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In the power grid, the Balance Responsible Parties (BRPs) purchase energy based on a forecast of the user consumption. The forecasts are imperfect, and the corrections of their real-time deviations are managed by a System Operator (SO), which charges the BRPs for the procured imbalances. Flexible consumers, associated with a BRP, can be involved in a demand response (DR) program to reduce the imbalance costs. However, running the DR program requires the BRP to invest resources in the infrastructure and increases its operating costs. To limit the intervention of BRP, we implement the DR via a blockchain smart contract. Moreover, to reduce the delay of publication of the imbalance price, caused by the inefficient accounting process of the current balancing markets, a second blockchain is adopted at the SO layer, procuring a fast and auditable credit settlements. The feasibility of the proposed architecture is evaluated over an Ethereum blockchain platform. The results show that blockchains can enable a high automation of the balancing market, by providing (i) the implementation of aggregators with low operating cost and (ii) the timely and transparent access to the balancing information, thus fostering new business models for the BRPs.

In recent years, local energy markets (LEMs) have been introduced to empower end-customers within energy communities at the distribution level of the power system, in order to be able to trade their energy locally in a competitive and fair environment. However, there is still some challenge with regard to the most efficient approach in organising the LEMs for the electricity exchange between consumers and prosumers while ensuring that they are responsible for their electricity-related choices, and concerning which LEM model is suitable for which prosumer or consumer type. This paper presents a hierarchical model for the organisation of agent-based local energy markets. According to the proposed model, prosumers and consumers are enabled to transact electricity within the local energy community and with the grid in a coordinated manner to ensure technical and economic benefits for the LEM’s agents. The model is implemented in a software tool called Grid Singularity Exchange (GSyE), and it is verified in a real German energy community case study. The simulation results demonstrate that trading electricity within the LEM offers economic and technical benefits compared to transacting with the up-stream grid. This can further lead to the decarbonization of the power system sector. Furthermore, we propose two models for LEMs consisting of multi-layer and single-layer hierarchical agent-based structures. According to our study, the multi-layer hierarchical model is more profitable for household prosumers as compared to trading within the single-layer hierarchical LEM. However, the single-layer LEM is more be beneficial for industrial prosumers.

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