Collaborative optimization scheduling strategy of electricity-heat-hydrogen comprehensive energy system in differentiated operation mode

Abstract

The invention provides a collaborative optimization scheduling strategy of an electric-thermal-hydrogen comprehensive energy system in a differentiated operation mode. The method comprises the following steps: firstly, establishing an electricity-hydrogen-heat comprehensive energy system, and respectively establishing WEHP module unified operation models of three electrolysis technologies, an HFC model considering thermoelectric coupling, an HSD model and a heat energy circulation system model; in an off-grid operation mode, supply and demand balance of electric power and heat energy is considered, and an objective function and corresponding constraints for minimizing the daily operation cost of the IES are designed. In a grid-connected operation mode, the IES participates in market transaction according to time-of-use electricity price and hydrogen energy transaction price, a target function considering electric power and hydrogen energy transaction cost is designed, and electric energy balance and tie line power constraint are established. And finally, converting the collaborative optimization scheduling model of the IES into a mixed integer linear model through a piecewise linearization method, establishing a collaborative optimization scheduling model in a differentiated operation mode, and solving the collaborative optimization scheduling model.

Description

Technical Field

[0001] The present invention belongs to the field of coordinated scheduling of integrated energy systems, and specifically relates to a coordinated optimization scheduling strategy for an electric-heat-hydrogen integrated energy system under a differentiated operation mode. Background Art

[0002] In the existing technology, as the penetration rate of renewable energy in the integrated energy system (IES) continues to increase, how to improve the utilization rate of renewable energy has become a key issue. Water electrolysis for hydrogen production (WEHP) technology has become an important means to solve this problem because it can convert excess renewable energy electricity into hydrogen storage. However, it is difficult to meet the diverse needs of complex energy systems by relying solely on a single WEHP system. Therefore, it is of great significance to study the combination of WEHP with flexible resources such as hydrogen fuel cells (HFC) to construct a coordinated optimization scheduling strategy for an electric-heat-hydrogen integrated energy system, which has broad application prospects.

[0003] At present, the dispatch optimization of the electricity-heat-hydrogen integrated energy system mainly faces the following problems:

[0004] 1. Lack of a unified operation model for WEHP modules. Different WEHP technologies vary significantly in performance, cost, and operating characteristics. Current research often models only a single technology, making it difficult to achieve unified management of WEHP modules. This limitation hinders the coordinated optimization of hydrogen production, storage, and utilization within an integrated energy system.

[0005] 2. The impact of errors in renewable energy generation forecast data. Renewable energy (such as photovoltaic and wind power) generation has strong randomness and volatility. Forecast errors will lead to an imbalance in energy supply and demand, which in turn affects the operating economy and reliability of the system. Although some studies have proposed some forecast correction methods, the improvement of forecast accuracy for complex systems is still insufficient.

[0006] 3. The scheduling model is complex to solve. The scheduling problem of an integrated energy system usually involves the coupling and optimization of multiple energy forms (such as electricity, thermal energy, and hydrogen energy). Its core is a complex nonlinear optimization problem that requires considering both the energy supply and demand balance in a time series and the dynamic switching of different modes (grid-connected and off-grid). This multi-objective and multi-constraint feature makes traditional solution methods less efficient when dealing with large-scale systems, and it is difficult to meet the requirements of practical applications for fast response and high-precision results. How to improve solution efficiency through effective algorithm design or problem linearization becomes the key.

[0007] 4. Lack of comprehensive evaluation of economy and reliability. Existing research usually takes reducing operating costs as the main goal in optimizing scheduling, but ignores the importance of system operation reliability, resulting in poor stability of scheduling schemes in practical applications. Reliability issues are mainly reflected in the lack of rationality of equipment output and the system's weak ability to respond to prediction errors and emergencies. For example, overload operation of equipment may reduce its service life, while ignoring hydrogen storage capacity and transportation costs will increase operational uncertainty. Therefore, it is necessary to further explore scheduling methods that can comprehensively evaluate economy and reliability to ensure cost optimization while improving the overall robustness and sustainability of the system. Summary of the invention

[0008] In view of the shortcomings of the prior art, this application proposes a coordinated optimization scheduling strategy for the electric-heat-hydrogen integrated energy system under differentiated operation modes. The innovative points of the invention are as follows:

[0009] 1. Focus on the analysis of hydrogen production, storage and utilization, and analyze the differences in thermodynamic and electrochemical mechanisms of the three WEHP technologies. From the three aspects of cost, flexibility and efficiency, a WEHP general operation model and an HFC waste heat recovery model were established, which solved the problem of inconsistent mathematical forms of WEHP efficiency characteristic models, met the technical and economic performance requirements of actual engineering projects, and contributed to the low-carbon transformation of power production.

