From 2021, the Chamber of commercialization of electric energy (CCEE) will begin to disclose the price of the settlement of differences (PLD) on a hourly scale. In this article we analyze the implications of this change and how digital transformation can help companies in this new challenge.
What is PLD
The PLD (settlement price of differences) is used to price the energy settled in the short-term market (MCP), where the differences between the energy contracted and the amounts actually generated or consumed by CCEE agents are accounted for.
The LDP is based on the marginal cost of Operation (CMO) which is calculated by the national system operator (ONS). The CMO is used for the dispatch of power plants by the ONS, that is, it is an indicator of the cost of energy that is used by the operator of the National interconnected system (SIN) to decide which plants to trigger to meet an increase in demand.
The cost of operating a power plant depends on some characteristics, as well as other factors. For example, the cost of driving a thermoelectric power plant is linked to the cost of fuel (which can be natural gas, mineral coal, etc.) and the efficiency of the plant itself. Hydroelectric power plants, on the other hand, have their cost strongly linked to the level of the reservoirs, as well as the rainfall projections of the region.
The calculation of the CMO is done by the ONS through mathematical and statistical models, such as Newave and Decomp, which allow to project the cost of energy over time. Newave is used to project the cost over a long-term horizon (next 5 years with monthly scale) and Decomp for the medium-term (next month with weekly scale).
Until last year, CCEE used cost projections to calculate the LDP on a weekly scale for each submarket of the electrical system (North, Northeast, Midwest/Southeast, South). Every Friday, CCEE announced the PLD of the next week for each submarket, dividing the values into three load levels (high, medium and light) that sought to reflect the variability of consumption in the period.
Why the hourly PLD is being implemented
In the past, the Brazilian energy matrix was composed mostly of hydroelectric plants, which were responsible for more than 90% of the country’s energy generation. Today hydropower is responsible for approximately 60% of our energy production, so we have a much greater share of other energy sources (such as thermal, solar and wind) in the composition of our energy matrix.
The cost of operating hydroelectric power plants do not have great variation throughout the day, so the use of a weekly scale for their pricing has been adopted in the past without major problems. However, the greater diversity of the electrical Matrix, especially with the entry of intermittent renewables such as solar and wind, brings greater variability to the cost of energy throughout the day. This is because solar and wind renewable sources depend on environmental conditions that vary widely throughout the day.
Thus, to better reflect this cost variation and have a more adequate pricing of energy, it is essential to use a projection of costs and prices with greater granularity. In 2020, the CMO was also calculated in the short term through Dessem, a new mathematical model that allows the projection of prices in the short term with time scale.
From 2021 the PLD will also be calculated based on the hourly cost of energy. Every day the CCEE will disclose the value of the PLD for each region of the country for each hour of the following day. The figure below shows the hourly PLD for the Southeast/Midwest submarket of the day 06/01/2021. We can see that the maximum value is 12.6% higher than the minimum value of energy in the period, which can represent a significant variation for a large consumer.
PLD Southeast/Midwest submarket schedule (source CCEE)
What changes with the PLD schedule
The hourly PLD aims to bring greater reality and accuracy between the operating costs of the electrical system and the energy prices practiced in the wholesale market, composed of large energy consumers, such as industry.
This signaling of the economic value of energy should bring benefits, such as encouraging large consumers to make energy use more flexible, reducing its use in more expensive periods. In addition to enabling savings for consumers who can make their production more flexible, reducing demand at more critical times for the electrical system should also bring relief to the operation of the SIN.
Large consumers who contract Energy in the free market (ML), also called the free contracting environment (FTA), will be impacted by the greater granularity in the energy price in the MCP, and this impact can be positive or negative. For example, if at a certain time the consumer has a higher demand than his ML contract, the additional consumption will be settled in the MCP according to the price of the PLD of that time. If the PLD at this time is higher than the energy price in your ML contract the consumer will have a negative financial impact. On the other hand, if the LDP is lower than the energy price in your ML contract, the financial impact will be positive.
That is, the ACL consumer should know the load curve of his company, and have assertive forecasts for the evolution of this load, so that he can make ML contracts that bring benefits to his operation. These consumers should plan their consumption, with demand response programs, and manage the risk of their energy contracts with great parsimony so that they can optimize their costs and gain competitiveness in the market.
The other ACL agents, such as generators and energy marketers, may also be impacted by the hourly PLD, for example by offering new products and services to consumers that take into account the hourly modulation of contract Energy. Currently the contracts already take into account seasonality, that is, specific conditions of price and volume of energy delivered according to the months of the year. The modulation will also allow the creation of specific conditions for the Times of the day. Thus consumers can make contracts more adhering to their load curve, both from a seasonal and hourly point of view.
For small consumers, such as residential ones, which are part of the captive market, or regulated contracting environment (ACR), there will be no direct impact on the energy tariff, since in this case flat tariffs are practiced. However, the reduction between the projected values for energy and the actual operating cost should decrease the system service charges (SSE) that are indirectly passed on to all consumers.
How Digital transformation can help businesses
As discussed above, the hourly LDP model can have positive or negative impacts for large consumers, especially for ML consumers. In order for them to enjoy the benefits, it is essential that they have knowledge of their production processes and their electric energy consumption profile, so that they can make their production more flexible for times when there is lower energy cost.
Digital transformation, with the monitoring and digitization of processes, can be fundamental in this context, generating data on the operation and consumption of electricity for better decision-making. Data analytics and optimization algorithms can be important allies for planning and monitoring energy contract risks. Automation can also be an important ally, creating more flexible production processes that can take into account the hourly cost of energy among other productive factors.
For free market energy generators and marketers, digital transformation can enable the creation of customized products for customized to the needs of each customer. For example, solutions that analyze the demand and flexibility of each customer and automatically recommend plans suitable for them, which can be purchased online, simply and without human intervention. We can also imagine smart contracts that can be executed automatically taking into account customer-specific time modulation clauses, bringing greater efficiency to processes and reducing energy marketing costs.
In short, the hourly PLD represents a breakthrough for the energy sector towards a more diverse electrical Matrix and with more intense participation of renewable sources.
Digital transformation will clearly be an ally for consumers and other agents in the sector to enjoy its benefits. Companies that prepare will be able to optimize their costs and gain competitiveness in their market. Generators and marketers will be able to count on more suitable products that will be able to attract new customers.
The SIN may have a simpler operation, with possible reduction of demand at more critical times due to price signaling.