Power exchange friendly day-ahead scheduling method for building light storage direct-current flexible energy microgrid

Abstract

The invention belongs to the technical field of power systems, and particularly relates to a day-ahead scheduling method for a building light storage direct-flexible energy microgrid with friendly power exchange. Comprising the steps that a mathematical model of the negative carbon building light storage direct-flexible energy microgrid is constructed, so that the complex operation characteristics of the negative carbon building light storage direct-flexible energy microgrid are converted into quantifiable optimization problems; wherein the mathematical model comprises a power generation constraint model, a power balance constraint model, a peak-valley difference and volatility constraint model, a storage battery constraint model, a phase change heat storage system operation constraint model and a water supply system operation constraint model; constructing a target function of an optimal scheduling model by taking the minimum total operation cost of the negative carbon building light-storage direct-flexible energy microgrid in a scheduling period as a target; wherein the total operation cost comprises an economic cost item, an environmental cost item and a power grid interaction optimization demand cost item. After the heat and water storage system is introduced, except for the friendly cost of a power grid, other costs are remarkably reduced.

Description

Technical Field

[0001] This invention belongs to the field of power system technology, and specifically relates to a day-ahead dispatch method for a building-integrated photovoltaic-storage-DC-flexible energy microgrid with power exchange friendliness. Background Technology

[0002] The photovoltaic-storage-DC-flexible microgrid effectively reduces interaction costs with the main power grid by combining high-precision photovoltaic output prediction models and load demand analysis with optimized energy storage system charging and discharging strategies. Its core advantage lies in its DC distribution architecture, reducing energy losses in AC-DC conversion stages, while flexible load control technology enables dynamic response and precise regulation of building equipment. This technological system not only increases the proportion of renewable energy incorporated into buildings but also continuously promotes buildings towards low-carbon or even negative-carbon goals. Through the synergistic application of photovoltaic energy production, energy storage system peak shaving, and carbon sink technologies, some demonstration buildings have already achieved zero carbon emissions throughout their entire lifecycle.

[0003] However, on the one hand, existing research has not adequately explored the load regulation capacity and the potential of diversified energy storage resources. It rarely considers the water pump regulation capacity and water tank energy storage effect in the water supply system, and also ignores the heat pump regulation capacity and phase change material thermal storage effect in the phase change material energy storage system, which has severely limited the photovoltaic-storage-DC-flexible technology. On the other hand, existing research mainly focuses on the external power trading cost of photovoltaic-storage-DC-flexible microgrids, rarely explores the friendliness of external active power exchange, and has not explored its reactive power support potential, resulting in a waste of resource potential.

[0004] Therefore, there is an urgent need to propose a negative carbon photovoltaic storage DC flexible energy microgrid dispatching method that considers the friendliness of external active / reactive power exchange. The above problems have been solved. Summary of the Invention

[0005] The purpose of this invention is to provide a day-ahead dispatch method for building-integrated photovoltaic-storage-direct-drive-flexible energy microgrids with power exchange friendliness. By introducing thermal and water storage systems, this invention significantly reduces costs other than grid-friendly costs (power exchange, carbon emissions, energy storage, and fuel oil), demonstrating the positive role of thermal and water storage systems in optimizing costs, reducing carbon emissions, and reducing fuel oil dependence.

[0006] To address the aforementioned technical problems, this invention provides a day-ahead scheduling method for building-integrated photovoltaic-storage-direct-flexible energy microgrids with power exchange friendliness, comprising:

[0007] By constructing a mathematical model of a negative carbon building photovoltaic-storage direct-flexible energy microgrid, the complex operating characteristics of the negative carbon building photovoltaic-storage direct-flexible energy microgrid are transformed into a quantifiable optimization problem; wherein the mathematical model includes: power generation constraint model, power balance constraint model, peak-valley difference and volatility constraint model, battery constraint model, phase change thermal storage system operation constraint model and water supply system operation constraint model.

[0008] The objective function of the optimized scheduling model is constructed by minimizing the total operating cost of the negative carbon building photovoltaic-storage-direct-flexible energy microgrid within the scheduling cycle; the total operating cost includes economic cost, environmental cost, and grid interaction optimization demand cost.

[0009] Preferably, the power generation constraint model, through the flexible and adjustable power generation characteristics of its gas turbine, effectively compensates for the fluctuation defects of photovoltaic power generation, achieving a smooth transition and continuous stability of power supply; specifically, it includes the following constraints:

[0010] Gas turbine constraints:

[0011] 0≤P g (t)≤P g max

[0012] Actual output constraints of photovoltaic power:

[0013] 0≤P pv (t)≤P pvmax (t)

[0014] In the formula: P g (t) represents the power generation of the gas turbine at time t; P pv (t) represents the actual photovoltaic power generation at time t; P represents the maximum power of the gas turbine generator; pv max (t) represents the photovoltaic power generation at time t.

[0015] Preferably, the power balance constraint model ensures that the negative carbon building photovoltaic-storage direct-drive flexible energy microgrid maintains stable power supply under various operating conditions, so as to avoid voltage and frequency anomalies caused by power imbalance and ensure the safe and reliable operation of various devices in the system; specifically, it includes the following constraints:

[0016] Electricity purchase and sale constraints:

[0017]

[0018] In the formula: u ex,sal (t), u ex,pur (t) represent the act of selling electricity to the power grid and the act of purchasing electricity from an external power grid, respectively; P ex,sal (t) represents the electricity sold at time t; P ex,pur (t) represents the power purchased at time t; These represent the maximum power sold and the maximum power purchased, respectively.

[0019] Power balance constraints:

[0020]

[0021] In the formula: P g (t) represents the power generation of the gas turbine at time t; P pv (t) represents the actual photovoltaic power generation at time t; P b,c (t) represents the battery charging power at time t; P b,d (t) represents the battery discharge power at time t; P hp (t) represents the power consumption of the heat pump at time t; P wp (t) represents the power consumption of the water pump at time t; P load (t) represents the load power at time t;

[0022] Thermal equilibrium constraint:

[0023]

[0024] In the formula: P pcm,c (t) represents the heat pump power of the phase change thermal storage system at time t; P pcm,d (t) represents the heat pump release power of the phase change thermal storage system at time t; η hp Indicates the electrothermal conversion efficiency of the heat pump; Q heat (t) represents the building's heat load power at time t;

[0025] Water balance constraints:

[0026]

[0027] In the formula: η wp P represents the water pump's water lifting efficiency. wc (t) represents the water inlet power of the water tank at time t; P wd (t) represents the water output power of the water tank at time t; Q water (t) represents the building water load power at time t.