[0010] 2. Taking into account the uncertainty of light intensity and wind speed, the output prediction curves of photovoltaic and wind turbines are corrected to ensure the accuracy of renewable energy output prediction in the coordinated optimization scheduling process. On the one hand, it can optimize equipment output and effectively extend equipment life; on the other hand, it can improve the operational reliability of IES.

[0011] 3. Aiming at the optimal operating cost under collaborative optimization dispatch, taking into full account factors such as renewable energy absorption capacity, transportation costs and operation of various equipment, a collaborative optimization dispatch model for the electric-heat-hydrogen integrated energy system in grid-connected / off-grid operation mode was established. This model can effectively reflect the impact of sensitive factors such as renewable energy penetration, electricity prices and hydrogen price fluctuations on dispatch results.

[0012] 4. The obtained scheduling scheme has a wide range of application scenarios and good economic benefits. It can reasonably arrange the operation time of various WEHPs from the three aspects of cost, flexibility and efficiency, realize HFC waste heat recovery, alleviate the insufficient consumption of renewable energy, and promote the low-carbon transformation of power production, which has higher engineering value.

[0013] The present invention takes the electric-heat-hydrogen integrated energy system model as the application object, and performs collaborative optimization scheduling under differentiated operation modes. The electric-heat-hydrogen complementary coordination mechanism utilizes the electricity cut by photovoltaic (PV) and wind power generation (WT) to produce hydrogen in the off-grid operation mode to achieve electric-hydrogen coupling. During peak load, hydrogen energy is supplied to hydrogen fuel cells (HFC) for "joint power generation" to achieve the coupling of electric heat and hydrogen energy. In the grid-connected operation mode, electric-hydrogen coupling is achieved through the production of hydrogen by photovoltaic and wind power generation cuts and hydrogen production during valley loads. During peak load, part of the hydrogen energy is sold to hydrogen stations, and the remaining hydrogen energy is supplied to HFC for "joint power generation" to achieve the coupling of electric heat and hydrogen energy. Therefore, the electric-heat-hydrogen coupling model consists of a WEHP model and an HFC model.

[0014] Step 1: Mathematical model of the electricity-heat-hydrogen integrated energy system

[0015] Energy supply links (such as renewable energy generation (RE) and public grid (UG)), energy conversion links (such as combined heat and power units (CHP), electric boilers (EB), hydrogen fuel cells (HFC) and WEHP, and energy storage links (such as hydrogen storage devices HSD). This section mainly establishes the analysis models of the WEHP model, the "combined heat and power" HFC characteristic model, the hydrogen storage device model and the thermal system model in the integrated electricity-heat-hydrogen energy system. The specific contents are described as follows.

[0016] A unified operation model of WEHP modules applicable to the three electrolysis technologies, a hydrogen production model of WEHP, and three working states and power consumption models of WEHP modules were established.

[0017] To establish the HFC model, in order to make the HFC output the required power, the invention considers N HFC The hydrogen fuel cells are connected in series. The operation of HFC generates more heat energy while generating electricity. The transportation cost model of hydrogen storage device for the coordinated optimization scheduling of the electric-heat-hydrogen integrated energy system is established as shown below. The total transportation cost of the hydrogen storage device can be calculated by the total amount of hydrogen energy that needs to be transported at the end of the scheduling period. Considering the transportation time of the hydrogen storage device, a time period needs to be reserved before the end of the scheduling period to constrain the capacity of the hydrogen storage device and ensure the implementation of the scheduling plan.

[0018] Establish a thermal energy system model. First, establish a thermal balance model of the thermal energy system. The electric-heat-hydrogen integrated energy system uses HFC, CHP and EB as heat sources, and uses heat exchangers as media to achieve heat energy transmission through the pipeline network. The above three together constitute a thermal energy circulation system. Then establish a thermal balance model of the thermal energy system. In the electric-heat-hydrogen integrated energy system model, the thermoelectric coupling equipment includes HFC, CHP and EB, which are all controllable devices. Among them, HFC and CHP generate electricity and heat at the same time, and the three together enhance the flexibility of heat and electricity conversion in IES. HFC determines the ratio of electricity and heat output by controlling the hydrogen supply rate and operating temperature. CHP uses a constant heat-to-electricity ratio for energy supply. EB can convert electricity into heat energy with a conversion efficiency of more than 90%. EB is installed in IES to meet the heating load demand, which can reduce the consumption of natural gas.

