Optimization and Control Method of Heating System for Low-Energy Buildings Based on Simulation Model

Abstract

This invention discloses an optimized control method for heating systems in low-energy buildings based on simulation models. The method first establishes a simulation model of the dynamic heating system and optimizes the system based on real-time electricity prices, building occupancy rates, and outdoor air temperatures to achieve energy-efficient operation while ensuring human thermal comfort. The study first establishes a simulation model of the heating system, including residential buildings, variable frequency pumps, valves, heat exchangers, pipe networks, and boilers. Then, based on factors such as real-time electricity prices, building internal heat load, and outdoor ambient temperature, it optimizes the water supply temperature on the heat source side, the opening control of pumps and valves on the primary side, and the water supply temperature and flow control on the secondary side. This invention achieves a dynamic balance between the supply and demand sides, effectively taps into the potential of demand-side resources, can transfer peak load demand, and improves the system's flexibility and resilience. It is expected to provide new ideas for energy-saving retrofitting and operation and maintenance optimization of heating systems.

Description

Technical Field

[0001] This invention relates to the field of heating system control, and more particularly to a method for optimizing the control of heating systems in low-energy buildings based on simulation models. Background Technology

[0002] Building energy consumption accounts for about one-third of global total energy consumption, and its carbon emissions account for as much as 37%, indicating significant potential for carbon reduction in the building sector. The proportion of renewable energy will inevitably increase gradually, but the intermittent, random, and unstable nature of renewable energy sources (such as wind and solar power) leads to drastic fluctuations in energy supply, making it difficult to consistently and stably meet people's energy needs. Furthermore, influenced by outdoor environmental factors and demand-side energy consumption, short-term imbalances in energy supply and demand frequently occur during summer, winter, or extreme weather conditions.

[0003] Furthermore, due to the rapid development of green and energy-saving buildings, many regions have already achieved four-step or even five-step energy-saving building standards. However, heating companies still adopt traditional heating strategies, failing to fully consider the dynamic changes in outdoor ambient temperature and demand, and failing to make full use of the characteristics of both the supply and demand sides. This increases heating costs and fails to adequately meet users' energy needs.

[0004] In order to meet the thermal comfort needs of the demand side, the heating system's heat production and heat supply to rooms can be continuously optimized and controlled to minimize energy costs and avoid energy use during peak periods. This can effectively alleviate the contradiction between the supply and demand sides, smooth out peak and valley loads, balance intermittent energy fluctuations, provide ancillary services, enhance the system's regulation capacity and stability, and solve the problem of unstable external conditions. Summary of the Invention

[0005] The proposed simulation model-based optimization control method for heating systems in low-energy buildings can maximize the scheduling of potential energy loads on the demand side while meeting users' thermal comfort needs. It fully considers factors such as outdoor environment, dynamic electricity prices, and human thermal comfort levels, and determines the system control strategy in real time according to external changes, thereby achieving global energy-saving management of the building and heating system under dynamic conditions.

[0006] The optimization control method for heating systems in low-energy buildings based on simulation models includes the following steps:

[0007] Step S1: Establish a simulation model of the heating system based on the architecture of the district heating system. The model includes energy-saving residential buildings, secondary side pumps, valves, heat exchangers, heating terminals, primary side pumps, heat sources and pipe networks.

[0008] Step S2: Determine the indoor temperature setpoint based on human thermal comfort temperature, indoor occupancy rate, and local dynamic electricity price, as the control target of the heating system.

[0009] Step S3: Based on the real-time monitoring or predicted outdoor temperature, take proactive climate compensation control measures to dynamically adjust the primary water supply temperature, optimize the system's heat output, and improve the system's ability to adapt to changes in outdoor temperature.

[0010] Step S4: Calculate the primary side water supply temperature setpoint based on the indoor set temperature, outdoor weather temperature, and secondary side water supply temperature. Use a PID controller with the primary side water supply temperature setpoint and actual measured value as input to adjust the primary side pump and valve opening to regulate the primary side flow rate, thereby achieving responsive control to changes in building heat load.

