Optimizing district energy use from the building-side (i.e. point-of-use) has many benefits, including lower costs and higher building value.
District energy is the go-to energy source for many buildings in urban areas. For a new building, connecting with a district energy network can mean lower up front costs, as investing in boilers or furnaces, air conditioning units, chimneys, and large boiler rooms are rendered unnecessary.
District energy-connected buildings benefit from no energy equipment maintenance. The district energy provider of course maintains a large plant, and those maintenance costs that it incurs benefit from it’s economies of scale. Those costs are passed on to the customer in the price of energy.
District Energy Rate Structures
District energy providers can charge for the energy they provide in a variety of ways. First, they can charge differently depending on the type of customer, such as multifamily, industrial, or office building.
Second, there may be different rate structures depending on past energy use. Users of energy can be shifted by the provider from one rate group or another based on past consumption levels. Third, and adding some complexity, each one of those rate groups can consist of multiple tiers of energy use, where the first “x” amount of energy use is charged at one level, the next batch of energy used above that would have another rate, the third quantity of energy above that another rate, and so on.
A fourth component of district energy costs is time-of-use rate. Some district energy providers charge higher rates, for example, between 8am and noon on weekdays, at certain times of year. These rates are usually posted and published well in advance, and they usually don’t change except for seasonally.
A fifth component is the demand rate. District heating companies can charge for each unit of energy, such as the peak amount of steam, or BTUs passing through the meter in a short period of time, like 15 minutes, over the course of a billing period. Providers can define their demand rates differently, so the details matter.
Day-Ahead Rates
Another rate type that is not so common in North America at this time is the day-ahead rate. It’s possible for district energy providers to anticipate demand ahead of time. With this knowledge, they can post a rate or rates for the following day. For example, if the energy provider expects heavy demand from 8am to 10am the following day, they can notify customers of a higher rate during that time slot. Customers with appropriate technology can then respond by shifting more of their energy consumption to before and after that time slot if the difference in energy costs is significant.
Technology Solutions
Technology that uses artificial intelligence (AI) has been developed that makes it possible to reduce all of these charges, by using the district energy more smartly. A successful example of this is our Finnish technology partner Leanheat.
Leanheat’s technology has been successfully deployed in district heating-connected buildings that collectively house tens of thousands of apartment units. Those apartment units have their heating and cooling costs bundled into the rent by the building owners. The Leanheat technology saves the building owners from 10-20% over previous energy consumption, without any sacrifice in comfort.
Contact CIMI Energy for information about the Leanheat district energy optimizing solution.
Outdoor reset technology, which uses a single outdoor temperature sensor to determine boiler temperatures, is being eclipsed by innovative control technologies that utilize multiple factors plus artificial intelligence (AI) to increase efficiency.
As an efficiency solution, outdoor reset is a step above older technologies that didn’t use any external factors for setting the boiler temperature. However, with the most cutting edge technologies of today, there are many additional factors that can be taken into account, and which improve efficiency even more.
Outdoor Reset Technology
Outdoor reset is a technology that correlates boiler settings with the outdoor temperature in one spot outside the building. The purpose of this match-up is to increase efficiency by lowering systemic losses of energy that naturally occur from the production and distribution of thermal energy.
Here’s how outdoor reset works. Heating curves are shown in the image below. One of the curves is chosen manually by an installer or commissioning agent. The colder the outside temperature, the hotter the water that’s produced (or the longer the system runs, in the case of steam systems). The heating curve slope is chosen manually (top image) and the level of the slope is also chosen (2nd image).
Choosing an Outdoor Reset Curve
Often there are more than a dozen curves to choose from. There is inherently some uncertainty in choosing a curve. One could argue that choosing a curve is part art and part science. The main objective is to find a curve that will work for the building, and that leaves some room for error. Finding that a curve is not steep enough, for example, is only going to be discovered when it’s really cold out. This is not a good result. Yet by choosing a curve that’s steeper than necessary, some system efficiency is sacrificed.