[0019] Based on historical data, a support vector machine model is established for short-term forecasting of renewable energy generation. Then, an idealized wind turbine power model is established and represented as a piecewise function. At the same time, a photovoltaic (PV) output power model is established. Since wind speed and light intensity are the main factors causing uncertainty in renewable energy generation, predictions are made in combination with the predicted sampling points of renewable energy generation, and then the predicted values ​​of renewable energy generation are corrected.

[0020] The electric-heat-hydrogen integrated energy system has two operating modes, namely off-grid mode and grid-connected mode. In the off-grid operation mode, WEHP and HFC, as controllable equipment of the electric-heat-hydrogen integrated energy system, play a role in achieving the "source-load" balance of the system and stabilizing the fluctuation of renewable energy power generation. In the grid-connected operation mode, electricity and hydrogen energy participate in market transactions, which can not only improve the energy supply reliability of the electric-heat-hydrogen integrated energy system, but also reduce daily operating costs through energy sales.

[0021] In the off-grid operation mode, there is no power exchange between IES and the grid, and the supply and demand balance of electricity and thermal energy is maintained by optimizing the output of each device in IES. The objective function to minimize the daily operating cost of IES is as follows:

[0022] minf tot,l =C RE +C cur +C WEHP +C HSD +C HFC +C EB +C gas

[0023]

[0024]

[0025] In the above formula, in the formula, f tot,l is the daily operating cost of IES in off-grid operation mode. T is the dispatch period. C RE is the electricity generation cost of photovoltaic and wind power. cur It is the penalty cost of “abandoning wind and solar power”. WEHP is the operating cost of WEHP. HSD is the hydrogen storage cost. C HFC , C EB and C CHP are the daily operating cost coefficients of HFC, EB and CHP respectively. PV and λ WT They are the daily operating cost coefficients of photovoltaic and wind power generation, with values ​​of 0.0235 and 0.0196 respectively. and are the output powers of photovoltaic and wind power generation at time t respectively. and are the fixed costs of photovoltaic and wind power generation respectively. and It is the penalty cost coefficient for “abandoning wind and solar power”. and is the power reduction of wind power and photovoltaic power generation at time t. N WEHP is the total number of WEHP modules. is the cost coefficient of the Mth module. is the fixed daily operating cost of the Mth module. HSD is the hydrogen storage cost coefficient. is the fixed maintenance cost of HSD. HFC is the daily operating cost coefficient of HFC. is the output power of the hydrogen fuel cell at time t. η HFC is the operating efficiency of the hydrogen fuel cell. is the fixed maintenance cost of the hydrogen fuel cell. EB It is the daily operating cost coefficient of EB. is the fixed maintenance cost of the electric boiler. gas is the price of natural gas. CHP , b CHP and c CHP is the fuel cost factor for CHP. is the fixed maintenance cost of the combined heat and power plant.

[0026] According to the actual situation of the off-grid operation mode of the electric-heat-hydrogen integrated energy system, constraints are designed to ensure the stability and economy of the system.

[0027] In the grid-connected operation mode, the integrated energy system (IES) participates in market transactions based on the time-of-use electricity price and hydrogen energy trading price, and its objective function is shown in the following formula. The objective function based on the off-grid operation mode adds additional transaction costs for electricity and hydrogen energy.

[0028]

[0029] In the formula, f tot,b represents the daily operating cost of the integrated energy system (IES) in the grid-connected operation mode; C Elec,int represents the electricity transaction cost; represents the transaction cost of hydrogen energy; Indicates time-of-use electricity price; It represents the power exchanged between IES and the public grid via the tie line at time t. When IES purchases electricity from the public grid, When IES sells electricity to the utility grid, Represents the trading price of hydrogen energy.

[0030] In the grid-connected operation mode, in addition to meeting the constraints of the off-grid operation mode, additional power energy balance constraints and power constraints of the interconnection line between the public grid and the IES must also be met.

[0031] The collaborative optimization scheduling model of the electric-heat-hydrogen integrated energy system established in this paper belongs to a mixed integer nonlinear model, and its standard solution form is as follows:

[0032]

[0033] In the formula, f(x,y) is the optimization objective function; x is the output variable of the energy supply device, energy conversion device and energy storage device, and x max and x min are the upper and lower limits of the equipment output respectively; y is the optimization variable of the equipment start and stop state; g i (x, y) are equality constraints, including power and thermal balance constraints of the integrated energy system; h j (x, y) are inequality constraints, including energy conversion equipment operation constraints, energy storage equipment operation constraints, and renewable energy power generation output constraints. v and w are the total number of equality constraints and inequality constraints, respectively, and i and j are used to indicate specific equality constraints and inequality constraints.

