Ideal Logic Heat H24 Real Time Boiler Performance #40
Replies: 2 comments 31 replies
-
|
@sergeantd83 Could I please have your thoughts on the efficiency notes I made in the first post when you have time? GCV vs NCV. Does that seem correct to you? |
Beta Was this translation helpful? Give feedback.
-
|
Sorry but I don’t have an answer for this. I noticed the same on my installation but I can’t explain it. My boiler manual indicates minimum gas consumption 0.53 m3/h, while in real life, after some calculations, gas meter indicates minimum gas consumption only 0.43 m3/h. That means my boiler in real life uses about 19% less gas than the manual indicates. In conclusion I can’t really tell what is happening here. But for sure it is a positive conclusion. |
Beta Was this translation helpful? Give feedback.
-
|
Prob 0.53m³ @ 20C? |
Beta Was this translation helpful? Give feedback.
-
|
Hi @sergeantd83 just started to use SAT as you know, entered my figures from the boiler manual (decimal point input would be nice) as 0.6 min and 3.4 max. then been looking at the gas sensor current_consumption figures which seemed higher than I expected. Anyway I've been monitoring my boiler for a while and the absolute minimum the relative modulation goes to is 3.57% and that seems to equate to what I've seen on my smart meter of around 5-6kw of gas usage per hr. With the setting from the boiler manual rounded to 0.6 for SAT, @3.57% RM that indicated a gas usage of roughly (Cal 40) 6.7kWhr which was not what I was seeing from the smart meter, more like 5.6kWhr. So I've adjusted my minimum value based on the following logic, which could be completely wrong :) The maximum gas use according to the manual is 3.314 so at a RM of 3.57% that would be around 0.1183098 I've then taken the minimum value 0.59 and then subtracted this to give 0.4716902, so rounded gives 0.5 to enter in SAT. This now give me a usage rate 0.5 at min RM @3.57% and hence 5.6kWhr which is closer to smart meter readings and what the boiler manual states as the minimum Thoughts? |
Beta Was this translation helpful? Give feedback.
-
|
Excellent write up, I've an Ideal Vogue Max 18kW system boiler which isn't on the SAT list of compatible gateway boilers, did your Opentherm system need a lot of configuration to get it to work for a boiler type not listed? The reason for asking is that I'm really keen in trying to smooth out my efficiency as I currently control with Hive and have Home Assistant, the big but is I'm not a coder, however, your experience has tweaked my interest. |
Beta Was this translation helpful? Give feedback.
-
|
You can set it manually to 50 for now, and we can tweak it later. Ideally, your temperature should be updated about every minute. We recommend the Xiaomi LYWSD03MMC with this firmware https://github.com/pvvx/ATC_MiThermometer which can be set to update every 30 seconds, but let's see how your Sonoff THR316D performs. I believe Sonoff THR316D can be flashed with Tasmota or ESP-Home and then it's easier to force them to update more frequently compared to stock firmware. |
Beta Was this translation helpful? Give feedback.
-
|
Thanks for the pointers and support, I've adjusted the temperature and ordered a couple of Xiaomi LYWSD03MMC as suggested, not flashed a device before, so I'm looking forward to having a go. |
Beta Was this translation helpful? Give feedback.
-
|
Odd one…does SAT alter the actual measured room temperature by adding some kind of correction factor to it? |
Beta Was this translation helpful? Give feedback.
-
|
Have you enabled thermal comfort in the configuration? |
Beta Was this translation helpful? Give feedback.
-
|
Yes I have, maybe I should just leave things alone 😊 |
Beta Was this translation helpful? Give feedback.
-
Real time performance of the Ideal Logic Heat H24 boiler, managed by SAT (Smart Autotune Thermostat) and OpenTherm:
EmonCMS
https://emoncms.org/app/view?name=MyBoilerIdealLogicH24OpenthermSAT&readkey=1d29c637a4817acdf6e6e271850c9026
Grafana Dashboard [NEW (Oct 2024)] - with additional data points:
https://gasboiler.grafana.net/public-dashboards/8d44381aafa94fe9bdc87839d8845ada
EmonCMS vs Grafana reporting.
EmonCMS - better for long term view.
Grafana - better for a daily snapshot view, with precise datapoints / timestamps where it matters.
Other example boilers and their real time data for comparison:
Also follow boiler's diary on Blue Sky and X/Twitter.
