Green Retailer : A Stochastic Bi-Level Approach to Support Investment Decisions in Sustainable Energy Systems

This paper presents a bi-level approach to support retailers in making investment decisions in renewable-based systems to provide clean electricity. The proposed model captures the strategic nature of the problem and combines capacity sizing decisions for installed technologies with pricing decisions regarding the electricity tariffs to offer to an end-user representative of a class of residential prosumers. The interaction between retailer and end-user is modelled using the Stackelberg game framework, with the former acting as a leader and the latter as follower. The reaction of the follower to the electricity tariff affects the retailer's profit which is computed as difference between therevenue generated from selling electricity and the total cost of investment,operation and management.To address uncertainty in wholesale electricity prices, renewable resource availability and electricity requests, the upper-level problem is formulated as a two-stage stochastic programming model. First-stage decisions refer to the sizing of installed technologies and electricity tariffs, whereas second-stage decisions refer to the operation and management of the designed system.The model also integrates a safety measure to control the average profit that can be achieved in a given percentage of worst case situations, so to provide a contingency against unforeseen changes.A tailored approach that exploits the specific problem structure is designed to solve the proposed formulation and widely tested on a realistic case study. The numerical results demonstrate the efficiency of the proposed approach and validate the significance of explicitly dealing with the uncertainty and the importance of incorporating a safety measure