• Energy Research

This paper addresses the challenges of integrating existing PHEV charging algorithms, which optimize PHEV charging per market timeslot (e.g., 15 minutes), into an environment with realistic communication conditions. To address this challenge, we propose a dual coordination mechanism, which controls a cluster of devices on two different operation levels: market operation and real-time operation. The market operation level uses an existing timeslot-based algorithm to calculate a charging schedule per timeslot. The real-time operation level translates this schedule into event-based control actions for a realistic communication environment, wherein a limited number of messages can be exchanged. A case study of 1000 PHEVs shows that it is possible to achieve results on par with the timeslot based algorithm but with significantly reduced communication with the PHEVs.

The integration of variable renewable energy resources result in an increased need for operational flexibility. Energy storage is one of the alternatives to conventional generation technologies to provide this flexibility. A generic model for energy storage is introduced into a generation expansion planning model, considering operational constraints of power plants and system balancing requirements. Different targets for the final renewable electricity generation towards the future are imposed, quantifying the need for electricity storage and the impact on the electricity generation mix. When facing high renewable targets, storage is found to reduce the need for installed generation capacity, both conventional and renewable, and reduce the electricity generation costs.

This article presents a Generation Expansion Model of the power system taking into account the operational constraints and the uncertainty of long-term electricity demand projections. The model is based on a discretization of the load duration curve and explicitly considers that power plant ramping capabilities must meet demand variations. A model predictive control method is used to improve the long-term planning decisions while considering the uncertainty of demand projections. The model presented in this paper allows integrating technical constraints and uncertainty in the simulations, improving the accuracy of the results, while maintaining feasible computational time. Results are tested over three scenarios based on load data of an energy retailer in Colombia.

This article introduces new roles in future peer-to-peer electricity trading markets. Following a qualitative approach, firstly, the value network of the current electricity market is presented. To do so, service streams, critical roles, activities, and their setting in the electricity market are identified. Secondly, in order to identify the main sources of uncertainty, the business model matrix framework is utilized to analyze peer-to-peer electricity trading. Thirdly, four future scenarios are built based on user involvement and customer ownership. The outcome of the scenario building is the emergence of new roles, brokers, and representatives in the future peer-to-peer electricity markets. Fourth, based on the four future scenarios, changes in the value network, new roles, and emerging/evolving activities are identified. Finally, the two new roles are discussed from grid structure, security and privacy, legal, and data protection perspectives. The data is gathered by conducting semi-structured interviews with stakeholders in the current electricity market as well as potential disruptors. This article elaborates on the configuration of the value network in the electricity market and highlights the changes that peer-to-peer trading imposes to the status quo. Through the outcomes of the value network analysis, it assists policy makers to consider the requirements and current market players to reconsider their business models.

This article addresses the suitable approaches for empowering energy citizens and smart energy communities through the development of community-based microgrid (C-MG) solutions while taking into consideration the functional architectural layers and system integration topologies, interoperability issues, strategies for consumer-centric energy trading under the local electricity market (LEM) mechanism, and socio-economic aspects. Thus, this article presents state-of-the-art microgrid solutions for the smart energy community along with their motivation, advantages and challenges, comprehensibly contrasted between the recommended generic architecture and every other reported structure. The notion of LEM for peer-to-peer (P2P) energy exchange inside a transactive energy system based on a flexible consumer-centric and bottom-up perspective towards the participation in the wholesale electricity market (WEM) is also reviewed and critically explored. Furthermore, the article reviews the interoperability issues in relation to the development of C-MG including energy trading facilities. The article’s overall contribution is that it paves the path for advanced research and industrialisation in the field of smart energy communities through the analytical recommendations of the C-MG architecture and DER (distributed energy resource) integration structure, considering the future trend of local energy markets and socio-economic aspects.

Electricity generation is decentralising quickly. Simultaneously, final energy use for residential customers electrifies in order to reduce carbon dioxide emissions. Together with ubiquitous digitalisation, this decentralisation and flexibility at the demand side paves the way towards local energy communities and – in its most distributed version – to peer-to-peer energy trading, where customers buy and sell electricity among each other. Although peer-to-peer energy trading is not yet legal everywhere, ‘citizen energy communities’ have been introduced as cornerstones of the energy transition by the European Commission in their ‘Clean Energy for All Europeans’ programme. This paper firstly discusses this digitalisation and decentralisation of the power infrastructure. These trends are supported by distributed information technologies, including peer-to-peer control paradigms. Distributed ledger technologies, such as blockchains, might be one such piece of the puzzle. The second part of the paper investigates whether blockchain technologies, and their associated smart contracts, offer advantages for larger-scale peer-to-peer energy-trading applications over a classic, centralised approach. Different blockchain implementations are investigated and qualitatively evaluated from a scalability, efficiency and trust perspective. The conclusion indicates that in the current state of the art, a trade-off between decentralised and more classical (hierarchically centralised) solutions suits larger-scale peer-to-peer energy-trading applications best.