Expand each section below for more details:
Overview
Some commercial thermostats advertise their thermostat as **smart**, where the only smart feature is the ability to control the heating remotely, but in fact, only offer the simple communication.Typical efficiency curve for condensing boilers:
image source: https://www.heatgeek.com/condensing-boilers-efficiency/
General notes
However, I have a workaround which ensures that most of the time, the boiler is indeed working at its minimum modulation, unless the target flow (heating curve + PID) demand is high [higher than current flow temperature] during warm up.The latest version of SAT now officially supports 0% modulation, sweet!.When DHW call is made, boiler ignores OpenTherm instructions and runs at 80 C degrees. There are three zone valves in the house: Hot Water, Upstairs and Downstairs (not talking about TRVs here). When DHW call is made, Hot Water valve opens, and Upstairs & Downstairs close; then if CH call is made, Hot Water valve closes and the other two open.(July 2024) EDIT: With some tweaks in Home Assitant, I'm now using OpenTherm with SAT to manage both Central Heating and Domestic Hot Water demand.What is ErP?
In the EU / UK, ErP stands for Energy-Related Products and is a way of measuring an energy consuming appliance, such as a boiler’s, efficiency in converting the energy it uses into the desired product, heat for your property and its water.
The Efficiency of a Boiler under the ErP (Energy-related Products Directive) typically refers to its energy efficiency rating, which is expressed in percentages and categorizations from A+++ (most efficient) down to G (least efficient). Most modern boilers must achieve an A rating under this system, indicating that they convert at least 90% of their fuel into heat.
GCV vs NCV (gross vs net calorific value) for condensing boilers
GCV (Higher Heating Value): Total energy, including latent heat of condensation of water vapour.
NCV (Lower Heating Value): Usable energy, excluding latent heat of water vapour.
Condensing boilers are designed to improve energy efficiency by recovering some of the latent heat from the water vapour in the flue gases, which would otherwise be lost in non-condensing boilers.
Since condensing boilers are capable of reclaiming a portion of the latent heat contained in the water vapour, they operate more efficiently and can achieve efficiencies higher than 90% relative to the GCV. Thus, when calculating the efficiency of condensing boilers, GCV might be considered more appropriate because it represents the maximum potential energy content of the fuel, including the recoverable heat.
https://eur-lex.europa.eu/legal-content/EN/TXT/PDF/?uri=CELEX:52014XC0703(01)&from=SL
https://www.legislation.gov.uk/eur/2013/813/annexes/data.xht?view=snippet&wrap=true
ErP of the Ideal Logic Heat H24 at the ErP rated 40 °C Mean Water Temperature
Ideal Logic Heat H24 ErP can be found: Ideal-Logic-Heat-H.pdf
Thanks to SAT and the boiler's real-time stats, we can say that this boiler is running at around the designed Part Load ƞ1 = 98.7% during CH duty cycles and slightly below that for DHW duty cycles (about 92-94%). It's not clear from the manufacturer's documentation whether the 98.7% value is GCV or NCV, however, given the industry standards, it more likely to be a GCV value.
ErP vs SAT-facilitated performance during Low Load Control (and Mean Water Temperature < 40 °C)
ErP Part Load ƞ1 was tested at the 40 °C mean water temperature MWT = (flow + return / 2). However, SATs low-load control makes it possible to run the boiler at below 40 °C.
Example April 24 2024
In the snapshot below, the MWT is about 35 °C degrees.
The table below indicates that the minimum output at 40 °C mean water temperature is 5.1 kW.
Using that data, we could plot a relationship between temperature and heat output
Mean Water Temperature Formula
mean_temp = (boiler_flow_temp + return_temp) / 2
Formula
Minimum Heat Output (kW)=−0.01× Mean Water Temperature (°C)+5.5
Table
<style> </style>Formula
Heat Output (kW)=−0.0467× Mean Water Temperature (°C)+27.467
Table
<style> </style>Using these values, we can adjust how we calculate the heat output dynamically!
This template does the following:
July 2024: Some DHW observations
Domestic Hot Water
Having tried various approaches to heating water, it seems that the best strategy is to heat at full throttle, i.e. 80 C degrees flow temperature.
The cost of providing hot water is much lower compared to central heating on annual basis, and the comfort of having hot water irrespective of demand is more important than some small potential energy saving that could be made.
Even with 80 C flow temperature, the average efficiency for DHW is > 90%
August 2024: Some more DHW observations
Domestic Hot Water
A slightly more efficient strategy is to heat the cylinder water tank at around 68 C degrees flow temperature. The max target water tank temperature is 54.5 C degrees which minimises the risk of domestic Legionella without having to worry about the average hot water turnover per day (see https://www.youtube.com/watch?v=oJeyc_cGIMU for context) and provides plenty of hot water for the whole day, also the minimum delta T while DHW is running is about 13 C degrees. Therefore, 54.5 + 13 = 67.5 is the minimum flow temperature required so that the boiler doesn't cycle during DHW.