[0011] Step S5: Using a PID controller with the actual indoor air temperature and the set temperature as input, adjust the opening of the secondary side pump and valve to regulate the water supply flow and accurately control the indoor temperature.

[0012] This invention can reduce energy consumption on the supply side by utilizing dynamic changes in demand, fully utilizing user demand load, and reducing energy consumption. Furthermore, it can achieve a dynamic balance between supply and demand. While ensuring human thermal comfort, by establishing a reasonable control strategy, it can completely avoid energy use during peak periods, ensuring that heat demand is met entirely during periods of low prices, thus alleviating supply pressure during peak periods. Attached Figure Description

[0013] Figure 1 This is a flowchart of the heating system optimization control method for low-energy buildings based on simulation models, as described in this invention.

[0014] Figure 2 This is a dynamic electricity price, indoor occupancy rate, and indoor set temperature diagram of the heating system optimization control method for low-energy buildings based on simulation models provided in this embodiment of the invention.

[0015] Figure 3 This is a graph showing the outdoor weather temperature and the water supply temperature on the heat source side of the heating system optimization control method for low-energy buildings based on simulation models, provided in an embodiment of the present invention.

[0016] Figure 4 This is a graph showing the outdoor weather temperature, indoor set temperature, and secondary water supply temperature of the heating system optimization control method for low-energy buildings based on simulation models provided in this embodiment of the invention.

[0017] Figure 5 The indoor air temperature and indoor set temperature are provided in the simulation model-based optimized control method for heating systems of low-energy buildings according to embodiments of the present invention.

[0018] Figure 6 This is a diagram showing the heating power and dynamic electricity price of the heating system optimization control method for low-energy buildings based on simulation models provided in this embodiment of the invention. Detailed Implementation

[0019] To better understand the subject matter, technical solutions, and advantages of this invention, the invention will be described in detail below with reference to the accompanying drawings and embodiments. It should be noted that the specific embodiments described below are merely illustrative of the invention and not intended to limit it. Furthermore, the embodiments of the invention and the technical features within them can be combined with each other, provided they do not conflict with each other.

[0020] The simulation model-based optimization control method for heating systems in low-energy buildings of the present invention mainly includes the following steps:

[0021] Step 1: Refer to the appendix Figure 1 A simulation model of the heating system was established, which mainly consists of a boiler, primary side pumps and valves, heat exchangers, secondary side pumps and valves, and residential buildings using floor radiant heating.

[0022] Step 2: Determine the dynamic indoor set temperature based on thermal comfort temperature, occupancy rate, and dynamic electricity price. The results are shown in the attached figure. Figure 2 As shown, (a) represents the relationship between time and electricity price, (b) represents the relationship between time and thermal comfort occupancy rate, and (c) represents the relationship between time and thermal comfort temperature. Electricity price is a dynamic price with peaks and troughs. Indoor occupancy rate depends on the actual situation. This example assumes the user leaves for work at 8:00 AM and returns home at 6:00 PM, remaining home from 6:00 PM to 8:00 AM the next morning. According to the "Design Code for Heating, Ventilation and Air Conditioning of Civil Buildings," the indoor design temperature range should be 18℃-24℃. The dynamic room temperature setting can be obtained: from 0:00 to 8:00 AM, the electricity price is low and stable, maintaining the room temperature at 22℃. From 8:00 to 11:00 AM, the electricity price is high, and the occupancy rate is 0. At this time, it is only necessary to maintain the room temperature no lower than the minimum thermal comfort temperature of 18℃. From 11:00 to 18:00, electricity prices are at a low point. Although the occupancy rate is 0% during this period, to reduce peak pressure, preheating is implemented a period earlier than peak hours to maintain the room temperature at the upper limit of the indoor thermal comfort temperature of 24°C. This allows for the storage of energy in the building envelope and the terminal of the floor radiant heating system for peak use. From 18:00 to 23:00, due to peak electricity prices, the indoor temperature is maintained at 20°C. From 23:00 to 24:00, during off-peak hours, the room temperature is maintained at 22°C.

