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

Smart grids for rural conditions and e-mobility - Applying power routers, batteries and virtual power plants

Significant reductions of greenhouse gas emission by use of renewable energy sources belong to the common targets of the European Union. Smart grids address intelligent use and integration of conventional and renewable generation in combination with controllable loads and storages. Two special aspects have also to be considered for smart grids in future: rural conditions and electric vehicles. Both, the increasing share of renewable energy sources and a rising demand for charging power by electrical vehicles lead to new challenges of network stability (congestion, voltage deviation), especially in rural distribution grids. This paper describes two lighthouse projects in Europe (“Well2Wheel” and “Smart Rural Grid”) dealing with these topics. The link between these projects is the implementation of the same virtual power plant technology and the approach of cellular grid cells. Starting with an approach for the average energy balance in 15 minutes intervals in several grid cells in the first project, the second project even allows the islanded operation of such cells as a microgrid. The integration of renewable energy sources into distribution grids primary takes place in rural areas. The lighthouse project “Smart Rural Grid”, which is founded by the European Union, demonstrates possibilities to use the existing distribution system operator infrastructure more effectively by applying an optimised and scheduled operation of the assets and using intelligent distribution power routers, called IDPR. IDPR are active power electronic devices operating at low voltage in distribution grids aiming to reduce losses due to unbalanced loads and enabling active voltage and reactive power control. This allows a higher penetration of renewable energy sources in existing grids without investing in new lines and transformers. Integrated in a virtual power plant and combined with batteries, the IDPR also allows a temporary islanded mode of grid cells. Both projects show the potential of avoiding or postponing investments in new primary infrastructure like cables, transformers and lines by using a forward-looking operation which controls generators, loads and batteries (mobile and stationary) by using new grid assets like power routers. While primary driven by physical restrictions as voltage-band violations and energy balance, these cells also define and allow local smart markets. In consequence the distribution system operators could avoid direct control access by giving an incentive to the asset owners by local price signals according to the grid situation and forecasted congestions.Peer ReviewedPostprint (published version

Exploring smart grid possibilities: a complex systems modelling approach

Smart grid research has tended to be compartmentalised, with notable contributions from economics, electrical engineering and science and technology studies. However, there is an acknowledged and growing need for an integrated systems approach to the evaluation of smart grid initiatives. The capacity to simulate and explore smart grid possibilities on various scales is key to such an integrated approach but existing models – even if multidisciplinary – tend to have a limited focus. This paper describes an innovative and flexible framework that has been developed to facilitate the simulation of various smart grid scenarios and the interconnected social, technical and economic networks from a complex systems perspective. The architecture is described and related to realised examples of its use, both to model the electricity system as it is today and to model futures that have been envisioned in the literature. Potential future applications of the framework are explored, along with its utility as an analytic and decision support tool for smart grid stakeholders

Analysing long-term interactions between demand response and different electricity markets using a stochastic market equilibrium model. ESRI WP585, February 2018

Power systems based on renewable energy sources (RES) are characterised by increasingly distributed, volatile and uncertain supply leading to growing requirements for flexibility. In this paper, we explore the role of demand response (DR) as a source of flexibility that is considered to become increasingly important in future. The majority of research in this context has focussed on the operation of power systems in energy only markets, mostly using deterministic optimisation models. In contrast, we explore the impact of DR on generator investments and profits from different markets, on costs for different consumers from different markets, and on CO2 emissions under consideration of the uncertainties associated with the RES generation. We also analyse the effect of the presence of a feed-in premium (FIP) for RES generation on these impacts. We therefore develop a novel stochastic mixed complementarity model in this paper that considers both operational and investment decisions, that considers interactions between an energy market, a capacity market and a feed-in premium and that takes into account the stochasticity of electricity generation by RES. We use a Benders decomposition algorithm to reduce the computational expenses of the model and apply the model to a case study based on the future Irish power system. We find that DR particularly increases renewable generator profits. While DR may reduce consumer costs from the energy market, these savings may be (over)compensated by increasing costs from the capacity market and the feed-in premium. This result highlights the importance of considering such interactions between different markets

Identifying prosumer’s energy sharing behaviours for forming optimal prosumer-communities

Smart Grid (SG) achieves bidirectional energy and information flow between the energy user and the utility grid, allowing energy users not only to consume energy, but also to generate the energy and share with the utility grid or with other energy consumers. This type of energy user who consumes energy and who also can generate the energy is called the “prosumer”. The sustainability of the SG energy sharing process heavily depends on its participating prosumers, making prosumer participation and management schemes crucial within the energy sharing approaches. The contribution of this article is twofold. First, this article introduces a novel concept of participating and managing the prosumers in the SG energy sharing process in the form of virtual communities, which involves with computation, software, data access, and storage services that do not need end-prosumer knowledge of the physical location and system configuration. Here, the community of prosumers can collectively increase the amount of power to be auctioned or bought offering higher bargaining power, thereby settling for a higher price per kilowatt in long-term. The initial step to build an effective prosumer-community is the identification of those prosumers who would be suitable to make efficient prosumer communities. This leads the necessity of identifying parameters that influence the energy sharing behaviours of prosumers. The second contribution of this article is that, this comprehensively analyses the different parameters influencing the prosumer’s energy sharing behaviours and thus presents multi-agent architecture for optimal prosumer-community formation

Modeliranje prožnosti končnih odjemalcev v okviru energetske skupnosti

The integration of renewable energy sources (RES) is an important step in the transition to a more sustainable energy system. With the development of EU energy policy, the role of the consumer is more active and recognized as a central role in this transition. One of the concepts that we have investigated is the organisation of consumers and prosumers in energy communities. This master\u27s thesis deals with approaches to modelling the concept of energy communities, where we chose the prosumer/consumer pair as a baseline model. With different scenarios, we analyzed how the flexibility of energy community members affects the increase of self-consumption of the energy community. Agent-based modelling represents an established approach to modelling socio-technical systems such as energy communities. The proposed models are implemented in the AnyLogic environment. By changing their flexibility and the availability of the energy storage system, we explored the possibilities for increasing the self-consumption of the energy community. With the acquired knowledge, we upgraded the baseline model into a smaller energy community aiming to achieve 100% self-consumption.Vključevanje obnovljivih virov energije (OVE) je pomemben korak pri prehodu na bolj trajnosten energetski sistem. Z razvojem energetske politike EU je vloga klasičnega odjemalca aktivnejša in prepoznana kot osrednja vloga v tem prehodu. Eden od konceptov, ki smo mu sledili je, da se klasični in aktivni odjemalci organizirajo v energetske skupnosti. Magistrsko delo obravnava pristope k modeliranju koncepta energetskih skupnosti, kjer smo za izhodišče izbrali par aktivni/klasični odjemalec. Z različnimi scenariji smo analizirali, kako prožnost odjema odjemalcev vpliva na povečanje lastne porabe energetske skupnosti. Agentno modeliranje predstavlja uveljavljen pristop za modeliranje družbeno-tehničnih sistemov, kot so energetske skupnosti. Predlagani modeli so implementirani v okolju AnyLogic. S spreminjanjem njihove prožnosti odjema in razpoložljivosti hranilnika električne energije smo raziskali možnosti za povečanje lastne porabe energetske skupnosti. Z pridobljenim znanjem smo izhodiščni model nadgradili v manjšo energetsko skupnost s ciljem doseči sto odstotno lastno porabo zelene energije