Fuel consumption is more efficient at 67.5 C degree flow temperature rather than when running the boiler at 80 C degrees flow temperature.
Legionella risk vs Cylinder Water Tank Temperatures and Water Daily Turnover (from the YouTube video above)
September 2024: Estimating Gas Consumption based on historical data
Manufacturer's Gas Consumption
When the boiler is working in the condensing mode, the minimum NCV (Net CV) gas consumption is at 4.9 kW and the minimum heat output is 5.1 kW, so the maximum efficiency (NCV) according to the data is 104.1% at 40 °C Mean Water Temperature. This figure is higher than 100%, because it's the additional latent heat that is recovered during the operation.
Historical data observations
Looking at the smart gas meter data and comparing it to the heat output and the overall efficiency, I noticed that the efficiency can indeed operate at that level.
According to the "Typical efficiency curve for condensing boilers" graph from Heat Geek, the lower the Mean Water Temperature, the higher the efficiency. However, this is only true if the system has warmed up, meaning that the radiators and pipes have warmed up from cold. And the period between cold and the warm up is under 100% efficient, even with low mean water temperature.
Typically, looking at historical data, you will observe that
System is
Smart Meter Gas Readings limitations
The installed smart gas meter runs on a battery, which can last for many years, however, the gas meter readings are limited to every 30min.
Other gas appliances
There is also a gas hob for cooking, which means that it adds another complexity when estimating efficiency. On average, about 1.2 kWh is used for cooking per day. And it's usually early morning or evening when gas hob is used.
Warmer months
During spring, summer and autumn, central heating is only required throughout the night, therefore, gas hob gas use can be easily distinguished most of time time, and with the help of some home assistant automations, rules put in place account for that.
Winter months
During winter months, the central heating is likely to operate during the day, which means that the average gas used for cooking needs to be accounted for. However, the estimation becomes more tricky and not always precise.
Estimating Central Heating & Domestic Hot Water gas consumption
Looking at the historical data, it's possible to create a set of functions which can estimate gas consumption within 1% margin error. Below, is the jinja home assistant template, which apply the correct function (coefficient) depending on the Mean Water Temperature.
These functions were derived from the following data
Mean Water Temperature (left column), typical efficiency at that the level (right column)
Here's the complete home assistant template that calculates the estimated gas consumption. Note that this template first calculates the Heat Output Dynamically, depending on Mean Water Temperature and Modulation, and then, it applies the relevent gas consumption factor, and the final output is the estimated gas consumption.
Comparing Actual vs Estimated Gas Consumption results during CH cycles 18:00~ 26th Sep 24 and 09:00~ 27th Sep 24
0.97763 is the Actual efficiency
where 29.241 = Heat Output, and 29.91 = Actual Gas Consumption
0.97541 is the Estimated efficiency
where 29.241 = Heat Output, and 29.978 = Estimated Gas Consumption
The estimated efficiency will always aim to be a conservative estimation, in order to ensure that the result is as trustworthy as possible.
Comparing Actual vs Estimated Gas Consumption results during CH and DHW cycles 20:50~ 30th Sep 24 and 09:30~ 1st Oct 24
<style> </style>Gas Smart Meter Data
Estimated Gas Data
Comparing Actual vs Estimated Gas Consumption results during CH cycles 21:30~ 3th Oct 24 and 09:30~ 4th Oct 24
<style> </style>Gas Smart Meter Data
Estimated Gas Data
Comparing Actual vs Estimated Gas Consumption results during DHW cycles
DHW cycles operate at higher modulation levels, and additional factor is applied on top of above template, which is:
DHW Gas Consumption = CH Gas Consumption Template Above * 1.12October 2024: Create dynamic Heat Loss sensor in Home Assistant (using SAT as the tool to measure it): 4th 22:00~ and 5th 10:00~ October 2024
SAT temperature precision = 99.95%, i.e. target vs actual average temperatures over the specified period of time
Indoor target temperature is set to 20.5 C degrees and actual average indoor temperature over this period of time was 20.51 C degrees.
This tells us that SAT demanded exactly the same amount of heat from the boiler as the house was losing.
Actual Gas Consumption based on the data from the smart meter over the specified period of time.
31969.48 - 31945.46 = 24.02 kWh
Average outdoor temperature over the specified period of time
9.48 C degrees
Calculate average gas consumption over the specified period of time
Heating Start Time: 22:15
Heating Stop Time: 09:45 (following day)
Heating Demand Total Hours = 11 hours and 30 minutes
24.02 kWh / 11.5 = 2.088695652173913 kW or 2088.7 Watts
Given that we know the average Watts required to keep the house at 20.5 C degrees while the outside temperature was 9.48 C degrees, we can use that to calculate the U value
Calculated U value
The U-value, also known as thermal transmittance, is a measure of how well a building element conducts heat. It quantifies the rate of heat transfer through a material or assembly of materials (like walls, windows, roofs, or floors) per unit area per degree of temperature difference between the inside and outside environments.