[0023] Step 3: A climate compensator is used on the heat source side to regulate the boiler's water supply temperature. The boiler's water supply temperature change curve is as follows:

[0024]

[0025] In the formula, t sup_pri The primary side water supply temperature of the boiler; t wea_low The minimum outdoor temperature setting is -12℃; t wea_high The outdoor maximum temperature is set at 12℃; t sup_high The upper limit for boiler water supply temperature is 80℃; t sup_low The lower limit of the boiler water supply temperature is 60℃; t wea This is the real-time outdoor temperature.

[0026] Figure 3 The diagram shows the relationship between outdoor weather temperature and the water supply temperature on the heat source side. When the outdoor weather temperature is low, the boiler water supply temperature is increased, and when the outdoor air temperature is high, the boiler water supply temperature is decreased.

[0027] Step 4: Adjust the circulating water flow using a climate compensator on the secondary side, such as... Figure 4 As shown, the secondary water supply temperature is determined based on the outdoor weather temperature and the indoor air set temperature. When the outdoor air temperature is higher than the indoor air set temperature minus 8°C, the circulating water flow rate is 0 and no heating is provided.

[0028] Its heating compensation curve is as follows:

[0029] T Out_offset =T out +dT Out_HeaBal

[0030] In the formula, T Out_offset To compensate for temperature changes caused by outdoor weather; T out dT represents the outdoor temperature. Out_HeaBal The temperature compensation value is 8K.

[0031] The heating compensation curve under standard conditions is as follows:

[0032] T Out_offset_nominal =T out_niminal +dT Out_HeaBal

[0033] In the formula, T Out_offset The outdoor temperature is -7℃ under standard conditions.

[0034] To correlate the outdoor weather-compensated temperature with the setpoint of the secondary water supply temperature, a heating compensation coefficient is introduced. When the indoor setpoint temperature is lower than the weather-compensated temperature, the compensation coefficient is 0, calculated as follows:

[0035]

[0036] In the formula, T Roo_set Set the indoor air temperature as shown in step 2; T Roo_nominal The indoor air temperature is 20℃ under standard conditions.

[0037] The secondary water supply temperature setpoint is calculated as follows:

[0038]

[0039] In the formula, T sup_nominal The secondary water supply temperature under standard conditions; T Ret_nominal is the secondary return water temperature under standard conditions; m is the heat transfer coefficient, 1.3.

[0040] The difference between the setpoint of the secondary side water supply temperature and the actual measured value of the secondary side water supply temperature is compared. The difference is reduced by adjusting the PID controller, which generates valve and pump opening control signals to regulate the primary side flow.

[0041] Step 5: Use a PID controller to adjust the secondary side water supply flow rate so that the indoor air set temperature continuously approaches the actual indoor air temperature. Figure 5 As shown, due to the thermal inertia of the floor radiant heating system, the indoor air temperature will not immediately reach the set value. However, as the heating system operates, it will eventually reach the set indoor air temperature. On the third day, the indoor air temperature exceeds the set temperature because the solar radiation is too strong on that day, and the extra heat gained from the outside causes overheating.

[0042] Appendix Figure 6 This demonstrates the boiler's heating power performance under time-of-use pricing. This control method can completely transfer the demand load during high-price periods to low-price periods, thereby alleviating the pressure on heating and power supply during peak hours. It can tap the potential of demand-side resources, improve the flexibility and resilience of the system, and help the consumption of new energy sources such as wind and solar power while ensuring system safety, thus contributing to the green and low-carbon transformation of the energy system.