[0034] In order to solve the above problems, the collaborative optimization scheduling model of the electric-heat-hydrogen integrated energy system is first converted into a mixed integer linear model through the piecewise linearization method. Then, the collaborative optimization scheduling model of the integrated energy system is established based on the MATLAB / Simulink platform and solved. The specific linearization process is described as follows.

[0035] According to the design of CHP cost function in the previous article, remove the constant term c in the quadratic function CHP , the CHP cost function can be represented by a quadratic function curve. Divide it into N segments for linear approximation, and the linearized function expression of the CHP cost function is as follows:

[0036]

[0037] In the linearized function expression of the CHP cost function, is the slope of the nth segment CHP cost function curve, is the energy of CHP corresponding to the time t of the nth segment CHP cost function, is the startup and shutdown status of CHP at time t, Indicates that CHP is started. Indicates that the CHP is shut down.

[0038] The specific processing method for linearizing the minimum time constraints for startup and shutdown mentioned above is as follows.

[0039] Linearization of the minimum time constraint for startup

[0040]

[0041] Linearization of the Minimum Stopping Time Constraint

[0042]

[0043] In the formula, and They represent the initial startup time and initial shutdown time of device k respectively; i represents the duration of the device being started or shut down before time 0; T k and T k ′ are the startup time and shutdown time required for device k, respectively. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 Logical framework of coordinated optimization scheduling strategy for electricity-heat-hydrogen integrated energy system

[0045] Figure 2 Structure and energy flow of electricity-heat-hydrogen integrated energy system

[0046] Figure 3 Composition of water electrolysis hydrogen production WEHP system

[0047] Figure 4 Block diagram of proportional control of HFC electrical and thermal energy output

[0048] Figure 5Heat recovery system structure of the electric-heat-hydrogen integrated energy system

[0049] Figure 6 The overall structure of the electric-heat-hydrogen integrated energy system under differentiated operation modes DETAILED DESCRIPTION

[0050] The specific implementation of the present application is further described in detail below in conjunction with the drawings and examples.

[0051] The structure of IES is as follows Figure 2 As shown. Figure 2 It can be seen that IES mainly includes: energy supply links, such as renewable energy generation (RE) and public power grid (UG); energy conversion links, such as combined heat and power (CHP) units, electric boilers (EB), hydrogen fuel cells (HFC) and water electrolysis hydrogen production (WEHP); energy storage links, such as hydrogen storage devices (HSD). The invention first established the WEHP analysis model in the electric-heat-hydrogen integrated energy system, the combined power generation characteristics of HFC, the analysis model of the hydrogen storage device and the thermal system, such as Figure 1 The specific contents are as follows.

[0052] Step 1: Mathematical model of the electricity-heat-hydrogen integrated energy system

[0053] The present invention takes the electric-heat-hydrogen integrated energy system (IES) model as the application object and performs collaborative optimization scheduling under differentiated operation modes. Figure 2 As shown. The complementary coordination mechanism of electric, thermal and hydrogen energy is as follows: In the off-grid operation mode, hydrogen is produced by the abandoned electricity of photovoltaic (PV) and wind power generation (WT) to achieve electric-hydrogen coupling. During peak load, hydrogen is supplied to hydrogen fuel cells (HFC) for combined heat and power, realizing the coupling of electric heat and hydrogen energy. In the grid-connected operation mode, hydrogen is produced by the abandoned electricity of photovoltaic and wind power generation, and hydrogen is produced during low load periods to achieve electric-hydrogen coupling. During peak load periods, part of the hydrogen energy is sold to hydrogen refueling stations, and the remaining hydrogen energy is supplied to hydrogen fuel cells for "combined heat and power", realizing the coupling of electric heat and hydrogen energy. Therefore, the electric, thermal and hydrogen energy coupling model consists of a WEHP model and an HFC model.

[0054] The structure of IES is as follows Figure 2 As shown in the figure, it mainly includes the following parts: energy supply link (such as renewable energy generation (RE) and public power grid (UG)), energy conversion link (such as combined heat and power unit (CHP), electric boiler (EB), hydrogen fuel cell (HFC) and WEHP) and energy storage link (such as hydrogen storage device HSD). This section mainly establishes the analysis models of WEHP model, "combined heat and power" HFC characteristic model, hydrogen storage device model and thermal system model in the integrated power-heat-hydrogen energy system. The specific contents are described as follows.

