TY - JOUR A1 - Grimm, Veronika A1 - Schewe, Lars A1 - Schmidt, Martin A1 - Zöttl, Gregor T1 - Uniqueness of Market Equilibrium on a Network: A Peak-Load Pricing Approach JF - European Journal of Operational Research N2 - In this paper we analyze peak-load pricing in the presence of network constraints. In our setup, firms facing fluctuating demand decide on the size and location of production facilities. They make production decisions constrained by the invested capacities, taking into account that market prices reflect scarce transmission capacities. We state general conditions for existence and uniqueness of the market equilibrium and provide a characterization of equilibrium investment and production. The presented analysis covers the cases of perfect competition and monopoly - the case of strategic firms is approximated by a conjectural variations approach. Our result is a prerequisite for analyzing regulatory policy options with computational multilevel equilibrium models, since uniqueness of the equilibrium at lower levels is of key importance when solving these models. Thus, our paper contributes to an evolving strand of literature that analyzes regulatory policy based on computational multilevel equilibrium models and aims at taking into account individual objectives of various agents, among them not only generators and customers but also, e.g., the regulator deciding on network expansion. KW - Pricing KW - Peak-Load Pricing KW - Networks KW - Uniqueness Y1 - 2017 U6 - https://doi.org/10.1016/j.ejor.2017.03.036 VL - 261 IS - 3 SP - 971 EP - 983 ER - TY - JOUR A1 - Grimm, Veronika A1 - Orlinskaya, Galina A1 - Schewe, Lars A1 - Schmidt, Martin A1 - Zöttl, Gregor T1 - Optimal Design of Retailer-Prosumer Electricity Tariffs Using Bilevel Optimization JF - Computers & Operations Research N2 - 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 fixed-price 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, e.g., 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. KW - Electricity tariffs KW - Pricing KW - Bilevel optimization KW - Mixed-integer optimization KW - Tariff design Y1 - 2019 IS - 114 ER - TY - JOUR A1 - Schewe, Lars A1 - Schmidt, Martin T1 - The Impact of Potential-Based Physics Models on Pricing in Energy Networks JF - Central European Journal of Operations Research N2 - Pricing of access to energy networks is an important issue in liberalized energy sectors because of the natural monopoly character of the underlying transport infrastructures. We introduce a general pricing framework for potential-based energy flows in arbitrarily structured transport networks. In different specifications of our general pricing model we discuss first- and second-best pricing results and compare different pricing outcomes of potential-free and potential-based energy flow models. Our results show that considering nonlinear laws of physics leads to significantly different pricing results on networks and that these differences can only be seen in sufficiently complex, e.g., cyclic, networks as they can be found in real-world situations. KW - Energy Networks KW - Pricing KW - Gas Networks KW - Electricity Networks Y1 - 2018 IS - 28(3) SP - 1003 EP - 1029 ER -