[0028] Preferably, the peak-valley difference and volatility constraint model includes the following constraints:

[0029] Active peak-to-valley difference and volatility constraint:

[0030]

[0031] ΔP valley-to-peak =P max -P min

[0032] -P Lmax ≤P grid (t)≤P Lmax

[0033] In the formula: P grid(t) represents the active power exchanged with the power grid at time t; P max P min ΔP represents the maximum and minimum active power exchange of the power grid within a day, respectively. valley-to-peak P represents the peak-to-valley difference in active power. Lmax This indicates the maximum capacity of the AC-DC converter;

[0034] Reactive peak-to-valley difference and volatility constraints:

[0035] [P grid (t)] 2 +[Q grid (t)] 2 ≤(P Lmax ) 2

[0036]

[0037] ΔQ valley-to-peak =Q max -Q min

[0038] In the formula: Q grid (t) represents the reactive power exchanged with the grid at time t; Q max Q min ΔQ represents the maximum and minimum reactive power exchange of the power grid within a day, respectively. valley-to-peak This indicates the peak-to-valley difference in reactive power.

[0039] Preferably, the battery constraint model includes the following constraints:

[0040]

[0041]

[0042] In the formula: u b,c (t), u b,d (t) represent the charging and discharging behavior of the battery, respectively; These represent the rated charging power and discharging power of the battery, respectively; P b,c (t), P b,d (t) represent the charging power and discharging power of the battery at time t, respectively; η b Indicates the battery's charge and discharge efficiency; E b (t) represents the capacity of the battery at time t; Indicates the rated capacity of the battery; This indicates that the battery energy storage returns to its initial value when the scheduling ends.

[0043] Preferably, the operational constraint model of the phase change thermal storage system includes:

[0044]

[0045] In the formula: P hp (t) represents the electrical power consumed by the heat pump at time t; Indicates the rated power of the heat pump; P pcm,c (t) represents the heat pump power of the phase change thermal storage system at time t; η hp Indicates the electrothermal conversion efficiency of the heat pump; P pcm,d (t) represents the heat pump release power of the phase change thermal storage system at time t; E pcm (t) represents the thermal storage capacity of the phase change thermal storage system at time t; Indicates the rated capacity of the phase change thermal energy storage system; This indicates that the phase change thermal energy storage system returns to its initial value when the scheduling ends.

[0046] Preferably, the water supply system operation constraint model includes:

[0047]

[0048]

[0049] In the formula: P wt (t) represents the power consumption of the water pump at time t; u wp (t) represents the start / stop status of the water pump at time t; These represent the minimum and maximum operating power of the water pump, respectively; η wp P represents the water pump's water lifting efficiency. wc (t) represents the water inlet power of the water tank at time t; P wd (t) represents the water output power of the water tank at time t; E wt (t) represents the water tank's storage capacity at time t; This indicates the rated water storage capacity of the water tank.

[0050] Preferably, in the objective function, the total operating cost includes:

[0051] The economic cost items include the cost of power exchange with the main grid, the energy storage cost of the energy storage system, and the fuel consumption cost of the traditional generators in the system, in order to accurately quantify the economic expenditure of system operation;

[0052] The environmental cost item is calculated based on carbon emission factors to determine the cost of greenhouse gas emissions generated during operation, thereby reinforcing the constraints of low-carbon operation targets.

[0053] The power grid interaction optimization demand cost item introduces a penalty function mechanism to quantify and punish the behavior of power fluctuations between the microgrid and the main grid that affect the stability of the grid. By adding a penalty item, the friendly and coordinated operation of the microgrid and the main grid can be achieved, thereby realizing the goal of grid friendliness.

[0054] Preferably, the objective function is as follows:

[0055]

[0056] In the formula: C elec (t) represents the cost of exchanging electricity with the external power grid at time t; C represents the carbon emission cost at time t; storage (t) represents the energy storage cost at time t; P b,c (t), P b,d (t) represent the charging power and discharging power of the battery at time t, respectively; η b Indicates the battery's charge and discharge efficiency; C fuel (t) represents the fuel cost; P fuel (t) represents the fuel power generation at time t; λ represents the active power peak-to-valley difference penalty coefficient; ΔP valley-to-peak ξ represents the peak-to-valley difference; ξ represents the reactive power peak-to-valley difference bonus coefficient; ΔQ valley-to-peak p represents the peak-to-valley difference in reactive power. b Indicates the unit energy storage cost; λ carbon Indicates carbon price; e fuei Indicates the fuel carbon emission factor; c fuel Indicates fuel price; p ex,pur p ex,sal These represent the purchase price of electricity from the external power grid and the sales price of electricity, respectively; P ex,pur (t), P ex,sal (t) represents the power purchased from and sold to the external power grid at time t, respectively; T represents the time period (T = 24h); η fuel This indicates the efficiency of fuel power generation.

[0057] The present invention also provides a power-switching-friendly building-integrated photovoltaic-storage-direct-flexible microgrid day-ahead scheduling system, which executes the power-switching-friendly building-integrated photovoltaic-storage-direct-flexible microgrid day-ahead scheduling method as described above.

[0058] Compared with the prior art, the present invention has the following advantages:

[0059] The objective function of this invention is constructed around core objectives such as economy, environmental protection, and grid friendliness. Through mathematical modeling, the complex operational characteristics of a photovoltaic-storage-direct-current-flexible energy microgrid are transformed into a quantifiable optimization problem, providing a theoretical basis for the formulation and optimization of system scheduling strategies. This study adopts a multi-objective summation modeling approach, integrating economic costs, environmental costs, and grid interaction optimization requirements. The economic cost term includes the power exchange cost with the main grid, the energy storage cost of the energy storage system, and the fuel consumption cost of traditional generators in the system, accurately quantifying the economic expenditure of system operation. The environmental cost term is based on the carbon emission factor, calculating the cost of greenhouse gas emissions generated during operation, strengthening the constraint of low-carbon operation objectives. The grid interaction optimization term introduces a penalty function mechanism to quantify and punish behaviors affecting grid stability, such as power fluctuations between the microgrid and the main grid. By adding a penalty term, friendly and coordinated operation between the microgrid and the main grid is achieved, realizing the goal of grid friendliness. By introducing a thermal and water storage system, this invention significantly reduces costs in several areas (electricity exchange, carbon emissions, energy storage, and fuel oil) except for grid-friendly costs, demonstrating the positive role of thermal and water storage systems in optimizing costs, reducing carbon emissions, and decreasing fuel oil dependence. Attached Figure Description

[0060] Figure 1 This is a diagram showing the maximum photovoltaic output in the region, provided by the present invention.

[0061] Figure 2 The present invention provides a heat load diagram of the community at various times.

