دانلود رایگان مقاله انگلیسی بهره برداری از هوش تجاری در شبکه های هوشمند: مورد بازار برق - الزویر 2018

ABSTRACT

This paper discusses analytical aspects of smart grids and offers insights into the development of a business intelligence solution for the electricity market. The goal is to design a system that provides an emerging electricity market with the necessary data flows and information for forecasting, data analysis and decision making, leading to better business results and more control over the market. By employing a methodology specifically suited to the electricity market domain, we designed a business intelligence solution for the Serbian electricity market operator “Elektromreža Srbije”. The research results show that the proposed approach leads to more effective market management in data-rich smart grid environments, while still being dynamic enough to adapt to frequent rule changes in the still developing grids and their markets.

5. Discussion and conclusions

The future of the energy industry is synonymous with smart grid technologies and their applications, with the end goal being the construction of a platform suited for new business models, the so-called “Energy Internet” [44,45]. For this to become a reality, the electricity companies will have to modernize and accept new paradigms if they wish to become adaptive to end users' needs and operate in competitive and deregulated markets [46,47].

Various reports have shown that the existing information systems are struggling to meet the current needs of participants in the energy industry. The challenge of improving operational and managerial capacity implies the need for an integrated business intelligence platform designed for KPI management, analysis and forecasts. Business intelligence can be effectively used to integrate large data volumes and support a variety of difficult and challenging energy market issues, such as prediction, load optimization, pattern recognition and others. In this complex scenario, selecting a BI approach is an important decision, and this paper offers one such approach that has proven to be adequate for the Serbian market.

The main contribution of the paper is the approach to designing a BI system that provides the emerging electricity market with the necessary data flows and information for forecasting, data analysis and decision making. As such, this approach may be adequate for countries whose electricity market is in the process of development.