1,960 research outputs found
Demand and Storage Management in a Prosumer Nanogrid Based on Energy Forecasting
Energy efficiency and consumers' role in the energy system are among the strategic research topics in power systems these days. Smart grids (SG) and, specifically, microgrids, are key tools for these purposes. This paper presents a three-stage strategy for energy management in a prosumer nanogrid. Firstly, energy monitoring is performed and time-space compression is applied as a tool for forecasting energy resources and power quality (PQ) indices; secondly, demand is managed, taking advantage of smart appliances (SA) to reduce the electricity bill; finally, energy storage systems (ESS) are also managed to better match the forecasted generation of each prosumer. Results show how these strategies can be coordinated to contribute to energy management in the prosumer nanogrid. A simulation test is included, which proves how effectively the prosumers' power converters track the power setpoints obtained from the proposed strategy.Spanish Agencia Estatal de Investigacion ; Fondo Europeo de Desarrollo Regional
Stochastic Optimal Investment Strategy for Net-Zero Energy Houses
In this research, we investigate Net-Zero Energy Houses (ZEH), which harness
regionally produced electricity from photovoltaic(PV) panels and fuel cells,
integrating them into a local power system in pursuit of achieving carbon
neutrality. This paper examines the impact of electricity sharing among users
who are working towards attaining ZEH status through the integration of PV
panels and battery storage devices. We propose two potential scenarios: the
first assumes that all users individually invest in storage devices, hence
minimizing their costs on a local level without energy sharing; the second
envisions cost minimization through the collective use of a shared storage
device, managed by a central manager. These two scenarios are formulated as a
stochastic convex optimization and a cooperative game, respectively. To tackle
the stochastic challenges posed by multiple random variables, we apply the
Monte Carlo sample average approximation (SAA) to the problems. To demonstrate
the practical applicability of these models, we implement the proposed
scenarios in the Jono neighborhood in Kitakyushu, Japan.Comment: Submitted to IET Renewable Power Generatio
Designing Collaborative Energy Communities: A European Overview
open5noEnergies is a peer-reviewed, open access journal of related scientific research, technology development, engineering, and the studies in policy and management and is published semimonthly online by MDPI.
Impact Factor: 3.004 (2020) ; 5-Year Impact Factor: 3.085 (2020).
Founded: 2008 (Volumes: 15)
This article belongs to the Special Issue Advanced Technologies in Smart Cities.
This research was funded by the H2020 project GRETA-Green Energy Transition Actions, grant number 101022317 and the EIT Climate-KIC project GECO- Green Energy COmmunity Project, grant number EIT 2.2.5 2002279Renewable energy has a crucial role in facing climate change. One promising strategy is the creation of energy communities that require active involvement from a bottom-up perspective. Their implementation is difficult, as they currently rely on local policies, community readiness, and technological availability. The objective of this paper is to provide a qualitative overview of energy community concepts and strategies at the European level. The aim is to identify common approaches that are framing the development of energy communities, and to understand the most successful steps leading to their creation and growth. To achieve this objective, a threefold methodology is provided: (1) an updated review on policies dealing with energy communities at the European and Italian level; (2) a qualitative overview of European-funded projects under the Horizon 2020 work program; and (3) a qualitative overview of some of the most successful existing energy communities in Europe. The results outline a series of considerations and lessons learned that are useful for implementing this transition pathway in a real case, which is also presented in the paper. The conclusions will identify some future directions of this research, particularly in relation to the results coming from the implementation of actions in the real case.openBoulanger S.O.M.; Massari M.; Longo D.; Turillazzi B.; Nucci C.A.Boulanger S.O.M.; Massari M.; Longo D.; Turillazzi B.; Nucci C.A
Fair Energy Allocation in Risk-aware Energy Communities
This work introduces a decentralized mechanism for the fair and efficient
allocation of limited renewable energy sources (RESs) among consumers in an
energy community. In the proposed non-cooperative game, the self-interested
community members independently decide whether to compete or not for access to
RESs during peak hours and shift their loads analogously. In the peak hours, a
proportional allocation policy is used to allocate the limited RESs among them.
The existence of a Nash equilibrium (NE) or dominant strategies in this
non-cooperative game is shown, and closed-form expressions of the renewable
energy demand and social cost are derived. Moreover, a decentralized algorithm
for choosing consumers' strategies that lie on NE states is designed. The work
shows that the risk attitude of the consumers can have a significant impact on
the deviation of the induced social cost from the optimal. Besides, the
proposed decentralized mechanism is shown to attain a much lower social cost
than one using the naive equal sharing policy
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 preocupación por la escasez de combustibles fósiles, sus costos
y su impacto en el medio ambiente ha llevado a las instituciones
gubernamentales a lanzar políticas energéticas que promuevan la creciente
instalación de tecnologías que utilizan fuentes de energía renovables para
generar energía. La creciente penetración de las fuentes de energía renovable trae
consigo una gran fluctuación en el lado de la generación, lo que afecta
fuertemente la gestión del sistema de potencia y energía. El control de este
sistema está pasando de un enfoque jerárquico y central a un enfoque inteligente
y distribuido. Actualmente, los operadores del sistema están comenzando a
considerar a los usuarios finales (consumidores y prosumidores) como parte de
la solución en las actividades de operación del sistema eléctrico. En este sentido,
los usuarios finales están cambiando su comportamiento de jugadores pasivos a
jugadores activos. El papel de los agregadores es esencial para empoderar a los
usuarios finales, contribuyendo también a esos cambios de comportamiento.
Aunque en varios países los agregadores están legalmente reconocidos como una
entidad del sistema eléctrico y energético, su papel se centra principalmente en
representar a los usuarios finales en la participación del mercado mayorista.
Este trabajo contribuye al avance del estado del arte con modelos que
permiten la participación activa de los usuarios finales en los mercados eléctricos
para convertirse en participantes clave en la gestión de los sistemas de potencia
y energía. Se espera que los agregadores desempeñen un papel esencial en estos
modelos, haciendo la conexión 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 desafíos que enfrentan los
agregadores.
Los principales resultados de este trabajo incluyen los modelos
desarrollados para permitir la participación de los consumidores y prosumidores
en los mercados eléctricos y la gestión de los sistemas de potencia y energía. Los
modelos de soporte de decisiones propuestos consideran aplicaciones de gestión
del lado de la demanda, modelos de mercado eléctrico local, gestión 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 validación 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 características de cada modelo y demostrar
cómo cada uno de ellos contribuye a responder las preguntas de investigación
definidas para este trabajo
Impact of local energy markets integration in power systems layer: A comprehensive review
In recent years extensive research has been conducted on the development of different models that enable energy trading between prosumers and consumers due to expected high integration of distributed energy resources. Some of the most researched mechanisms include Peer-to-Peer energy trading, Community Self-Consumption and Transactive Energy Models. To ensure the stable and reliable delivery of electricity as such markets and models grow, this paper aims to understand the impact of these models on grid infrastructure, including impacts on the control, operation, and planning of power systems, interaction between multiple market models and impact on transmission network. Here, we present a comprehensive review of existing research on impact of Local Energy Market integration in power systems layer. We detect and classify most common issues and benefits that the power grid can expect from integrating these models. We also present a detailed overview of methods that are used to integrate physical network constraints into the market mechanisms, their advantages, drawbacks, and scaling potential. In addition, we present different methods to calculate and allocate network tariffs and power losses. We find that financial energy transactions do not directly reflect the physical energy flows imposed by the constraints of the installed electrical infrastructure. In the end, we identify a number of different challenges and detect research gaps that need to be addressed in order to integrate Local Energy Market models into existing infrastructure
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