[0062] Figure 3 The present invention provides a water load diagram of the community at various times.

[0063] Figure 4 The present invention provides a diagram of the routine electricity load of the community at various times.

[0064] Figure 5 The power balance simulation diagram of Scheme 1 provided by the present invention.

[0065] Figure 6 The water power balance simulation diagram for Scheme 1 provided by the present invention.

[0066] Figure 7 The thermal power balance simulation diagram of Scheme 1 provided by the present invention.

[0067] Figure 8 The heat storage and release power diagram of Scheme 1 provided by the present invention.

[0068] Figure 9 The diagram shows the water storage and release power of Scheme 1 provided by the present invention.

[0069] Figure 10 The diagram shows the energy storage and release power of Scheme 1 provided by the present invention.

[0070] Figure 11 The power balance simulation diagram of Scheme 2 provided by the present invention.

[0071] Figure 12 The diagram shows the energy storage and release power of Scheme 2 provided by the present invention. Detailed Implementation

[0072] The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. The advantages and features of the present invention will become clearer from the following description. It should be noted that the drawings are all in a very simplified form and use non-precise proportions, and are only used to facilitate and clarify the illustration of the embodiments of the present invention.

[0073] This invention discloses a day-ahead dispatch method for a building-integrated photovoltaic-storage-direct-current flexible energy microgrid with power exchange friendliness. The method includes: constructing a mathematical model of the negative-carbon building-integrated photovoltaic-storage-direct-current flexible energy microgrid to transform its complex operating characteristics into a quantifiable optimization problem; wherein the mathematical model includes: a power generation constraint model, a power balance constraint model, a peak-valley difference and volatility constraint model, a battery constraint model, a phase change thermal energy storage system operation constraint model, and a water supply system operation constraint model; and constructing an objective function for the optimized dispatch model by minimizing the total operating cost of the negative-carbon building-integrated photovoltaic-storage-direct-current flexible energy microgrid within the dispatch cycle; wherein the total operating cost includes an economic cost item, an environmental cost item, and a grid interaction optimization demand cost item.

[0074] Further elaboration of the embodiments of the present invention reveals that photovoltaic power generation, as a clean energy source, possesses advantages such as environmental friendliness and renewability, and is widely used, promoting the exploration and application of green energy. However, because photovoltaic power generation is highly dependent on sunlight conditions, its output power fluctuates dramatically due to day-night cycles and changes in weather, exhibiting significant intermittency and uncertainty. To ensure the stable operation of the power system, traditional generators can be introduced as a stable support. Their flexible and adjustable power generation characteristics effectively compensate for the fluctuation defects of photovoltaic power generation, achieving a smooth transition and continuous stability of power supply. The power generation constraint model specifically includes the following constraints:

[0075] Gas turbine power generation P at time t g,i Within the generator output range, the gas turbine is constrained as follows:

[0076] 0≤P g (t)≤P g max (1)

[0077] Solar power output is affected by weather and time, constraining actual solar power output:

[0078] 0≤P pv (t)≤P pvmax (t) (2)

[0079] In the formula: P g (t) represents the power generation of the gas turbine at time t; P pv (t) represents the actual photovoltaic power generation at time t; P represents the maximum power of the gas turbine generator; pv max (t) represents the photovoltaic power generation at time t.

[0080] Further elaboration of the embodiments of the present invention reveals that the power balance constraint of the negative carbon building photovoltaic-storage-direct-connection-flexible energy microgrid is a key condition for ensuring its stable operation. Due to the susceptibility of new energy system integration to power balance issues caused by various factors, it is essential to manage power balance according to actual conditions. This requires that at any given time, the total power generation of the microgrid, the charging and discharging power of the energy storage system, and the power exchange with the main grid must match the load demand. The power balance constraint ensures that the negative carbon building energy microgrid maintains stable power supply under various operating conditions (such as sudden weather changes and load fluctuations), avoiding voltage and frequency anomalies caused by power imbalance, and ensuring the safe and reliable operation of various devices within the system. For example, through the coordinated regulation of energy storage and flexible loads, the uncertainties of photovoltaics can be effectively addressed, maintaining stable system operation.

[0081] The power balance constraint model specifically includes the following constraints:

[0082] At any given time, a microgrid can only be in one of three states: "purchasing electricity," "selling electricity," or "power balance." It cannot simultaneously purchase or sell electricity to the grid. For example, it can sell electricity to the grid when there is a surplus of photovoltaic power generation, and purchase electricity from the grid when there is a shortage of photovoltaic power generation.

[0083] Electricity purchase and sale constraints:

[0084]

[0085] In the formula: u ex,sal (t), u ex,pur (t) represent the act of selling electricity to the power grid and the act of purchasing electricity from an external power grid, respectively; P ex,sal (t) represents the electricity sold at time t; P ex,pur (t) represents the power purchased at time t; These represent the maximum power sold and the maximum power purchased, respectively.

[0086] Power balance is crucial for the stable operation of microgrids. At all times, generation must match load; otherwise, frequency or voltage instability will occur. Furthermore, it's necessary to distinguish between steady-state and dynamic conditions. In steady-state conditions, the equations relating generation, energy storage, grid interaction, and load must hold. In dynamic conditions, fluctuations and rapid response must be considered. The constraints for power balance must include generation capacity, energy storage charge / discharge rates, grid connection limitations, and load demand.

[0087] Power balance constraints:

[0088]

[0089] In the formula: P g (t) represents the power generation of the gas turbine at time t; P pv (t) represents the actual photovoltaic power generation at time t; P b,c (t) represents the battery charging power at time t; P b,d (t) represents the battery discharge power at time t; P hp (t) represents the power consumption of the heat pump at time t; P wp (t) represents the power consumption of the water pump at time t; P load (t) represents the load power at time t;

[0090] In integrated energy systems, thermal balance constraints are a core and crucial element, precisely regulating the energy flow at every stage of the entire thermal energy cycle, from the generation of heat sources to the dynamic adjustment of energy storage devices, as well as the unavoidable energy consumption during system operation. The essence of thermal balance constraints lies in achieving a match between the supply and demand of thermal energy and the system through a rigorous dynamic balance mechanism.

[0091] Thermal equilibrium constraint:

[0092]

[0093] In the formula: P pcm,c (t) represents the heat pump power of the phase change thermal storage system at time t; P pcm,d (t) represents the heat pump release power of the phase change thermal storage system at time t; η hp Indicates the electrothermal conversion efficiency of the heat pump; Q heat (t) represents the building's heat load power at time t;

[0094] Water balance constraints are a key factor in maintaining stable system operation. Water balance constraints stipulate that the total amount of water supply, storage release, and external water replenishment within the system must be equal to the total water demand, storage increment, and water network loss at any given time. This aims to ensure water supply security, improve water resource utilization, and further promote the coordinated optimization with the power and heating systems.