Once the system is set up, the chosen curve is usually not changed more than once or twice, if at all, so there’s not much in the way of “fine-tuning”. Curve adjustments are only made after the fact, based on tenant complaints. If the curve is too steep, tenants will not complain, yet efficiency is sacrificed.
[Note that steam systems use outdoor reset, but don’t work exactly like this. Read about steam systems here:
A Modern Innovation for Improving the Efficiency of Steam Heating Systems]
Upgrading from Outdoor Reset to Leanheat AI
Among the factors that can be used to improve system efficiency is a group of building-specific factors such as how a building reacts to sun (e.g. amount of sunshine, time of day and time-of-year), wind (speed and direction), and “thermal inertia”, how a building responds to the heating system. Other important factors that are accounted for are individual unit temperatures, particularly those units farthest from the heat source. What’s needed to account for all these factors is energy intelligence software using algorithms that learn and adapt.
Leanheat AI actually takes into account all these extra factors using local weather forecasts, plus in-unit temperatures and humidity levels that are gathered by strategically placed sensors through cellular IoT technology. Without human intervention, a dynamic heating curve unique to the building is created. Boiler temperatures are controlled better, so there’s none of the typical large buffer that’s always been a necessary part of outdoor reset-controlled systems. As a result, the heating system runs more efficiently. In Finland, where Leanheat was first introduced, efficiency improvements of 10-20% have been realized.
An added benefit has been lower technical maintenance costs, such as from identifying and correcting housing units where climate control is problematic.
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Outdoor reset technology, which bases operational temperatures on the outdoor temperature, is going to be eclipsed by innovative control technologies that can utilize more factors. As an efficiency solution, outdoor reset is a step above older technologies that use no external factors for achieving a measure of system efficiency, but there are plenty of external factors that, if taken into account, would improve efficiency even more. Information about energy intelligence software that accounts for these factors follows below, but first a review of outdoor reset.
Outdoor reset is a technology that matches up heating and cooling temperatures with corresponding outdoor temperatures. The purpose of this match-up is to increase efficiency by lowering systemic losses of energy that naturally occur from the production and distribution of thermal energy.
Here’s how outdoor reset works. Heating curves are shown in the image below. One of the curves is chosen manually by an installer or commissioning agent. The colder the outside temperature, the hotter the water that’s produced (or the longer the system runs, in the case of steam systems). The heating curve slope is chosen manually (top image) and the level of the slope is also chosen (2nd image).
Choosing an Outdoor Reset Curve
Often there are more than a dozen curves to choose from. There is inherently some uncertainty in choosing a curve. One could argue that choosing a curve is part art and part science. The main objective is to find a curve that will work for the building, and that leaves some room for error. Finding that a curve is not steep enough, for example, is only going to be discovered when it’s really cold out. This is not a good result. Yet by choosing a steeper than necessary curve, some system efficiency is sacrificed.
Once the system is set up, the chosen curve is usually not changed more than once or twice, if at all, so there’s not much in the way of “fine-tuning”. There’s just too much uncertainty for any one person or team to deal with.
Upgrading from Outdoor Reset to Leanheat AI
Among the factors that can be used to improve system efficiency is a group of building-specific factors such as how a building reacts to sun (e.g. amount of sunshine, time of day and time-of-year), wind (speed and direction), and thermal inertia. Other important factors that are accounted for are individual unit temperatures, particularly those units farthest from the heat source. What’s needed to account for all these factors is energy intelligence software using algorithms that learn and adapt.
Leanheat AI actually takes into account all these extra factors and creates, without human intervention, a heating curve unique to the building. As a result, the heating system runs more efficiently. In Finland, where Leanheat was first introduced, efficiency improvements of 10-20% have been realized.
An added benefit has been lower technical maintenance costs, such as from identifying and correcting housing units where climate control is problematic.
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