Abstract
The relevance of this study is due to the importance of assessing the prospective dynamics and structure of demand for energy carriers when developing and making strategic decisions in the field of energy and economic security of the country and its regions. The advance of digital technology redefines the properties of electric power supply systems, erases the boundary between electric power producers and consumers, and impacts the formation of electricity price and demand in the region. This study presents a method of electricity costing in the regional power system, which serves as an integral part of the approach to assessing the impact of intelligent systems development on the demand for electricity in the region. The approach is unique in that it simulates the behavior of electricity consumers and producers of various types as they pursue their own interests and assesses the impact of this behavior on the demand and price of electricity in the regional power system. Determining the cost of electricity in the system is based on the consistent alignment of the required amount of electricity consumption with the capabilities of producers seeking to achieve their best economic performance. Each producer is described as an optimization model, which is a standalone agent in a multi-agent power system model.
Highlights
Studying and projecting the prospective dynamics of volumes and changes in the structure with respect to demand for fuel and energy resources (FER) is one of the most important tasks when developing and making strategic-level decisions in the area of energy and economic security of the country and its regions and the policy aimed at improving the quality of life
One should have an overall idea of the dynamics and structure of the demand for energy carriers when developing directions for efficient development of the energy sector of the country and its regions, ensuring reliability of energy supply to the individual geographical areas, and developing long-term programs of activities of energy companies, etc
Attempts to overcome these difficulties have led to the development of quite a large number of approaches, methods and models for projecting estimates of demand for fuel and energy both in our country and abroad. These are heuristic methods based on the knowledge and experience of professionals active in this field, extrapolation methods, methods based on long-term trends and patterns in changes in energy consumption and basic macroeconomic indicators of development of different countries, and building of a variety of models. Such models are used both for solving standalone problems of projecting demand for fuel and energy resources and for serving as a part of model systems employed to determine directions of energy industry development [11,12,13,14]
Summary
Studying and projecting the prospective dynamics of volumes and changes in the structure with respect to demand for fuel and energy resources (FER) is one of the most important tasks when developing and making strategic-level decisions in the area of energy and economic security of the country and its regions and the policy aimed at improving the quality of life. Attempts to overcome these difficulties have led to the development of quite a large number of approaches, methods and models for projecting estimates of demand for fuel and energy both in our country and abroad These are heuristic methods (expert judgment, brainstorming, the Delphi method, etc.) based on the knowledge and experience of professionals active in this field (see, e.g., [1, 2]), extrapolation methods, methods based on long-term trends and patterns in changes in energy consumption and basic macroeconomic indicators of development of different countries (see, e.g., [3,4,5,6]), and building of a variety of models (simulation, optimization, and input-output models) (see, for example, [7,8,9,10]).
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