[0043] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for optimal control of a heating system of a low-energy building based on a simulation model, The features include the following steps: Step S1, a simulation model of the heating system is established according to the district heating system architecture, the simulation model comprising an energy-saving residential building, a secondary side pump, a valve, a heat exchanger, a heating terminal, a primary side pump, a heat source and a pipe network; Step S2, an indoor set temperature is determined as a control target of the heating system according to a human thermal comfort temperature, an indoor occupancy rate and a local dynamic electricity price; Step S3, an active climate compensation control is adopted according to a real-time monitoring value or a prediction value of an outdoor temperature, a primary side water supply temperature is dynamically adjusted, a heating output of the system is optimized, and an ability of the system to adapt to outdoor temperature changes is improved; Step S4, a primary side water supply temperature set value is calculated according to the indoor set temperature, an outdoor weather temperature and a secondary side water supply temperature, a PID controller is adopted to take the primary side water supply temperature set value and an actual measurement value as inputs, a primary side flow is adjusted by adjusting an opening degree of a pump and a valve, and a response control of building heat load changes is realized; The specific process is that the primary side flow is controlled by a climate compensator, the climate compensator comprehensively considers the secondary side water supply temperature, the outdoor temperature and the indoor set temperature, and outputs the secondary side water supply temperature set value; the secondary side water supply temperature set value of the heating system is calculated as follows: First, calculate the outdoor weather temperature compensation curve in real time and in standard state : ； In the formula, is the outdoor weather temperature; is the temperature compensation value; Outdoor weather temperature heating compensation curve in standard state is: ； In the formula, T is the outdoor weather temperature under standard conditions; The compensation coefficient is then calculated : ； The compensation factor is 0 when the indoor temperature is below the weather compensation temperature; setting a temperature for the indoor air, setting a temperature for the indoor air in standard conditions, compensation of the outdoor weather temperature in standard conditions; The secondary side water supply temperature set value thereof is calculated as follows: ； In the formula, is the secondary-side water supply temperature under standard conditions; is the return water temperature under standard conditions; m is the heat transfer coefficient; Step S5, a PID controller is adopted to take an actual indoor air temperature and a set temperature as inputs, an opening degree of a secondary side pump and a valve is adjusted to adjust a water supply flow, and an indoor temperature is accurately controlled. 2.The simulation model based optimization control method of a heating system of a low energy building according to claim 1, wherein, The simulation model of the heating system in the step S1 is established by Dymola software, the simulation model accurately determines parameters of each component element through building design parameters and equipment selection parameters, and can accurately reflect dynamic thermal characteristics of the heating system. 3.The simulation model based optimization control method of a heating system of a low energy building according to claim 1, wherein, The heating terminal in the step S1 is a floor radiant heating system. 4.The simulation model based optimization control method of a heating system of a low energy building according to claim 1, wherein, The local dynamic electricity price in the step S2 has a low valley period, a flat period and a peak period, and an indoor thermal comfort temperature range is determined by demand. 5.The simulation model based optimization control method of a low energy building heating system according to claim 1, wherein, The heat source in the step S3 comprises a boiler, a thermal power plant or a heat pump. 6.The simulation model based optimization control method of a heating system of a low energy building according to claim 1, wherein, The water supply temperature change curve in the step S3 is as follows: ； In the formula, is the supply water temperature of the primary side of the heat source, as an output; is the minimum temperature setting value of the outdoor weather; is the maximum temperature setting value of the outdoor weather; is the upper limit of the supply water temperature of the heat source; is the lower limit of the supply water temperature of the boiler; is the real-time outdoor weather temperature, as an input; The water supply temperature of the heat source side is determined by the outdoor weather temperature, when the outdoor temperature is low, the water supply temperature of the heat source side is increased, and when the outdoor air temperature is high, the water supply temperature of the heat source side is decreased. 7.The simulation model based optimization control method of a heating system of a low energy building according to claim 1, wherein, The adjustment mode in the step S4 is that a PID controller is adopted to compare a difference between the secondary side water supply temperature set value output by the climate compensator and an actual measurement value of the system, an opening degree control signal of a valve and a pump is generated, a primary side flow is accurately adjusted, and coordinated optimization and energy-saving control of system parameters are realized. 8.The simulation model based low energy consumption building heating system optimization control method of claim 1, wherein, The secondary side flow in the step S5 is controlled by a PID controller, the PID controller generates and controls an opening degree signal of a valve and a pump based on a difference between an actual indoor temperature and a set temperature, and ensures that the indoor air temperature reaches the set value.

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