πŸ•ΈοΈ Procedural Grid Expansion

Introduction

Transmission Network Expansion Planning (TNEP) represents a complex optimization problem requiring the simultaneous integration of interdependent technical and economic variables. Neglecting these factors results in suboptimal network designs characterized by excessive costs, operational inefficiencies, and reduced system security.

The literature identifies optimization techniques like Genetic Algorithms to isolate high performing solutions through population based evolution. However, these methodologies are typically constrained by the requirement for a fixed network topology.

The Procedural Grid Expansion feature overcomes the topological rigidity of traditional optimization which in turn minimizes the risk of local optima entrapment and enables a flexible evaluation of transmission expansion alternatives.

Methodology

There are many ways to approach and solve a TNEP problem, and the best candidate depends on the problem conditions. That is why the procedural grid expansion feature offers a range of methods the user can choose from.

Since the Transmission Expansion Planning problem can be broken down into two subproblems - topology design and template allocation - the user can choose to solve one or both problems simultaneously. This could be useful in a case where the topology has already been decided and only the selection of templates is to be decided.

Topology design methods

Steiner Tree: Steiner trees are graphs with N-1 edges that leverage auxiliary nodes called Steiner Points to minimize overall cable length. Once the nodes to be connected are known, a Minimum Spanning Tree algorithm finds the length-minimizing edge combination. The algorithm used to find optimal Steiner Point connections is the Vortex Search Algorithm (VSA), a nature-inspired method that mimics the behavior of vortices in fluid dynamics. More details can be found in the source paper Sustainable Metaheuristic-Based Planning of Rural Medium-Voltage Grids: A Comparative Study of Spanning and Steiner Tree Topologies for Cost-Efficient Electrification.

Template allocation methods

NSGA3: Genetic Algorithms perform remarkably well for optimization problems with discrete decision variables, particularly once the topology is fixed. In this context, the catalogue elements are defined by the topology, and the options are limited by the catalogue. For example, if two buses have different nominal voltages, the algorithm will only try to allocate transformers from the catalogue that have the same high and low rated voltages. More details can be found in Investment Optimization.

User guide

🚧 Work in progress 🚧

  1. Open a grid model that has a Map widget associated with it.

  2. Add the substations that are planned to be constructed in the map.

  3. Select the Map Widget on the right hand side panel.

  4. Click on the Procedural Grid Expansion button.

  5. Select the number of candidate substations to connect the planned to be constructed substations. The closest ones will be chosen automatically.