Inteligentní řízení hybridní fotovoltaické elektrárny

Abstract

This thesis deals with the design and implementation of an intelligent control system (EMS) for hybrid photovoltaic power plants with the aim of optimizing operational efficiency and protecting the battery storage system. The computational core is an ESP32 microcontroller, which communicates via the Modbus TCP protocol with a GoodWe ET G2 asymmetric inverter. The system’s predictive layer combines adaptive consumption estimation using an exponential moving average (EMA), weather forecasts, and active control based on spot electricity prices for energy arbitrage. To protect the batteries from detrimental microcycling, the calculation of levelized cost of storage (LCOS) is integrated. The work also addresses the smooth feeding of solar surpluses into the boiler using synchronous Sigma-Delta modulation, which effectively minimizes billing inaccuracies on digital electricity meters. The solution includes a cloud-based backend for aggregating data from external APIs and a local web user interface for analytics and parameter configuration.