Research Output
1 - 3 of 3
Publication
A method for modeling voltage regulators in probabilistic load flow for radial systems
2014-07-10, Melhorn, Alexander C., Dimitrovski, A.
Probabilistic load flow is becoming a more useful and needed power system analysis technique with the increase of stochastic generation and demand. This paper improves the usefulness of probabilistic load flow by demonstrating an algorithm for modeling voltage regulators within the probabilistic load flow solution. Previously, the voltage regulators have been removed from the system before analysis. The proposed technique is verified by comparing the solutions to those obtained by Monte Carlo simulation.
Publication
Sub-hour Unit Commitment MILP Model with Benchmark Problem Instances
2017-07-07, Carroll, Paula, Flynn, Damian, Fortz, Bernard, Melhorn, Alexander C.
Power systems are operated to deliver electricity at minimum cost while adhering to operational and technical constraints. The introduction of smart grid technologies and renewable energy sources offers new challenges and opportunities for the efficient and reliable management of the grid. In this paper we focus on a Mixed Integer Programming sub-hour Unit Commitment model. We present analysis of computational results from a large set of problem instances based on the Irish system and show that problem instances with higher variability in net demand (after the integration of renewables) are more challenging to solve.
Publication
Validating unit commitment models: A case for benchmark test systems
2016-07-21, Melhorn, Alexander C., Li, Mingsong, Carroll, Paula, Flynn, Damian
Due to increasing penetration of non-traditional power system resources; e.g. renewable generation, electric vehicles, demand response, etc. and computational power there has been an increased interest in research on unit commitment. It therefore may be important to take another look at how unit commitment models and algorithms are validated especially as improvements in solutions and algorithmic performance are desired to combat the added complexity of additional constraints. This paper explores an overview of the current state of unit commitment models and algorithms, and finds improvements for both comparing and validating models with benchmark test systems. Examples are provided discussing the importance for a standard benchmark test system(s) and why it is needed to compare and validate the real world performance of unit commitment models.