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3142. Optimizing System Sizing: A Stochastic Bi-Level Approach for Green Electricity Retailers

Invited abstract in session MB-35: Stochastic Optimization for Energy Transition, stream Stochastic, Robust and Distributionally Robust Optimization.

Monday, 10:30-12:00
Room: 44 (building: 303A)

Authors (first author is the speaker)

1. Patrizia Beraldi
Department of Mechanical, Energy and Management Engineering, University of Calabria

Abstract

We present a stochastic Bi-Level approach to support electricity retailers in making investment decisions in sustainable energy systems to supply green electricity. The interaction between the retailer, acting as leader, and the follower, representing a set of residential prosumers, is modelled as a Stackelberg game. Both players solve an optimization problem subject to uncertainty related to fluctuating market prices, weather variables and prosumer load. In particular, the leader solves a strategic problem referring to the optimal sizing of the energy system while conjecturing the possible reaction of the follower to the offered tariffs. The follower reacts to the communicated prices defining the procurement plan in terms of amount of electricity to purchase from the retailer and competitors so to minimize the expected electricity bill. The follower’s reaction affects the retailer’s profit computed as difference between the revenue from electricity selling and the total cost. To account for the retailer's attitude towards risk, the upper level problem includes a safety measure to control the average profit that can be gained in a given percentage of unfavourable situations. A tailored solution approach is developed and tested on a realistic case study calibrated on the Italian electricity market. Numerical results demonstrate the efficiency of the proposed approach and validate the significance of explicitly dealing with uncertainty and integrating safety measures.

Keywords

Status: accepted

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