[0095] Water balance constraints:

[0096]

[0097] In the formula: η wp P represents the water pump's water lifting efficiency. wc (t) represents the water inlet power of the water tank at time t; P wd (t) represents the water output power of the water tank at time t; Q water (t) represents the building water load power at time t.

[0098] In a further description of the embodiments of the present invention, the peak-valley difference and volatility constraint model includes the following constraints:

[0099] On the one hand, the goal of "grid friendliness" is achieved by incorporating a peak-valley difference penalty term. Active power peak-valley difference and volatility constraints:

[0100]

[0101] ΔP valley-to-peak =P max -P min (14)-P Lmax ≤P grid (t)≤P Lmax (15)

[0102] In the formula: P grid (t) represents the active power exchanged with the power grid at time t; P max P min ΔP represents the maximum and minimum active power exchange of the power grid within a day, respectively. valley-to-peak P represents the peak-to-valley difference in active power. Lmax This indicates the maximum capacity of the AC-DC converter;

[0103] On the other hand, the photovoltaic-storage-DC-flexible microgrid is connected to the external power grid through an AC-DC structure, which can develop its reactive power support capability and achieve friendly interaction with the power grid, while mitigating reactive power peak-to-valley differences and volatility constraints.

[0104] [P grid (t)] 2 +[Q grid (t)] 2 ≤(P Lmax ) 2 (15-1)

[0105]

[0106] ΔQ valley-to-peak =Q max -Q min (14-1)

[0107] In the formula: Q grid (t) represents the reactive power exchanged with the grid at time t; Q max Q min ΔQ represents the maximum and minimum reactive power exchange of the power grid within a day, respectively. valley-to-peak This indicates the peak-to-valley difference in reactive power.

[0108] Further elaboration of the embodiments of the present invention reveals that in a grid-friendly photovoltaic-storage-DC-flexible energy microgrid system, the battery, as a crucial component of the energy storage system, plays a vital role in the system's peak-shaving and valley-filling performance, economy, safety, and reliability due to its operational constraints. These constraints not only affect the system's flexible adjustment capability during power load fluctuations but also relate to the overall economic benefits of the energy microgrid. Furthermore, they are essential factors in ensuring stable system operation and preventing hazards.

[0109] Battery capacity planning is a critical technical aspect, as batteries are a vital component of DC microgrid systems. Due to the volatility and uncertainty of renewable energy generation, batteries can assist renewable energy generation through charging and discharging, improving system stability. However, battery storage capacity is not unlimited. Reasonable battery capacity configuration requires comprehensive consideration of various factors, including microgrid load characteristics, photovoltaic output characteristics, and electricity consumption time characteristics. If the capacity is too low, the battery will struggle to meet load demands during peak electricity consumption periods or off-peak photovoltaic periods, leading to reduced power supply reliability. Conversely, if the capacity is too high, it will increase initial investment costs, require more floor space, and impose unnecessary maintenance burdens, reducing economic efficiency. The charging and discharging rates of batteries are also strictly limited. Excessively high charging rates can easily cause severe overheating within the battery, significantly shortening its cycle life and potentially leading to thermal runaway and other safety hazards, even fires and explosions. Similarly, excessively high discharging rates cause a rapid drop in battery voltage during discharge, compromising load stability and system stability, and causing irreversible damage to battery electrode materials, reducing battery performance and lifespan. From a safety operation perspective, batteries operating in microgrids must adhere to strict safety regulations. Preventing serious abnormalities such as overcharging, over-discharging, short circuits, and overheating is of paramount importance, as these issues will directly affect the safe and stable operation of the system.

[0110] Considering that batteries cannot be charged and discharged simultaneously within the same time period, a binary variable u is introduced. b,c (t), u b,d (t) represents the charge / discharge state of the battery, u b,c (t) = 1 or u b,d (t) = 1 indicates that the battery is charging or discharging.b,c (t) = 0 or u b,d (t) = 0 indicates that the battery is not being charged or discharged. To prevent damage to the battery, the charging and discharging power of the battery should be limited to a safe range. At the same time, considering the battery's service life, the remaining capacity of the battery also needs to be limited to a certain range.

[0111] The battery operation model is shown in equations (16) to (21). Equation (16) restricts the battery from being charged and discharged simultaneously at any time. Equations (17) and (18) indicate that the charging power and discharging power of the battery at any time cannot exceed the rated power. Equation (19) indicates that the energy storage of the battery at time t is determined by the energy storage at time t-1 and the charging and discharging power at time t. Equation (20) requires that the energy storage of the battery at time t cannot exceed the rated value. Equation (21) requires that the energy storage of the battery return to the initial value when the scheduling ends.

[0112] The battery constraint model includes the following constraints:

[0113]

[0114] In the formula: u b,c (t), u b,d (t) represent the charging and discharging behavior of the battery, respectively; These represent the rated charging power and discharging power of the battery, respectively; P b,c (t), P b,d (t) represent the charging power and discharging power of the battery at time t, respectively; η b Indicates the battery's charge and discharge efficiency; E b (t) represents the capacity of the battery at time t; Indicates the rated capacity of the battery; This indicates that the battery energy storage returns to its initial value when the scheduling ends.

[0115] Further elaboration of the embodiments of the present invention reveals that phase change thermal energy storage technology has broad application prospects in fields such as building energy conservation, thermal management of electronic devices and lithium batteries, industrial waste heat recovery, and power energy storage. The basic principle of phase change thermal energy storage is to store heat by utilizing the release and absorption of the latent heat of phase change in materials, characterized by high heat storage density and small temperature changes. Phase change thermal energy storage systems can efficiently store and precisely release thermal energy throughout the entire system. In grid-friendly photovoltaic-storage-direct-current-flexible energy microgrids, phase change thermal energy storage systems are a core element for achieving coordinated thermal and power dispatch. Phase change thermal energy storage systems deeply integrate the thermodynamic properties of phase change materials with the energy supply and demand characteristics of microgrids, playing a crucial role in the intermittent distribution of thermal and electrical energy. It can not only effectively buffer the intermittent fluctuations of distributed photovoltaic power generation but also dynamically balance thermal and electrical loads, providing a solid guarantee for improving the overall energy efficiency of energy microgrids and strengthening grid interaction capabilities, effectively improving the power supply reliability of the grid.

