The book examines the problems in the fields of power systems functioning, optimization of operating modes of electric power facilities and their control systems, information and measuring systems and metrological support in the electric power industry, ensuring the functioning of the electric power system in the conditions of a competitive market of the electric power. The book is devoted to modern problems ensuring operational reliability and safety of objects integrated power system of Ukraine in the areas such as distribution systems automation, forecasting and optimization of energy processes with solar power plants, hydropower plants and other plants, and development solutions for smart monitoring systems for DERs. The presented research results in the book allow to increase the reliability and efficiency of operation of energy facilities and ensure the stability of power systems, the introduction of effective methods and tools for forecasting electricity supply and optimize power systems taking into constraints in modern of electricity markets. The book consists of 14 chapters. The book is for researchers, engineers, as well as lecturers and postgraduates of higher education institutions dealing with problems of operation, control, diagnosis and monitoring of integrated power system, power equipment, and other.

This book covers new technologies and methods related to models for short-term forecasting of electricity imbalances in the IPS of Ukraine, taking into account the impact of forecasts of energy production from renewable sources on the accuracy of the imbalance forecast. The book proposed architecture and mathematical model of an artificial neural network for deep learning forecasting of short-term electricity imbalances using hourly data. Using a model to aggregate data with an hourly resolution followed by forecasting to reduce forecast error, the quasi-dynamic modeling method was used to analyze the impact of periodic generation on the network. The application of quasi-dynamic modeling also allows taking into account the system load curve, generation profile, storage system, as well as renewable energy sources (RES) operation in this area. The use of models makes it possible to achieve realistic estimates of generation for the required period. The book considers a local hybrid renewable energy system (HRES) based on different types of RES, which is more efficient than a system with one type of source.

The book examines the problems in the fields of power systems functioning, optimization of operating modes of electric power facilities and their control systems, information and measuring systems and metrological support in the electric power industry, ensuring the functioning of the electric power system in the conditions of a competitive market of the electric power. The book is devoted to modern problems ensuring operational reliability and safety of objects integrated power system of Ukraine in the areas such as distribution systems automation, forecasting and optimization of energy processes with solar power plants, hydropower plants and other plants, and development solutions for smart monitoring systems for DERs. The presented research results in the book allow to increase the reliability and efficiency of operation of energy facilities and ensure the stability of power systems, the introduction of effective methods and tools for forecasting electricity supply and optimize power systems taking into constraints in modern of electricity markets. The book consists of 14 chapters. The book is for researchers, engineers, as well as lecturers and postgraduates of higher education institutions dealing with problems of operation, control, diagnosis and monitoring of integrated power system, power equipment, and other.

This book covers new technologies and methods related to models for short-term forecasting of electricity imbalances in the IPS of Ukraine, taking into account the impact of forecasts of energy production from renewable sources on the accuracy of the imbalance forecast. The book proposed architecture and mathematical model of an artificial neural network for deep learning forecasting of short-term electricity imbalances using hourly data. Using a model to aggregate data with an hourly resolution followed by forecasting to reduce forecast error, the quasi-dynamic modeling method was used to analyze the impact of periodic generation on the network. The application of quasi-dynamic modeling also allows taking into account the system load curve, generation profile, storage system, as well as renewable energy sources (RES) operation in this area. The use of models makes it possible to achieve realistic estimates of generation for the required period. The book considers a local hybrid renewable energy system (HRES) based on different types of RES, which is more efficient than a system with one type of source.