RT info:eu-repo/semantics/article
T1 A simple and efficient method to allocate costs and benefits in energy communities
A1 Gonzalez-Asenjo, David
A1 Izquierdo Millán, Luis Rodrigo
A1 Sedano, Javier
K1 Energy community
K1 Prosumer
K1 Allocation
K1 Costs
K1 Fairness
K1 Efficiency
K1 Ingeniería
K1 Engineering
K1 Informática
K1 Computer science
AB Purpose: Define a simple and efficient method to allocate costs and benefits in energy communities, and characterize some of its key properties. Design/methodology/approach: The approach is theoretical. We define an algorithm to allocate costs and benefits in energy communities, and derive some of its formal properties using mathematical reasoning. We also compare the proposed algorithm with several alternatives. Findings: The proposed algorithm is simple and it ensures that the resulting distribution of costs and benefits is (i) beneficial for every member of the community, (ii) efficient, (iii) fair (in a formally defined sense), (iv) smooth (small changes in the consumption or in the generation of energy cannot lead to big changes in the allocation of costs and benefits), and (v) environmentally friendly in the sense that the individual allocated cost is a strictly increasing function of individual consumption. Research limitations/implications: The properties of the proposed algorithm are satisfied for a specific type of energy community that is defined in the paper. Practical implications: The algorithm is easy to implement in any energy community. Social implications: The algorithm is highly relevant for any community of prosumers who are willing to exchange energy internally. It guarantees a number of desirable properties that are formally defined in the paper. Originality/value: We prove that a simple algorithm to allocate costs and benefits in energy communities guarantees the fulfilment of several desirable properties.
PB OmniaScience
SN 2013-8423
YR 2023
FD 2023
LK http://hdl.handle.net/10259/7775
UL http://hdl.handle.net/10259/7775
LA eng
NO This research has been founded by the CDTI (Centro para el Desarrollo Tecnológico Industrial) under projects CER-20211022, MIG-20211008 and MIG-20211033, by the ICE (Junta de Castilla y León) under projects CCTT3/20/BU/0002, by the Artificial Intelligence R&D Missions Program of the State Secretariat for Digitalization and Artificial Intelligence (SEDIA) of the Ministry of Economic Affairs and Digital Transformation (MIA.2021.M01.0004) corresponding to the funds of the Recovery, Resilience and Transformation Plan, by the Spanish State Research Agency (PID2020-118906GB-I00/AEI/ 10.13039/501100011033), and by the Ministry of Science and Innovation (TED2021-131388B-I00).
DS Repositorio Institucional de la Universidad de Burgos
RD 09-may-2024