[0116] The charging and releasing rates of a phase change thermal energy storage system are limited by the thermophysical properties of the phase change material, its heat transfer performance, and the system's structural design. An excessively rapid charging rate can lead to localized overheating of the phase change material, disrupting the uniformity of the phase change process, reducing storage efficiency, and potentially damaging the storage device. Conversely, an excessively rapid releasing rate can cause a sudden drop in the phase change material's temperature, affecting its phase change characteristics and potentially failing to meet stable heat load requirements. During the charging process, it is typically necessary to control the charging power within a certain range to ensure slow and uniform heat absorption and achieve efficient heat storage. Phase change thermal energy storage systems must meet stringent safety requirements during operation. On one hand, it is crucial to prevent accidents such as leaks and explosions caused by abnormal conditions like high temperatures and high pressures, ensuring the safety of the system equipment. On the other hand, the safety of the phase change material must be considered, as some materials may be flammable or toxic. Appropriate fire prevention and poisoning prevention measures must be taken during storage, transportation, and use to ensure the safety of personnel and the environment. Furthermore, factors such as the system's installation location and ventilation conditions must be considered to avoid safety hazards caused by environmental factors.

[0117] The operational constraints of the phase change thermal energy storage system are shown in equations (22)-(28). Equation (22) indicates that the operating power of the heat pump at any given time cannot exceed the rated power. Equation (23) indicates the heat pump's electro-thermal conversion constraint. Equation (24) indicates that the energy storage of the phase change thermal energy storage system at time t is determined by the energy storage at time t-1 and the heat generation and release power of the heat pump at time t. Equation (25) requires that the energy storage of the phase change thermal energy storage system at time t cannot exceed the rated value. Equation (26) requires that the energy storage of the phase change thermal energy storage system return to its initial value when the scheduling ends.

[0118] The operational constraint model for the phase change thermal storage system includes:

[0119]

[0120] In the formula: P hp (t) represents the electrical power consumed by the heat pump at time t; Indicates the rated power of the heat pump; P pcm,c (t) represents the heat pump power of the phase change thermal storage system at time t; η hp Indicates the electrothermal conversion efficiency of the heat pump; P pcm,d (t) represents the heat pump release power of the phase change thermal storage system at time t; E pcm (t) represents the thermal storage capacity of the phase change thermal storage system at time t; Indicates the rated capacity of the phase change thermal energy storage system; This indicates that the phase change thermal energy storage system returns to its initial value when the scheduling ends.

[0121] In a further description of the embodiments of the present invention, the operating constraints of the water supply system are shown in equations (29)-(34). Among them, equation (29) restricts the operating power of the water pump at time t to be between the minimum operating power and the maximum operating power, equation (30) represents the relationship between the operating power of the water pump and the water inlet power of the water tank, equation (31) represents that the water storage of the water supply system at time t is determined by the water storage at time t-1 and the inlet and outlet power at time t, equation (32) requires that the water storage of the water supply system at time t cannot exceed the rated value, and equation (33) requires that the water storage of the water supply system return to the initial value when the scheduling ends.

[0122] The water supply system operation constraint model includes:

[0123]

[0124] In the formula: P wt (t) represents the power consumption of the water pump at time t; u wp (t) represents the start / stop status of the water pump at time t; These represent the minimum and maximum operating power of the water pump, respectively; η wp P represents the water pump's water lifting efficiency. wc (t) represents the water inlet power of the water tank at time t; P wd (t) represents the water output power of the water tank at time t; E wt (t) represents the water tank's storage capacity at time t; This indicates the rated water storage capacity of the water tank.

[0125] In further elaboration of the embodiments of the present invention, in the research of photovoltaic-storage-direct-current-flexible energy microgrids, the objective function is the core expression of the optimization scheduling model. The construction of the objective function usually revolves around core objectives such as economy, environmental protection, and grid friendliness. Through mathematical modeling, the complex operating characteristics of photovoltaic-storage-direct-current-flexible energy microgrids are transformed into quantifiable optimization problems, providing a theoretical basis for the formulation and optimization of system scheduling strategies. This study adopts a multi-objective summation modeling approach, integrating economic costs, environmental costs, and grid interaction optimization demand costs. The economic cost term includes the power exchange cost with the main grid, the energy storage cost of the energy storage system, and the fuel consumption cost of the traditional generators in the system, accurately quantifying the economic expenditure of system operation. The environmental cost term is based on the carbon emission factor, calculating the cost of greenhouse gas emissions generated during operation, strengthening the constraint of low-carbon operation objectives. The grid interaction optimization term introduces a penalty function mechanism to quantify and punish behaviors that affect grid stability, such as power fluctuations between the microgrid and the main grid. By adding a penalty term, friendly and coordinated operation between the microgrid and the main grid is achieved, realizing the goal of grid friendliness.

[0126] In the objective function, the total operating cost includes:

[0127] The economic cost items include the cost of power exchange with the main grid, the energy storage cost of the energy storage system, and the fuel consumption cost of the traditional generators in the system, in order to accurately quantify the economic expenditure of system operation;

[0128] The environmental cost item is calculated based on carbon emission factors to determine the cost of greenhouse gas emissions generated during operation, thereby reinforcing the constraints of low-carbon operation targets.

[0129] The power grid interaction optimization demand cost item introduces a penalty function mechanism to quantify and punish the behavior of power fluctuations between the microgrid and the main grid that affect the stability of the grid. By adding a penalty item, the friendly and coordinated operation of the microgrid and the main grid can be achieved, thereby realizing the goal of grid friendliness.

[0130] In a further explanation of the embodiments of the present invention, the objective function is as follows:

[0131]

[0132]

[0133] In the formula: C elec (t) represents the cost of exchanging electricity with the external power grid at time t; C represents the carbon emission cost at time t; storage (t) represents the energy storage cost at time t; P b,c (t), P b,d(t) represent the charging power and discharging power of the battery at time t, respectively; η b Indicates the battery's charge and discharge efficiency; C fuel (t) represents the fuel cost; P fuel (t) represents the fuel power generation at time t; λ represents the active power peak-to-valley difference penalty coefficient; ΔP valley-to-peak ξ represents the peak-to-valley difference; ξ represents the reactive power peak-to-valley difference bonus coefficient; ΔQ valley-to-peak p represents the peak-to-valley difference in reactive power. b Indicates the unit energy storage cost; λ carbon Indicates carbon price; e fuei Indicates the fuel carbon emission factor; c fuel Indicates fuel price; p ex,pur p ex,sal These represent the purchase price of electricity from the external power grid and the sales price of electricity, respectively; P ex,pur (t), P ex,sal (t) represents the power purchased from and sold to the external power grid at time t, respectively; T represents the time period (T = 24h); η fuel This indicates the efficiency of fuel power generation.

