  Citation: Lautert, R.R.; Brignol, W.d.S.; Canha, L.N.; Adeyanju, O.M.; Garcia, V.J. A Flexible-Reliable Operation Model of Storage and Distributed Generation in a Biogas Power Plant. Energies 2022, 15, 3154. https://doi.org/10.3390/ en15093154 Academic Editor: Lieven Vandevelde Received: 27 January 2022 Accepted: 27 March 2022 Published: 26 April 2022 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affil- iations. Copyright: © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). energies Article A Flexible-Reliable Operation Model of Storage and Distributed Generation in a Biogas Power Plant Renata Rodrigues Lautert 1, * , Wagner da Silva Brignol 1 , Luciane Neves Canha 1 , Olatunji Matthew Adeyanju 1 and Vinícius Jacques Garcia 2 1 Graduate Program in Electrical Engineering—PPGEE, Federal University of Santa Maria—UFSM, Santa Maria 97105-900, Brazil; brignol@ifsul.pelotas.edu.br (W.d.S.B.); lucianecanha@ufsm.br (L.N.C.); olatunji.adeyanju@acad.ufsm.br (O.M.A.) 2 Graduate Program in Industrial and Systems Engineering—PPGEP, Federal University of Santa Maria—UFSM, Santa Maria 97105-900, Brazil; viniciusjg@ufsm.br * Correspondence: renata.lautert@acad.ufsm.br Abstract: This paper presents a novel methodology for planning and operating biogas energy systems based on the transactive energy concept to determine multilevel operating regimes for distributed generation. The developed model is used to manage the production, storage, and dispatch of biogas energy systems to meet the load demands of the biogas producer and support the operation of the distribution network operator. An Integer Linear Programming (ILP) is fitted to optimize the biogas production of the biogas producer, including the operation of the biogas storage systems and their interaction with the network operator. The model’s objective is to maximize benefits for the participating agents in a transactive energy context. The model’s effectiveness is validated using seven case studies involving biogas systems having different operating ranges and modes to achieve enhanced flexibility and reliability for the system operation with a large proportion of intermittent energy resources. The simulation results showed that the approach could effectively manage the operation of biogas systems and their interaction with the network operator. The developed model is suitable for systems fostering net metering charging and real-time pricing. Keywords: biogas; energy storage; distributed generation; optimization; transactive energy 1. Introduction 1.1. Literature Review The distribution system (DS) is undergoing substantial changes with new techno- logical advances implemented to accommodate the high-share integration of renewable energy resources (RES), including distributed generation (DG) and energy storage systems (ESS) [1–4]. Intermittent energy sources have variable behavior in terms of uncertainty in energy production. Consequently, energy supplied by RES could be greater than the load demand at one point in time and become insufficient at another time. This uncertainty makes it more challenging for the network operator to manage the reliability and security of the systems [5–8]. According to [9], the massive adoption of RES brings challenges regarding efficiency, resilience, and flexibility to operating systems. Currently, the development of microgrids as decentralized distribution networks is paving ways to better integrate RES into the DS with greater flexibility of balancing energy generation and loads locally [10]. Microgrids can be in islanded mode as well as be connected to the main grid, depending on the predefined agreement between the microgrid and network operators for economic and technical reasons [11]. Also, there are possibilities for increased RES in the distribution systems regarding the capability of the ESS systems. Many ESS technologies can be utilized with scalable capacities to store the energy in mechanical, thermodynamical, electrochemical, or electro- magnetic form. Presently, pumped storage represents the majority of installed capacity, Energies 2022, 15, 3154. https://doi.org/10.3390/en15093154 https://www.mdpi.com/journal/energies