Unlocking Local Energy Markets

This is the final version. Freely available from University of Exeter Energy Policy Group via the link in this recordEuropean Regional Development FundCentric

Sharing Economy in Local Energy Markets

With an increase in the electrification of end-use sectors, various resources on the demand side provide great flexibility potential for system operation, which also leads to problems such as the strong randomness of power consumption behavior, the low utilization rate of flexible resources, and difficulties in cost recovery. With the core idea of 'access over ownership', the concept of the sharing economy has gained substantial popularity in the local energy market in recent years. Thus, we provide an overview of the potential market design for the sharing economy in local energy markets (LEMs) and conduct a detailed review of research related to local energy sharing, enabling technologies, and potential practices. This paper can provide a useful reference and insights for the activation of demand-side flexibility potential. Hopefully, this paper can also provide novel insights into the development and further integration of the sharing economy in LEMs.</p

Reinforcement learning in local energy markets

Local energy markets (LEMs) are well suited to address the challenges of the European energy transition movement. They incite investments in renewable energy sources (RES), can improve the integration of RES into the energy system, and empower local communities. However, as electricity is a low involvement good, residential households have neither the expertise nor do they want to put in the time and effort to trade themselves on their own on short-term LEMs. Thus, machine learning algorithms are proposed to take over the bidding for households under realistic market information. We simulate a LEM on a 15 min merit-order market mechanism and deploy reinforcement learning as strategic learning for the agents. In a multi-agent simulation of 100 households including PV, micro-cogeneration, and demand shifting appliances, we show how participants in a LEM can achieve a self-sufficiency of up to 30% with trading and 41,4% with trading and demand response (DR) through an installation of only 5kWp PV panels in 45% of the households under affordable energy prices. A sensitivity analysis shows how the results differ according to the share of renewable generation and degree of demand flexibility

Forecasting in Blockchain-Based Local Energy Markets

Increasingly volatile and distributed energy production challenges traditional mechanisms to manage grid loads and price energy. Local energy markets (LEMs) may be a response to those challenges as they can balance energy production and consumption locally and may lower energy costs for consumers. Blockchain-based LEMs provide a decentralized market to local energy consumer and prosumers. They implement a market mechanism in the form of a smart contract without the need for a central authority coordinating the market. Recently proposed blockchain-based LEMs use auction designs to match future demand and supply. Thus, such blockchain-based LEMs rely on accurate short-term forecasts of individual households’ energy consumption and production. Often, such accurate forecasts are simply assumed to be given. The present research tested this assumption by first evaluating the forecast accuracy achievable with state-of-the-art energy forecasting techniques for individual households and then, assessing the effect of prediction errors on market outcomes in three different supply scenarios. The evaluation showed that, although a LASSO regression model is capable of achieving reasonably low forecasting errors, the costly settlement of prediction errors can offset and even surpass the savings brought to consumers by a blockchain-based LEM. This shows that, due to prediction errors, participation in LEMs may be uneconomical for consumers, and thus, has to be taken into consideration for pricing mechanisms in blockchain-based LEMs.Peer Reviewe

Local energy markets - an IT-architecture design

In recent years, local energy markets have become an important concept in more decentralized energy systems. Implementations in pilot projects provide first insights into different hypotheses and approaches. From a technical perspective, the requirements for the IT infrastructure of a local energy market are diverse, and a holistic view of its architecture is therefore necessary. This article presents an IT-architecture, which enables all basic local energy market functionalities, processes and modules based on the available literature. The proposed IT-architecture can serve as a blueprint for future local market projects as it covers the basic processes and is at the same time extendable. Furthermore, we give a detailed description of a real-world implementation of a local energy market using the described IT-architecture and discuss the advantages and disadvantages of the utilized technologies along with this case study