[0134] The present invention also provides a power-switching-friendly building-integrated photovoltaic-storage-direct-flexible microgrid day-ahead scheduling system, which executes the power-switching-friendly building-integrated photovoltaic-storage-direct-flexible microgrid day-ahead scheduling method as described above.

[0135] Furthermore, embodiments of the present invention also include the following simulation process:

[0136] (1) Basic data; the water load, heat load, and regular electricity load of the community at various times are known, such as Figures 2-4 As shown in the figure. This embodiment of the invention studies the electricity price setting based on the industrial and commercial electricity policy of Henan Province. The electricity purchase price adopts a time-of-use pricing mechanism, dividing the day into three periods: peak period from 16:00 to 24:00, off-peak period from 0:00 to 6:00 and 11:00 to 14:00, and the remaining periods are flat periods. The electricity price fluctuation ratio follows a uniform standard throughout the year, with the peak, flat, and off-peak electricity price ratio adjusted to 1.72:1:0.45. The flat period price is set at 0.56 yuan / kWh, resulting in a peak price of 0.9632 yuan / kWh and an off-peak price of 0.252 yuan / kWh. The electricity sales price adopts a fixed benchmark price of approximately 0.3949 yuan / kWh, which does not fluctuate over time, ensuring the stability of revenue calculation. This electricity price setting scheme not only conforms to local policy realities but also provides a reliable quantitative basis for the economic analysis of photovoltaic-storage-DC-flexible systems.

[0137] Power generation equipment: The generator has a rated maximum power of 800 kilowatts and serves as backup power support for the system;

[0138] Electrochemical energy storage: The battery has bidirectional power regulation capability, with a maximum charging and discharging power of 500 kW and a maximum energy storage capacity of 2000 kWh. The single charge-discharge cycle efficiency is 90%, and the initial energy storage state when the system starts is 50% of the full capacity, i.e., 1000 kWh.

[0139] Thermal energy storage system: The phase change thermal energy storage device is equipped with a heat pump with a maximum power of 600 kW, a heat pump efficiency of 2.6, a maximum thermal energy storage capacity of 3000 kWh, and an initial energy storage state of 50% of full capacity, that is, an initial heat storage capacity of 1500 kWh.

[0140] Water supply and energy storage unit: The water pump has a maximum power of 500 kW and an operating efficiency of 85%. The water tank serves as the water energy storage carrier, with a maximum water storage capacity equivalent to 2000 kWh. The initial energy storage state is 50% of full capacity, i.e., the initial water storage volume is 1000 kWh. The parameters of each device work together to form the basic constraints for system operation, providing a quantitative basis for energy dispatch and load balancing.

[0141] Economic and environmental parameters: The carbon trading price is set at 0.085 yuan / kg, the carbon emission factor for fuel power generation is 0.8 kg / kWh, the fuel price is 1.0 yuan / kWh, and the power generation efficiency is 0.8. Energy storage costs are calculated using a tiered pricing system: a full charge-discharge cycle cost of 0.5 yuan / kWh and a single charge or discharge process cost of 0.25 yuan / kWh. The time scale is divided into 1-hour intervals for intraday dispatch optimization. Furthermore, to enhance grid friendliness, a peak-valley difference penalty coefficient of 3 is set to dynamically constrain power fluctuations between the system and the grid, ensuring a smooth power curve and improving grid collaborative operation capabilities.

[0142] (2) Model simulation analysis; To verify the superiority of the proposed strategy, two schemes are set up for comparison:

[0143] ① Scheme 1 (the scheme proposed in this invention): Considering thermal and water storage systems.

[0144] ② Option 2 (Comparative Option): Without considering thermal and water storage systems, the other conditions are the same as Option 1.

[0145] The simulation results of Scheme 1 are as follows Figure 5 As shown, in grid-friendly energy microgrid systems, power balance is crucial for ensuring stable operation. When photovoltaic power generation is at its peak (e.g., ... Figure 5During the 10-15 hour window, the heat pump exhibits high power consumption (significant negative power), directly absorbing a large amount of photovoltaic power, reducing curtailment and improving the utilization rate of clean energy. When photovoltaic power generation is insufficient (such as during early morning and evening hours), the external power grid provides positive input (purchasing electricity from the external grid), supplementing the system's power gap. Working in conjunction with energy storage devices, it meets the energy demands of internal loads (including heat pumps, conventional loads, water pumps, etc.), ensuring that the microgrid can achieve power balance and maintain stable operation under different power generation conditions. This multi-source collaborative and flexible control model demonstrates the grid-friendly microgrid's adaptability to energy fluctuations and its efficient absorption capacity.

[0146] Water towers balance supply and demand by dynamically adjusting the water release rate, such as... Figure 6 As shown, water demand is low during the first 1-5 hours, and the water tower releases little water as well; after 5 hours, water demand gradually increases, and the water tower releases water accordingly; during system operation, the water tower continuously adjusts the water release according to fluctuations in water demand to ensure a stable water supply.

[0147] Phase change materials (PCMs) balance heat supply and demand by dynamically adjusting their heat release. When heat load demand is high, the heat release of the PCM increases; when heat load demand is low, the heat release decreases accordingly. During this period, the PCM continuously adjusts its heat release according to fluctuations in heat load demand. This response mechanism demonstrates the crucial role of PCMs in regulating heat balance, ensuring that the system's heat demand is met at different times.

[0148] Figure 8 The data clearly outlines the dynamic relationship between heat storage / release power and the thermal storage state of charge (SOC). When the heat storage / release power is greater than 0, indicating the heat storage phase, the SOC steadily increases; when the heat storage / release power is less than 0, indicating the heat release phase, the SOC decreases accordingly. During the 10-15 hour period, the significant heat storage process causes the SOC to rise rapidly. In other periods, the SOC dynamically adjusts based on the positive / negative characteristics and magnitude of the heat storage / release power. This process reveals the thermal storage system's ability to balance energy storage and release.

[0149] Figure 9 This visually demonstrates the intrinsic relationship between water storage / release power and the state of matter (SOC) of the stored water. When the water storage / release power is greater than 0, indicating a water storage state, the SOC of the stored water shows an upward trend; conversely, when the water storage / release power is less than 0, indicating a water release state, the SOC of the stored water decreases accordingly. During the 10-15 hour period, the intense water storage process drives the rapid accumulation of SOC in the stored water. During other periods, the SOC of the stored water dynamically adjusts according to the positive and negative characteristics and magnitude of the water storage / release power. This process clearly reflects the precise control capability of the water storage system over water storage and release, fully demonstrating the water resource balancing mechanism of the water storage system at different times.

