
Description: Optimal Power Flow with AMPL, Python and amplpy
Author: Nicolau Santos (9 notebooks) <nicolau@ampl.com>
Power Generation Portfolio Optimization#
Description: Power generation portfolio optimization to manage several assets and resources.
Power System Optimization with Amplpower package#
Description: this notebook uses amplpower package to solver opf problems
Unit Commitment MINLP with Knitro#
Description: Solving a nonlinear Unit Commitment problem with Knitro using MP features for logic and multi-objective optimization. The goal of this notebook is to show a straightforward and clear way of using nonlinear solvers for complex models with logical expressions and also hierarchical multi-objective optimization.
Tags: mp, knitro, mp2nl, nonlinear, quadratic, minlp, unit-commitment, electric-power-industry, energy, multi-objective, gurobi, xpress, mp2nl
Unit Commitment Problem with AMPL and Python - Power Grid Lib#
Description: Generic notebook to solve Unit Commitment problems with AMPL and Python using the Power Grid Lib model and test instances.
Author: Nicolau Santos (9 notebooks) <nicolau@ampl.com>
Unit Commitment for Colombia’s Energy Market#
Description: Unit Commitment and Reserve Co-Optimization in the Colombian Market.
Unit Commitment for Electrical Power Generation#
Description: This notebook illustrates the power generation problem using AMPL. The original version featured the Gurobi solver. By default, this notebook uses the HiGHS and CBC solvers.
Using multiple objectives in your model#
Description: We show how to use multiple objectives with Amplpy using a nonlinear Unit Commitment problem. We won’t be using native or emulated features from the solver interface, but emulating manually a lexicographic multiobjective problem.
Tags: warm-start, mp, multi-objective, gurobi, xpress, knitro, mp2nl, electric-power-industry, unit-commitment
Warm start solvers with snapshot#
Description: We show how to warm start a solver with a previous solution. A nonlinear Unit Commitment problem is being used as example. We will use the “snapshot” feature for this matter.