Optimal design of retailer-prosumer electricity tariffs using bilevel optimization. (July 2021)

• Record Type: Journal Article
• Authors: Grimm, Veronika; Orlinskaya, Galina; Schewe, Lars; Schmidt, Martin; Zöttl, Gregor
• Is Part Of: Omega. Volume 102(2021)
• Publication Date: 2021-07
• Subjects: Electricity tariffs -- Pricing -- Bilevel optimization -- Mixed-integer optimization -- Tariff design; 90-XX -- 90Bxx -- 90C11 -- 90C90; Management -- Periodicals; 658.4005
• DOI: 10.1016/j.omega.2020.102327
• Languages: English
• ISSNs: 0305-0483

Abstract

Highlights: We study single or bilevel models, respectively, for flexible electricity tariffs to appropriately capture the incentives of retailers and consumers. We consider the following flexible electricity tariffs: fixed-price, time-of-use, real-time-pricing, and critical-peak-pricing tariffs. The tariffs are analyzed in a detailed computational study. Real-time-pricing increases retailer profits, however, shifts all price risk to the prosumer. Time-of-use and critical-peak-pricing only yield mild additional retailer profits. Abstract: We compare various flexible tariffs that have been proposed to cost-effectively govern a prosumer's electricity management—in particular time-of-use (TOU), critical-peak-pricing (CPP), and a real-time-pricing tariff (RTP). As the outside option, we consider a fixed-price tariff (FP) that restricts the specific characteristics of TOU, CPP, and RTP, so that the flexible tariffs are at least as profitable for the prosumer as the FP tariff. We propose bilevel models to determine the optimal interplay between the retailer's tariff design and the prosumer's decisions on using the storage, on consumption, and on electricity purchases from as well as electricity sales to the grid. The single-level reformulations of the considered bilevel models are computationally highly challenging optimization problems since they combine bilinearities and mixed-integer aspects for modeling certain tariff structures. Based on a computational study using real-world data, we find that RTP increases retailer profits, however, leads to the largest price volatility for the prosumer. TOU and CPP only yield mild additional retailer profits and, due to the multiplicity of optimal plans on the part of the prosumer, imply uncertain revenues for the retailer.