A Multi-Agent System Simulation Model for Trusted Local Energy Markets

The energy market and electric grid play a major role in everyday life. Most areas in modern society, such as: communication, health, transportation, the financial system and many others; require electrical energy to operate properly. Traditionally energy grids operate in a centralized manner. Consumers are connected to centralized utilities in the grid and energy flows from producers to Consumers. However, the rising in popularity in Renewable Energy Sources (RES) such as photovoltaic panels installed in households, small commerce and small industry wide spread the use of distributed energy generation, which the main energy grid was not designed to support. One of the possible solutions for this problem is the creation of a Local Energy Market (LeM). A LeM is a market that operates in a small physical area such as a neighborhood. Traditional consumers can become active market participants under a LeM. That is possible because the LeM is structured in such a way as to enable small-scale negotiations and energy exchanges between participants, who traditionally would only be final consumers. The LeM is capable of dealing with distributed energy generation from RES because negotiations and distribution happen at a local level, thus reducing problems with the main grid. Furthermore, the participation in the local market can reduce energy costs or even create profits for consumers, while contributing to easy the management of the grid and associated technical losses. This work explores the concept of LeM and is focused on two main objectives: designing and developing a system that allows the simulation of LeM, and designing and developing a mechanism that allows trusted negotiations in this market. To accomplish these objectives a Multi-Agent System (MAS) architecture is proposed to model and allow the simulation of LeM. Furthermore to support the market it is also proposed a trust model used to evaluate the behavior of participants and detecting faulty or malicious activities. The developed MAS models a LeM based on a Smart Grid, that is an energy grid with a cyber-physical system with smart meters and communications mechanisms. The MAS was developed with agents to model sensors, market participants and a Market Interaction Manager (MIM) agent that is responsible for managing the negotiations and for applying trust mechanisms. The trust mechanism was designed to attribute a dynamic trust value to each participant, which is reviewed during the all negotiation period. This evaluation of the participant’s trust is based on the analysis of historical data, contextual data, such as weather conditions, and by using forecasting methods to predict the participant expected behavior, allowing to penalize the ones that are exhibiting a questionable behavior in the market. A case study simulation was made with the objective of understanding how the proposed trust mechanism performed, and how the use of different forecasting methods can interfere with it. The results obtained allowed us to conclude that the trust methodology is able to update the trust of each participant, during the negotiation period, and when paired with a well performing forecasting mechanism it is able to achieve a trusted evaluation of the participants behavior. Taking into consideration these results we believe that the proposed trust methodology is capable of providing a valuable trust assessment when used by the MIM agent. This Master Thesis is developed within the scope of a project called Secure interactions and trusted Participation in local Electricity Trading (SPET), a FCT-SAICT2017 funded Research & Development project. SPET project envisions the development of a MAS that is designed to model and simulate the operations of a LeM, taking a focus on security and market trust necessary in this negotiation environment.O mercado de energia e a rede elétrica desempenham um papel importante na vida quotidiana da população. Grande parte das áreas da sociedade moderna, como é o caso da comunicação, transportes, saúde, sistema financeiro, entre outras; requer energia elétrica para funcionar corretamente. Tradicionalmente, as redes de energia operam de forma centralizada. Os consumidores estão conectados a fornecedores centralizados na rede e a energia é transferida dos produtores para os consumidores. No entanto, o aumento da popularidade das Fontes de Energia Renováveis (FER), como painéis fotovoltaicos instalados nas residências, pequeno comércio e pequena indústria, difundiu o uso da geração distribuída de energia, que a rede principal de energia não foi projetada para suportar. Uma das possíveis soluções para esse problema é a criação de um Mercado Local de Energia (MLe). Um MLe é um mercado que opera numa pequena área física, como uma vizinhança. Num MLe, os consumidores tradicionais têm a possibilidade de ser participantes ativos no mercado. Isto é possível porque o MLe está estruturado de forma a permitir negociações em pequena escala e trocas de energia entre os participantes, que tradicionalmente seriam apenas consumidores finais. O MLe é capaz de lidar com a geração de energia distribuída proveniente das FER, porque as negociações e a distribuição ocorrem a um nível local, reduzindo assim os problemas com a rede principal. Para além disso, a participação no mercado local pode reduzir os custos de energia ou até gerar lucros para os consumidores, contribuindo ainda para facilitar a gestão da rede e reduzir as perdas técnicas a ela associadas. Este trabalho explora o conceito de MLe e está focado em dois objetivos principais: projetar e desenvolver um sistema que permita a simulação de MLe, bem como um mecanismo que permita negociações confiáveis neste mercado. Para atingir estes objetivos, é proposta uma arquitetura de Sistema Multi-Agente (SMA) para modelar e permitir a simulação do MLe. Para além disso, para apoiar o mercado, também é proposto um modelo de confiança utilizado para avaliar o comportamento dos participantes e detetar falhas ou atividades maliciosas. O SMA desenvolvido modela um MLe com base numa Smart Grid, que é uma rede de energia com um sistema ciber-físico, com sensores inteligentes e mecanismos de comunicação. O SMA foi desenvolvido com agentes para modelar sensores, participantes do mercado e um agente Market Interaction Manager (MIM), responsável pela gestão das negociações e pela aplicação de mecanismos de confiança. O mecanismo de confiança foi projetado para atribuir um valor de confiança dinâmico a cada participante, que é adaptado durante todo o período de negociação. Essa avaliação da confiança do participante é baseada na análise de dados históricos, contextuais, como condições climatéricas, e no uso de métodos de previsão para antever o comportamento esperado do participante, permitindo penalizar aqueles que exibem um comportamento questionável no mercado. Foi realizada uma simulação de caso de estudo, com o objetivo de avaliar o desempenho do mecanismo de confiança proposto e de que forma é que o uso de diferentes métodos de previsão interfere neste desempenho. Os resultados obtidos permitiram concluir que a metodologia de confiança é capaz de atualizar a confiança de cada participante, durante o período de negociação e, quando combinada com um mecanismo de previsão com bom desempenho, é capaz de obter uma avaliação confiável do comportamento dos participantes. Tendo em consideração estes resultados, acreditamos que a metodologia de confiança proposta é capaz de fornecer uma avaliação de confiança valiosa quando usada pelo agente MIM. Esta tese de mestrado é desenvolvida no âmbito de um projeto chamado Secure interactions and trusted Participation in local Electricity Trading (SPET), um projeto de Investigação e Desenvolvimento (I&D) financiado pela FCT-SAICT2017. O projeto SPET tem como objetivo o desenvolvimento de um MAS para a modelação e simulação de MLe, tendo como foco a segurança e confiança necessárias neste ambiente de negociação