[0150] Figure 10 The diagram clearly demonstrates the intrinsic relationship between energy storage and release power and the energy storage state of charge (SOC). When the energy storage and release power is greater than 0, the system is in a storage state, and the SOC increases accordingly. Conversely, when the energy storage and release power is less than 0, the system is in a release state, and the SOC decreases accordingly. At different times, the system dynamically adjusts the SOC through charging and discharging operations. This process clearly reflects the balance mechanism between energy storage and release, fully demonstrating the energy storage system's precise control over electrical energy.

[0151] Overall, the system significantly reduces its dependence on the external power grid through photovoltaic-storage complementarity, multi-energy synergy, and time-sharing dispatch. The energy storage SOC remains within a reasonable range, meeting the requirements of grid friendliness and negative carbon targets. By equipping the system with energy storage, in addition to providing emergency power during unforeseen circumstances, the stored surplus photovoltaic power can also play a role in peak shaving for daily building electricity consumption. The energy storage system not only reduces electricity operating costs and load losses but also improves the utilization rate of renewable energy. Further optimization could consider increasing the depth of energy storage charging during off-peak electricity price periods or dynamically adjusting gas turbine output based on forecast data to improve economic efficiency and low carbon footprint.

[0152] The simulation results of Scheme 2 are as follows Figure 11 As shown: Photovoltaic power output peaks around 10-15 AM, reflecting typical characteristics of photovoltaic power generation. High power generation occurs during periods of ample sunshine, making it the primary power source during this time. Gas turbines have some power output around 6-10 PM, indicating their role as a supplementary power source during periods of insufficient photovoltaic power output (e.g., evening to night). Power exchange with the external grid has some output at different times, especially during photovoltaic off-peak hours, playing a role in power regulation and balancing system power supply and demand. Batteries have significant positive power output during peak photovoltaic power generation (10-15 AM), being in a charging state; during off-peak hours (e.g., 6-10 PM), they have negative power output, being in a discharging state, thus regulating energy storage and release. Heat pumps have power output during certain periods for heating and other needs; their operation is related to power supply and heat demand. Water pumps have negative power output during some periods; due to the lack of heat and water storage systems, their role and power contribution in the system are relatively limited.

[0153] like Figure 12 As shown, the stored and released power is closely related to the State of Charge (SOC). Discharging directly leads to a decrease in SOC, while charging (blue positive) causes SOC to increase. The dynamic changes of these two processes reflect the "storage-release" process of energy in the energy storage system.

[0154] Compared with Option 1 Figure 5 compared to, Figure 11 The negative output of the medium-pressure water pump is not significant and is relatively rare; Figure 5During the middle period (e.g., 10-15 o'clock), the water pump outputs significantly and with a large amplitude, indicating that after the introduction of the thermal and water storage system, the water pump needs to cooperate with the system's energy storage and release process, making its operation more complex and requiring stronger regulation. Figure 5 The photovoltaic output is higher during peak hours (such as 10-3 PM). Combined with a thermal and water storage system, it is possible to absorb the photovoltaic power through adjustments made by other equipment (such as water pumps). Moreover, the thermal and water storage system expands the output variation range of some components, resulting in a wider dynamic range for system regulation. By comparing the two schemes, it was found that the thermal and water storage system enhances the complexity of interactions between components within the system by altering the operating logic and intensity of components such as water pumps, thus enabling more precise energy management.

[0155] (3) Economic analysis;

[0156] Table 1 Costs

[0157]

[0158] In summary, cost analysis revealed that Scheme 1, which incorporates thermal and water storage, is less expensive than Scheme 2. Introducing a thermal and water storage system significantly reduces costs beyond grid-friendly aspects (electricity exchange, carbon emissions, energy storage, and fuel oil), demonstrating the positive effects of thermal and water storage systems in optimizing costs, reducing carbon emissions, and decreasing fuel oil dependence. Calculations showed that incorporating thermal and water storage systems reduces costs by 32.65% compared to the comparative schemes.

[0159] The above description is merely a description of preferred embodiments of the present invention and is not intended to limit the scope of the present invention in any way. Any changes or modifications made by those skilled in the art based on the above disclosure shall fall within the protection scope of the claims.

Claims

1. A day-ahead scheduling method for a building-integrated photovoltaic-storage-direct-drive flexible energy microgrid with power exchange friendliness, characterized in that, include: By constructing a mathematical model of a negative carbon building photovoltaic-storage direct-flexible energy microgrid, the complex operating characteristics of the negative carbon building photovoltaic-storage direct-flexible energy microgrid are transformed into a quantifiable optimization problem. The mathematical models mentioned include: power generation constraint model, power balance constraint model, peak-valley difference and volatility constraint model, battery constraint model, phase change thermal storage system operation constraint model, and water supply system operation constraint model; The objective function of the optimized scheduling model is constructed by taking the minimum total operating cost within the scheduling cycle of the negative carbon building photovoltaic-storage direct-flexible energy microgrid. The total operating cost includes economic costs, environmental costs, and costs related to power grid interaction optimization.

2. The day-ahead scheduling method for a power-switching-friendly building-integrated photovoltaic-storage-direct-drive flexible energy microgrid as described in claim 1, characterized in that, The power generation constraint model, through the flexible and adjustable power generation characteristics of its gas turbine, effectively compensates for the fluctuation defects of photovoltaic power generation, achieving a smooth transition and continuous stability of power supply; specifically, it includes the following constraints: Gas turbine constraints: 0≤P g (t)≤P g max Actual output constraints of photovoltaic power: 0≤P pv (t)≤P pvmax (t) In the formula: P g (t) represents the power generation of the gas turbine at time t; P pv (t) represents the actual photovoltaic power generation at time t; P g max P represents the maximum power of the gas turbine generator; pv max (t) represents the photovoltaic power generation at time t.

