9 research outputs found
Is electricity storage systems in the Netherlands indispensable or doable? Testing electricity storage business models with exploratory agent-based modeling
Electricity storage systems (ESS) are hailed by many scholars and
practitioners as a key element of the future electricity systems and a key step
toward the transition to renewables . Nonetheless, the global speed of ESS
implementation is relatively slow, and among possible reasons is the lack of
viable business models. We developed an agent-based model to simulate the
behavior of ESS within the Dutch electricity market. We adopted an exploratory
modeling analysis (EMA) approach to investigate the effects of two specific
business models on the value of ESS from the perspective of both investors and
the government under uncertainties in the ESS technical and economics
characteristics, and uncertainties in market conditions and regulations. Our
results show ESS is not profitable in most scenarios, and generally wholesale
arbitrage business model leads to more profit than reserve capacity. In
addition, ESS economic and technical characteristics play more important roles
in the value of ESS than market conditions, and carbon pricing.Comment: 39 Pages, 6 Figures, 2 tables, article under revie
Designing Local Energy Market Applications
Local energy markets and corresponding information systems are a way to integrate and involve residential customers in the energy transition, which can increase acceptance and drive private investment. This study is focused on the generation of design knowledge for these local energy market user applications in general and specifically to ensure long-term user engagement, which is a crucial success factor to maintain long-term effects. To this end, we derive, instantiate and evaluate seven design principles based on a field implementation with user interaction over 13 months using a design science research approach. The design principles and their instantiations are evaluated based on semi-structured interviews with the participants and a consecutive online experiment. The design principles provide fundamental knowledge for the setup of local energy market user applications and are therefore of value for researchers and practitioners alike
The Merge of Two Worlds: Integrating Artificial Neural Networks into Agent-Based Electricity Market Simulation
Machine learning and agent-based modeling are two popular tools in energy research. In this article, we propose an innovative methodology that combines these methods. For this purpose, we develop an electricity price forecasting technique using artificial neural networks and integrate the novel approach into the established agent-based electricity market simulation model PowerACE. In a case study covering ten interconnected European countries and a time horizon from 2020 until 2050 at hourly resolution, we benchmark the new forecasting approach against a simpler linear regression model as well as a naive forecast. Contrary to most of the related literature, we also evaluate the statistical significance of the superiority of one approach over another by conducting Diebold-Mariano hypothesis tests. Our major results can be summarized as follows. Firstly, in contrast to real-world electricity price forecasts, we find the naive approach to perform very poorly when deployed model-endogenously. Secondly, although the linear regression performs reasonably well, it is outperformed by the neural network approach. Thirdly, the use of an additional classifier for outlier handling substantially improves the forecasting accuracy, particularly for the linear regression approach. Finally, the choice of the model-endogenous forecasting method has a clear impact on simulated electricity prices. This latter finding is particularly crucial since these prices are a major results of electricity market models
Decision support for participation in electricity markets considering the transaction of services and electricity at the local level
[EN] The growing concerns regarding the lack of fossil fuels, their costs, and their
impact on the environment have led governmental institutions to launch energy
policies that promote the increasing installation of technologies that use
renewable energy sources to generate energy. The increasing penetration of
renewable energy sources brings a great fluctuation on the generation side,
which strongly affects the power and energy system management. The control of
this system is moving from hierarchical and central to a smart and distributed
approach. The system operators are nowadays starting to consider the final end users (consumers and prosumers) as a part of the solution in power system
operation activities. In this sense, the end-users are changing their behavior from
passive to active players. The role of aggregators is essential in order to empower
the end-users, also contributing to those behavior changes. Although in several
countries aggregators are legally recognized as an entity of the power and energy
system, its role being mainly centered on representing end-users in wholesale
market participation.
This work contributes to the advancement of the state-of-the-art with
models that enable the active involvement of the end-users in electricity markets
in order to become key participants in the management of power and energy
systems. Aggregators are expected to play an essential role in these models,
making the connection between the residential end-users, electricity markets,
and network operators. Thus, this work focuses on providing solutions to a wide
variety of challenges faced by aggregators.
The main results of this work include the developed models to enable
consumers and prosumers participation in electricity markets and power and
energy systems management. The proposed decision support models consider
demand-side management applications, local electricity market models,
electricity portfolio management, and local ancillary services.
The proposed models are validated through case studies based on real data.
The used scenarios allow a comprehensive validation of the models from
different perspectives, namely end-users, aggregators, and network operators.
The considered case studies were carefully selected to demonstrate the characteristics of each model, and to demonstrate how each of them contributes
to answering the research questions defined to this work.[ES] La creciente preocupaci贸n por la escasez de combustibles f贸siles, sus costos
y su impacto en el medio ambiente ha llevado a las instituciones
gubernamentales a lanzar pol铆ticas energ茅ticas que promuevan la creciente
instalaci贸n de tecnolog铆as que utilizan fuentes de energ铆a renovables para
generar energ铆a. La creciente penetraci贸n de las fuentes de energ铆a renovable trae
consigo una gran fluctuaci贸n en el lado de la generaci贸n, lo que afecta
fuertemente la gesti贸n del sistema de potencia y energ铆a. El control de este
sistema est谩 pasando de un enfoque jer谩rquico y central a un enfoque inteligente
y distribuido. Actualmente, los operadores del sistema est谩n comenzando a
considerar a los usuarios finales (consumidores y prosumidores) como parte de
la soluci贸n en las actividades de operaci贸n del sistema el茅ctrico. En este sentido,
los usuarios finales est谩n cambiando su comportamiento de jugadores pasivos a
jugadores activos. El papel de los agregadores es esencial para empoderar a los
usuarios finales, contribuyendo tambi茅n a esos cambios de comportamiento.
Aunque en varios pa铆ses los agregadores est谩n legalmente reconocidos como una
entidad del sistema el茅ctrico y energ茅tico, su papel se centra principalmente en
representar a los usuarios finales en la participaci贸n del mercado mayorista.
Este trabajo contribuye al avance del estado del arte con modelos que
permiten la participaci贸n activa de los usuarios finales en los mercados el茅ctricos
para convertirse en participantes clave en la gesti贸n de los sistemas de potencia
y energ铆a. Se espera que los agregadores desempe帽en un papel esencial en estos
modelos, haciendo la conexi贸n entre los usuarios finales residenciales, los
mercados de electricidad y los operadores de red. Por lo tanto, este trabajo se
enfoca en brindar soluciones a una amplia variedad de desaf铆os que enfrentan los
agregadores.
Los principales resultados de este trabajo incluyen los modelos
desarrollados para permitir la participaci贸n de los consumidores y prosumidores
en los mercados el茅ctricos y la gesti贸n de los sistemas de potencia y energ铆a. Los
modelos de soporte de decisiones propuestos consideran aplicaciones de gesti贸n
del lado de la demanda, modelos de mercado el茅ctrico local, gesti贸n de cartera
de electricidad y servicios auxiliares locales.
Los modelos propuestos son validan mediante estudios de casos basados en
datos reales. Los escenarios utilizados permiten una validaci贸n integral de los
modelos desde diferentes perspectivas, a saber, usuarios finales, agregadores y
operadores de red. Los casos de estudio considerados fueron cuidadosamente
seleccionados para demostrar las caracter铆sticas de cada modelo y demostrar
c贸mo cada uno de ellos contribuye a responder las preguntas de investigaci贸n
definidas para este trabajo