Local Energy Markets: Paving the Path Towards Fully Transactive Energy Systems

Triggered by the increased fluctuations of renewable energy sources, the European Commission stated the need for integrated short-term energy markets (e.g., intraday), and recognized the facilitating role that local energy communities could play. In particular, microgrids and energy communities are expected to play a crucial part in guaranteeing the balance between generation and consumption on a local level. Local energy markets empower small players and provide a stepping stone towards fully transactive energy systems. In this paper we evaluate such a fully integrated transactive system by (1) modelling the energy resource management problem of a microgrid under uncertainty considering flexible loads and market participation (solved via two-stage stochastic programming), (2) modelling a wholesale market and a local market, and (3) coupling these elements into an integrated transactive energy simulation. Results under a realistic case study (varying prices and competitiveness of local markets) show the effectiveness of the transactive system resulting in a reduction of up to 75/% of the expected costs when local markets and flexibility are considered. This illustrates how local markets can facilitate the trade of energy, thereby increasing the tolerable penetration of renewable resources and facilitating the energy transition

Policy and regulatory barriers to local energy markets in Great Britain

EPG Working Paper: EPG 1801The requirement to decarbonise the GB electricity system, alongside the falling costs of renewable technologies and developments in IT capabilities, provides GB with an opportunity for systemic change in the way that electricity is produced and sold, with the potential to enable flexibility markets at the local level given the correct regulatory conditions. The report highlights a range of regulatory and policy barriers to the Local Energy Market (LEM) approach

Zone-Based Privacy-Preserving Billing for Local Energy Market Based on Multiparty Computation

This paper proposes a zone-based privacy-preserving billing protocol for local energy markets that takes into account energy volume deviations of market participants from their bids. Our protocol incorporates participants' locations on the grid for splitting the deviations cost. The proposed billing model employs multiparty computation so that the accurate calculation of individual bills is performed in a decentralised and privacy-preserving manner. We also present a security analysis as well as performance evaluations for different security settings. The results show superiority of the honest-majority model to the dishonest majority in terms of computational efficiency. They also show that the billing can be executed for 5000 users in less than nine seconds in the online phase for all security settings, demonstrating its feasibility to be deployed in real local energy markets