The infrastructure required for collecting and distributing open data plays a vital role in the digital economy, serving as a valuable resource for fostering innovation through big data processing and artificial intelligence technologies. Unfortunately, several sectors, including the energy industry, lack a well-established ecosystem for implementing such innovations effectively. This paper addresses key challenges associated with the aggregation and utilization of open data in the electric power sector, while exploring potential solutions. Additionally, the paper provides a concise analysis of existing literature on organizing open data in the energy industry and examines the architectural aspects of foreign open data platforms designed for the electric power sector. The paper highlights the considerable focus on open data collection, storage, and provision, as well as the active resolution of both technical and regulatory issues in foreign contexts. Sources of open data in the Russian electric power industry and challenges associated with extracting data from heterogeneous sources are enumerated. The ecosystem approach to organizing an open data platform and the basic data monetization principles are discussed. The paper presents the key stakeholders of the platform and outlines the mechanisms for motivating their involvement. A platform architecture is proposed to meet the needs of stakeholders and ensure accelerated development of innovations in the energy sector. The use of a data lakehouse is recommended for efficient data storage in the platform. An example application on the basis of the open data platform is presented that forecasts peak load hours in regional power systems using machine learning. This application can be integrated into consumer energy management systems. Proposals are stated to refine the organizational and information support of open data of the electric power industry in order to increase the efficiency of their collection, storage, and processing on the basis of the digital platform.