Neural Networks for Encoding Dynamic Security-Constrained Optimal Power Flow to Mixed-Integer Linear Programs

03/17/2020
by   Andreas Venzke, et al.
0

This paper introduces a framework to capture previously intractable optimization constraints and transform them to a mixed-integer linear program, through the use of neural networks. We encode the feasible space of optimization problems characterized by both tractable and intractable constraints, e.g. differential equations, to a neural network. Leveraging an exact mixed-integer reformulation of neural networks, we solve mixed-integer linear programs that accurately approximate solutions to the originally intractable non-linear optimization problem. We apply our methods to the AC optimal power flow problem (AC-OPF), where directly including dynamic security constraints renders the AC-OPF intractable. Our proposed approach has the potential to be significantly more scalable than traditional approaches. We demonstrate our approach for power system operation considering N-1 security and small-signal stability, showing how it can efficiently obtain cost-optimal solutions which at the same time satisfy both static and dynamic security constraints.

READ FULL TEXT
research
09/05/2018

Tire Noise Optimization Problem: a Mixed Integer Linear Program Approach

We present a Mixed Integer Linear Program (MILP) approach in order to mo...
research
10/21/2021

Modeling the AC Power Flow Equations with Optimally Compact Neural Networks: Application to Unit Commitment

Nonlinear power flow constraints render a variety of power system optimi...
research
02/28/2023

Non-linear Topology Optimization of District Heating Networks: A benchmark of Mixed-Integer and Adjoint Approaches

The widespread use of optimization methods in the design phase of Distri...
research
09/28/2018

The Partially Observable Games We Play for Cyber Deception

Progressively intricate cyber infiltration mechanisms have made conventi...
research
01/25/2023

A Sequential Deep Learning Algorithm for Sampled Mixed-integer Optimisation Problems

Mixed-integer optimisation problems can be computationally challenging. ...
research
10/03/2019

Verification of Neural Network Behaviour: Formal Guarantees for Power System Applications

This paper presents for the first time, to our knowledge, a framework fo...
research
04/24/2020

Simulating and Evaluating Rebalancing Strategies for Dockless Bike-Sharing Systems

Following the growth of dock-based bike sharing systems as an eco-friend...

Please sign up or login with your details

Forgot password? Click here to reset