How to perform energy planning successfully

Submitted by Aline Gonçalves on Thu, 01/03/2019 - 15:45
How to perform energy planning successfully

Do you know how to predict your company's electricity consumption over the long term? In this article we will address two factors that influence strategic energy planning: consumption and market price dynamics.


The Statistical Review of World Energy, prepared by British Petroleum (BP), indicates that in 2017 primary energy consumption grew 2.2%, above the average of the last 10 years. Considering the projections, price instability, and concern about environmental issues, the development of a long-term energy consumption plan has become essential for strategic planning in the industrial sector, the largest energy consumer in the world – approximately 51% according to the 2018 BP report.

In addition to increasing their representation, industries that choose to develop a long-term consumption strategy will guarantee a strong basis for energy purchasing negotiations at competitive prices, and also minimize the risks of exposure to the short-term market, where rates are even higher.

Other beneficial factors for planning include the capacity to cushion cost variations from renewable energy generation, such as photovoltaic, wind, or biomass. As well as conscious energy consumption and energy efficiency initiatives in the company's production process.

Energy consumption forecast

Many energy management teams encounter difficulties in scenario forecasting, for example, to perform consumption planning without a dedicated tool. The ability to rapidly anticipate scenarios of energy and utilities consumption of a productive unit or even of an entire site from production plans is very important and brings savings as well as a reduction of operational risks.

The first step in planning consumption is to consolidate historical data. In practice, reference the invoices for the last 24 months for generation, transmission, and distribution, identify the amount of energy consumed during peak and off-peak periods, highlight the times of excessive demand and excess reactive energy consumption. The historical consumption profile, along with growth expectations for the next few years, forms part of the database necessary to construct the forecast of future scenarios.

The second step is to identify the main factors that influence your company's energy consumption, consolidate the historical data of these factors, and generate a mathematical model that demonstrates the relationship between consumption and these indicators.

The greater the adherence of the historical values to the proposed mathematical model, the greater the chances of success in contracting energy over the long term. In this article you can find a few techniques for creating consumption forecast models that can be applied to your business.

Price Forecasting in the Energy Market

According to the article Demand-Side View of Electricity Markets, by senior IEEE (Institute of Electrical and Electronics Engineers) member Daniel S. Kirschen, when it comes to price dynamics in the energy market, committees composed of representatives of producers, transmission and distribution companies, retail traders, and regulators make most of the decisions. And the influence of final consumers on strategic planning in the electricity sector is a market necessity.

Although not an easy task, understanding price dynamics is of fundamental importance to consumers who are considering migrating to the environment of non-regulated energy procurement. The complexity is due to the fact that the price of energy derives from the balance of the market, and this balance is in turn influenced by load and generation factors. Seasonal, meteorological, and economic factors are considered for the load factor. The generation factor includes factors such as the increase or decrease in generation capacity, interruptions for maintenance, and transmission congestion.

A reasonable accuracy can be obtained when predicting the long-term averave value and the expected volatility of prices for assessing coverage contracts. Techniques for forecasting the price of energy vary from neural networks to traditional time-series forecast models and can be consulted in the articles by Szkuta and Nogales, both of whom are members of the IEEE.

How to perform energy planning using a system

Analyzing data through metrics anchored to manual processes, for input of information, report generation, graphics, scenario projections, and synergy between areas is extremely complex and specific, which requires significant time from the team.

With the integrated real-time monitoring of energy inputs, an energy management system facilitates the management of the entire budgeting cycle of the organization, orchestrating procedures of prediction of consumption and of corresponding costs and offering information for planning that is more appropriate to the reality of the company and its objectives.

Also read: 4 important conecpts of industry 4.0 in energy and utilities management


Energy Management Analyst, Viridis

Energy Management Analyst at Viridis, working in Energy Management and Strategic Planning at Bayer. Trained in Electrical Engineering with emphasis on Control and Automation at the Federal University of Uberlândia. Participated in R&D projects for intelligent energy measurement at Enel and CEMIG, conducted innovation, artificial intelligence, robotics, and gamification projects for corporate environments. 

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