3. The day-ahead scheduling method for a power-switching-friendly building-integrated photovoltaic-storage-direct-drive flexible energy microgrid as described in claim 1, characterized in that, The power balance constraint model ensures that the negative carbon building photovoltaic-storage direct current-flexible energy microgrid maintains stable power supply under various operating conditions, so as to avoid voltage and frequency anomalies caused by power imbalance and ensure the safe and reliable operation of various devices in the system; specifically, it includes the following constraints: Electricity purchase and sale constraints: In the formula: u ex,sal (t), u ex,pur (t) represent the act of selling electricity to the power grid and the act of purchasing electricity from an external power grid, respectively; P ex,sal (t) represents the electricity sold at time t; P ex,pur (t) represents the power purchased at time t; These represent the maximum power sold and the maximum power purchased, respectively. Power balance constraints: In the formula: P g (t) represents the power generation of the gas turbine at time t; P pv (t) represents the actual photovoltaic power generation at time t; P b ,c (t) represents the battery charging power at time t; P b,d (t) represents the battery discharge power at time t; P hp (t) represents the power consumption of the heat pump at time t; P wp (t) represents the power consumption of the water pump at time t; P load (t) represents the load power at time t; Thermal equilibrium constraint: In the formula: P pcm,c (t) represents the heat pump power of the phase change thermal storage system at time t; P pcm,d (t) represents the heat pump release power of the phase change thermal storage system at time t; η hp Indicates the electrothermal conversion efficiency of the heat pump; Q heat (t) represents the building's heat load power at time t; Water balance constraints: In the formula: η wp P represents the water pump's water lifting efficiency. wc (t) represents the water inlet power of the water tank at time t; P wd (t) represents the water output power of the water tank at time t; Q water (t) represents the building water load power at time t.

4. The day-ahead scheduling method for a power-switching-friendly building-integrated photovoltaic-storage-direct-drive flexible energy microgrid as described in claim 1, characterized in that, The peak-valley difference and volatility constraint model includes the following constraints: Active peak-to-valley difference and volatility constraint: ΔP valley-to-peak =P max -P min -P Lmax ≤P grid (t)≤P Lmax In the formula: P grid (t) represents the active power exchanged with the power grid at time t; P max P min ΔP represents the maximum and minimum active power exchange of the power grid within a day, respectively. valley-to-peak P represents the peak-to-valley difference in active power. Lmax This indicates the maximum capacity of the AC-DC converter; Reactive peak-to-valley difference and volatility constraints: [P grid (t)] 2 +[Q grid (t)] 2 ≤(P Lmax ) 2 ΔQ valley-to-peak =Q max -Q min In the formula: Q grid (t) represents the reactive power exchanged with the grid at time t; Q max Q min ΔQ represents the maximum and minimum reactive power exchange of the power grid within a day, respectively. valley-to-peak This indicates the peak-to-valley difference in reactive power.

5. A day-ahead scheduling method for a building-integrated photovoltaic-storage-direct-drive flexible energy microgrid with power exchange friendliness as described in claim 1, characterized in that, The battery constraint model includes the following constraints: In the formula: u b,c (t), u b,d (t) represent the charging and discharging behavior of the battery, respectively; These represent the rated charging power and discharging power of the battery, respectively; P b,c (t), P b,d (t) represent the charging power and discharging power of the battery at time t, respectively; η b Indicates the battery's charge and discharge efficiency; E b (t) represents the capacity of the battery at time t; Indicates the rated capacity of the battery; This indicates that the battery energy storage returns to its initial value when the scheduling ends.

6. A day-ahead scheduling method for a power-switching-friendly building-integrated photovoltaic-storage-direct-drive flexible energy microgrid as described in claim 1, characterized in that, The operational constraint model for the phase change thermal storage system includes: In the formula: P hp (t) represents the electrical power consumed by the heat pump at time t; Indicates the rated power of the heat pump; P pcm,c (t) represents the heat pump power of the phase change thermal storage system at time t; η hp Indicates the electrothermal conversion efficiency of the heat pump; P pcm,d (t) represents the heat pump release power of the phase change thermal storage system at time t; E pcm (t) represents the thermal storage capacity of the phase change thermal storage system at time t; Indicates the rated capacity of the phase change thermal energy storage system; This indicates that the phase change thermal energy storage system returns to its initial value when the scheduling ends.

7. A day-ahead dispatching method for a power-switching-friendly building-integrated photovoltaic-storage-direct-drive flexible energy microgrid as described in claim 1, characterized in that, The water supply system operation constraint model includes: In the formula: P wt (t) represents the power consumption of the water pump at time t; u wp (t) represents the start / stop status of the water pump at time t; These represent the minimum and maximum operating power of the water pump, respectively; η wp P represents the water pump's water lifting efficiency. wc (t) represents the water inlet power of the water tank at time t; P wd (t) represents the water output power of the water tank at time t; E wt (t) represents the water tank's storage capacity at time t; This indicates the rated water storage capacity of the water tank.

8. A day-ahead scheduling method for a building-integrated photovoltaic-storage-direct-drive flexible energy microgrid with power exchange friendliness as described in claim 1, characterized in that, In the objective function, the total operating cost includes: The economic cost items include the cost of power exchange with the main grid, the energy storage cost of the energy storage system, and the fuel consumption cost of the traditional generators in the system, in order to accurately quantify the economic expenditure of system operation; The environmental cost item is calculated based on carbon emission factors to determine the cost of greenhouse gas emissions generated during operation, thereby reinforcing the constraints of low-carbon operation targets. The power grid interaction optimization demand cost item introduces a penalty function mechanism to quantify and punish the behavior of power fluctuations between the microgrid and the main grid that affect the stability of the grid. By adding a penalty item, the friendly and coordinated operation of the microgrid and the main grid can be achieved, thereby realizing the goal of grid friendliness.

9. A day-ahead scheduling method for a building-integrated photovoltaic-storage-direct-drive flexible energy microgrid with power exchange friendliness as described in claim 8, characterized in that, The objective function is as follows: In the formula: C elec (t) represents the cost of exchanging electricity with the external power grid at time t; C represents the carbon emission cost at time t; storage (t) represents the energy storage cost at time t; P b,c (t), P b,d (t) represent the charging power and discharging power of the battery at time t, respectively; η b Indicates the battery's charge and discharge efficiency; C fuel (t) represents the fuel cost; P fuel (t) represents the fuel power generation at time t; λ represents the active power peak-to-valley difference penalty coefficient; ΔP valley-to-peak ξ represents the peak-to-valley difference; ξ represents the reactive power peak-to-valley difference bonus coefficient; ΔQ valley-to-peak p represents the peak-to-valley difference in reactive power. b Indicates the unit energy storage cost; λ carbon Indicates carbon price; e fuei Indicates the fuel carbon emission factor; c fuel Indicates fuel price; p ex,pur p ex,sal These represent the purchase price of electricity from the external power grid and the sales price of electricity, respectively; P ex,pur (t), P ex,sal (t) represents the power purchased from and sold to the external power grid at time t, respectively; T represents the time period (T = 24h); η fuel This indicates the efficiency of fuel power generation.

10. A power-switching-friendly building-integrated photovoltaic-storage-direct-drive flexible energy microgrid day-ahead dispatching system, characterized in that: Implement a day-ahead scheduling method for a building-integrated photovoltaic-storage-direct-flexible energy microgrid with power exchange friendliness as described in any one of claims 1 to 9.

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