Energy and Power Industry has witnessed global investments in the technology to empower control mechanisms and monitoring systems. With millions of euros and dollars being traded in the sector every day, it is critical to determine the future demand for power as far as possible, both on an hourly and seasonal basis. It is only due to the Optimization techniques in Energy Analytics that accurate estimates can be made for each hour, day, month, and year of load levels. This results into utility companies making significant economies in building fuel inventory management, maintenance scheduling, and operating reserve.
Major utility suppliers depend on accurate forecasts generated a few days in advance. The manual process of projecting load is carefully studied using rich data stored for tens of years. A robust statistical model is manually built using principles of operations research and decisions analysis which suggests both periodicity and base load levels. The periodicity in Electric load occurs at three levels of frequencies – diurnal, weekly, and seasonal. Effects of holidays and big public events are modelled separately and the variations are incorporated as offset into the diurnal output. Regression models are built using climate data continuously generated and hourly updated on factors such as humidity, temperature, and wind speed. The effects of these parameters on load are determined to yield a performance which is unmatched to that of the trained human forecasters only allowing seconds to generate energy forecasts that would take hours otherwise.
Smart meters present unprecedented opportunities to push the boundaries of grid visibility beyond substations and transformers and into the home. The potential benefits of advanced metering infrastructure (AMI) go well beyond automating the meter-to-cash business process. It is now possible to view and analyse consumption data in new ways for a plethora of business applications, including capacity planning, demand management, rate design and reducing peak power consumption. Organizations seeking to attain maximum benefits from AMI need data analytics strategy solutions. The starting point is to understand the range of business applications enabled and enhanced by AMI data. Once these opportunities are identified, planners can determine which ones make the most business sense to pursue, the supporting data requirements, and the analytical processes needed to turn raw data into actionable information for improved decision-making.
Establishing a strategic data capability and analytics vision is paramount; however, the history of data and analytics is littered with grand plans that have been bogged down under the weight of their own complexity. Our data analytics solutions provide insights in getting smart grid up and running quickly with a limited number of dependencies.
We provide decision-support and management solutions to energy companies focused on fundamental market analysis and price forecasting. We provide data management and analysis, models to simulate the markets and consulting services to help energy companies make informed decisions, formulate and validate strategies for future growth.
We support companies with the management of complex and huge volume of data required for fundamental market analysis. Our models use the economic concept of supply and demand combined with the deep understanding of market and the relevant commodity supply chain to forecast future prices and trends.
We are acknowledged as specialists for providing data analytical services to the Energy Industry. Our core strength lies in the fact that in addition to strong experience in fundamental analysis of data using different statistical tools and models to derive trends and do predictive forecasting, we have deep knowledge and understanding of today’s complex energy markets.
(Power Demand and Supply Forecasting) To meet the system demands within geographies, energy trading methodologies require frequent and accurate estimates of the power outputs available from the various generation capacities. Analysts study the multitudes of information available at the various platforms of data and determine the demand supply gap that is dynamic and frequent changing. Based on multiple factors, price forecasting models are built and run on hourly basis and this supports the trading functions by designing and developing trading strategies which help the system operators, global utilities, commodity trading houses, investments banks, and hedge funds in generating substantial profits.
Penetration of renewable energy increase in the grid across the world poses many challenges for the proper management of the energy thus accrued given the non-firm nature. Accurate forecasting of this variable energy, thus, becomes critical for the proper optimization and management of the power grids. Grid operators should be able to regulate this variable source of energy well enough to reduce the indulgence of the other more expensive sources of power – e.g. gas, oil.
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