The Impact of Smart Grid Prosumer Grouping on Forecasting Accuracy and Its Benefits for Local Electricity Market Trading

A scaling law for short term load forecasting on varying levels of aggregation

“…This work aggregates up to 782 homes. In [28] the authors show that mean absolute percentage error decreases with the number of customers and use it for examining electricity market trading performance. In [29] the authors show that clustering can help improve the forecast accuracy, which follows the ideas proposed in this work.…”

“…Here we investigate the effect of aggregation in a linear scale and small sample sizes to show how the proposed model deviates from common understanding of aggregation smoothing. For example, analysis of 2000 customers was presented in [25] and with 200 customers in [28]. Such limited group sizes are unable to identify the various regimes present in the scaling law, thus an incomplete understanding.…”

Business Models in the Smart Grid: Challenges, Opportunities and Proposals for Prosumer Profitability

“…Da Silva et al [7] offer their own work dealing with grouping prosumers for forecasting services, which somewhat resembles the previously described proposal. However, the authors stress in this work the importance of performing accurate forecasts for local electricity markets, or rather, energy communities, as a way to offer a service that could become the cornerstone of a business model about energy consumption forecasting.…”

Smart Agents in Industrial Cyber–Physical Systems

“…The NOBEL project created a cloud-based platform offering energy services including a market where energy could be traded by agents representing their users [62,63]. The E2SG project was developed a decentralized and embedded agent oriented architecture for the optimization and management of intelligent buildings [64], and an asynchronous leaderless MAS-based approach that coordinates the reactive power outputs of a set of power capacitors [65].…”