In the context of calculating the heat loss of a house, the U-value plays a crucial role in determining how much heat energy is lost through the building's envelope. A lower U-value indicates better insulating properties, meaning less heat is lost and the building is more energy-efficient. Conversely, a higher U-value means the material allows more heat to pass through, leading to higher energy consumption to maintain indoor comfort levels.
The relationship between heat loss and the U-value is expressed by the formula:
{% set Watts = 2088.7 %} #Average Heat Loss
{% set A = 184.87 %} # total floor area in square meters
{% set indoor_temp = 20.51 | float %}
{% set outdoor_temp = 9.48 | float %}
{% set delta_t = indoor_temp - outdoor_temp %}
{% set U = Watts / (A * delta_t) %}
{{ U | round(10) }}
U = 1.0243163692
Create Dynamic Heat Loss sensor
And now, with the U value, we can dynamically calculate the Heat Loss given the indoor and outdoor conditions.
Heat Loss (Watts)=U×A×ΔT
𝑈: U-value (measured in Watts per square meter per degree Kelvin, W/m²·K)
A: Area of the building element through which heat is being transferred (in square meters, m²)
ΔT: Temperature difference between the inside and outside environments (in degrees Celsius or Kelvin)
Jinja Home Assistant Template
{% set U = 1.0243163692 %}
{% set A = 184.87 %} #total floor area in square meters
{% set indoor_temp = 20.51 | float %}
{% set outdoor_temp = 9.48 | float %}
{% set delta_t = indoor_temp - outdoor_temp %}
{{ (U * A * delta_t) | round(3) }}
U * A * delta_t = 2088.7 Watts
Calculate Heat Loss sensor at the design temperature
This calculates the heat loss for the worst case scenario expected during coldest months.
{% set U = 1.0243163692 %}
{% set A = 184.87 %} #total floor area in square meters
{% set indoor_temp = 20.51 | float %}
{% set outdoor_temp = -3.5 | float %}
{% set delta_t = indoor_temp - outdoor_temp %}
{{ (U * A * delta_t) | round(3) }}
U * A * delta_t = 4546.662 Watts
Note 1: This example exercise should be carried out during the coldest day, so that the true U value can be calculated, however, using warmer days should provide good indication. Therefore, the colder the outside conditions during which the U value is calculated, the more precise that U value will represent the real conditions.
Note 2: For your home assistance instance, replace static values with your dynamic sensors where relevant.
What does it mean to calculate Heat Loss at the design temperature?
Calculating heat loss at the design temperature involves determining the maximum amount of heat that will be lost from a building when the outdoor temperature reaches a specific, typically extreme, value known as the design temperature. This calculation is crucial for properly sizing heating systems to ensure they can maintain comfortable indoor temperatures even under the most demanding weather conditions.
What is Design Temperature?
Why Calculate Heat Loss at the Design Temperature?
Long Term Heat Loss Graph
Another run between 11th Oct and 12th Oct 2024
Gas Smart Meter usage between 17:17pm and 10:30am = 39.83 kWh, and average consumption 2343.288786 Watts
between 11th Oct - 17:15 and 10:30am - 12th Oct
{% set U = 0.9231852047 %}
{% set A = 184.87 %}
{% set indoor_temp = 20.53 | float %}
{% set outdoor_temp = -3.5 | float %}
{% set delta_t = indoor_temp - outdoor_temp %}
{{ (U * A * delta_t) | round(3) }} = 4101.182 Watts or 4.1 kW
This result seems very optimistic, so if we instead, look at data between 20:50pm and 07:30am, with average consumption at 2639.528571 Watts, we get
between 11th Oct - 20:50 and 07:30am - 12th Oct
{% set U = 0.9792698918 %}
{% set A = 184.87 %}
{% set indoor_temp = 20.5 | float %}
{% set outdoor_temp = -3.5 | float %}
{% set delta_t = indoor_temp - outdoor_temp %}
{{ (U * A * delta_t) | round(3) }} = 4344.903 Watts or 4.3 kW
28th October 2024: Random quality check to verify that the estimated gas consumption =< actual gas consumption
Actual
13.66
Estimated
13.594
22nd February 2025: A note to those interested in getting SAT / OpenTherm gateway
Please note that I still experiment with SAT and so when you look at the graphs, sometimes you might see they are quite messy. I made small modifications to the code, but for the best results, please use the official release without modifications.
Beta Was this translation helpful? Give feedback.
All reactions