collaborators

7 papers

eess.SY2026

ADMM-based decomposed DNN+RLT Relaxations for Completely Positive Models in Electricity Market Clearing

Shudian Zhao, Mohammad Reza Karimi Gharigh, Jan Kronqvist +1

The day-ahead electricity market clearing with nonconvex order types can be formulated as a mixed-integer linear program (MILP), but its LP relaxation may provide weak bounds, and…

eess.SY2026

Event-Based Dynamic Programming for Pumped-Storage Hydropower Scheduling

Bo Yang, Kai Pan, Mohammad Reza Hesamzadeh

This paper studies the single-unit pumped-storage hydropower (PSH) plant scheduling problem with reservoir dynamics, generation and pumping limits, ramping constraints, start-up an…

math.OC2026

A Framework for Eliminating Paradoxical Orders in European Day-Ahead Electricity Markets through Mixed-Integer Linear Programming Strong Duality

Zhen Wang, Mohammad Reza Hesamzadeh, Shudian Zhao +1

The presence of integer variables in the European day-ahead electricity market renders the social welfare maximization problem non-convex and non-differentiable, making classical m…

econ.TH2025

The Theory of Storage in a Power System with Stochastic Demand

Darryl Biggar, Mohammad Reza Hesamzadeh

Electric power systems are increasingly turning to energy storage systems to balance supply and demand. But how much storage is required? What is the optimal volume of storage in a…

econ.EM2025

Driver Identification and PCA Augmented Selection Shrinkage Framework for Nordic System Price Forecasting

Yousef Adeli Sadabad, Mohammad Reza Hesamzadeh, Gyorgy Dan +2

The System Price (SP) of the Nordic electricity market serves as a key reference for financial hedge contracts such as Electricity Price Area Differentials (EPADs) and other risk m…

math.OC2025

Sparse Polynomial Regression under Anomalous Data

Roozbeh Abolpour, Mohammad Reza Hesamzadeh, Maryam Dehghani

This paper starts with the general form of the polynomial regression model. We reformulate the Sparse Polynomial Regression Model (SPRM) with anomalous data filtering as Mixed-Inte…