[0055] Step 1.1: Unified mathematical model of water electrolysis hydrogen production WEHP module, such as Figure 3 As shown;

[0056] The present invention utilizes the energy originally wasted by “abandoning wind and solar power” to electrolyze water to produce hydrogen. Combined with fuel cell power generation technology, it can improve the utilization capacity of renewable energy and assist IES in achieving peak load regulation. At present, mainstream WEHP technologies mainly include alkaline electrolyzers (AECs), proton exchange membrane electrolyzers (PEMECs) and solid oxide electrolyzers (SOECs). The present invention innovatively establishes a unified operation model of WEHP modules applicable to these three electrolysis technologies, thereby improving the scope of application of the collaborative optimization scheduling strategy in engineering practice and enhancing the application value of the method.

[0057] The unified operation model of WEHP modules is suitable for studying WEHP modules with different technical routes and different equipment types in power system operation. The model framework mainly includes start and stop models, hydrogen production models and energy consumption models. In the present invention, M represents the electrolysis technology adopted by the module, M∈{A,P,S}, where A represents AEC, P represents PEMEC, and S represents SOEC; k is the WEHP module number.

[0058] Step 1.1.1: Start and stop model of WEHP module

[0059] 0-1 variables and Indicator variables representing the start and stop states, the start action, and the stop action, respectively. and The value is 1 only in the first period when the module starts or stops. The shutdown process of WEHP is very rapid, and hydrogen production stops as soon as the DC power supply is cut off. The startup delay of AEC and PEMEC is small, while SOEC cannot produce hydrogen before the stack is heated to a certain temperature, and its heating process cannot be ignored. Therefore, using α M represents the start-up delay, i.e. SOEC is only α after the start-up action M The mathematical model of the start-stop characteristics of the WEHP module considering the start delay is shown in the following formula:

[0060]

[0061] In the formula, t represents time, t≤T, T is the scheduling period, and its value is 24. The initial state of is determined by the working state of the previous cycle in a day, as shown in the following formula:

[0062]

[0063] Taking into account the impact of start-stop operation on the service life of the WEHP module, the upper limit of the number of starts and stops of the WEHP module per day is expressed by the following formula:

[0064]

[0065] Where Y M,max and Z M,max They respectively indicate the daily startup and shutdown limits for module M.

[0066] Step 1.1.2: Hydrogen production model of WEHP

[0067] When the WEHP module is running, its hydrogen production model and operating current With working power The relationship between them is shown in the formula.

[0068]

[0069] In the formula, is the hydrogen production rate of WEHP, U HHV =1.48V. is the efficiency of the WEHP module. γ is the conversion factor of the hydrogen production unit from mol / s to kg / h, which is 7.2. F is the Faraday constant, which is 96485 C / mol.

[0070] Step 1.1.3: Three working states and power consumption model of WEHP module

[0071] The power consumption model of the WEHP module mainly describes its operating range and ramp rate constraints. Considering the three operating states of WEHP, the operating power of the WEHP module The unified expression of is as follows:

[0072]

[0073] In the formula, P M,min and P M,max Respectively represent the minimum and maximum working power of module M when it is powered on. M ,boot It represents the power consumed by the WEHP module when it is started, and during this period, the WEHP does not produce hydrogen. In addition, due to the changes in temperature and material inertia, the WEHP module needs to meet the ramp rate constraints during operation, as shown below:

[0074]

[0075] In the formula, ΔP M,max Indicates the maximum rate of change of operating power of module M when it is powered on.

[0076] Step 1.2: Build HFC model

[0077] When there is a shortage of electricity supply in IES, HFC can generate electricity using hydrogen and oxygen through electrochemical reactions under the action of catalysts. Waste heat recovery technology can use the heat released by chemical reactions to improve energy utilization efficiency. The electrical energy output and thermal energy output of HFC affect each other. Studying its operating mechanism is very important to meet load requirements and improve the energy efficiency of HFC. Therefore, this section establishes a combined heat and power model of HFC, considering influencing factors such as hydrogen supply rate and reactor temperature.

[0078] In order to make HFC output the required power, the invention considers N HFC The output voltage of the hydrogen fuel cell cluster is Output Current and output power As shown below:

[0079]

[0080] In the formula, F. and They represent the output voltage, Faraday constant, hydrogen production rate and hydrogen molar mass of a single battery, respectively. The molar mass is 2.02×10 3 kg / mol.

[0081] The operation of HFC generates not only electricity but also more heat. As shown below

[0082]

[0083] In the formula Represents the Nernst voltage of HFC. The power and heat output of HFC are mainly related to the hydrogen supply rate and polarization voltage loss. These three overvoltage losses are mainly related to the operating temperature of HFC. Therefore, the ratio of power and heat output can be determined by controlling the hydrogen supply rate and the operating temperature of HFC. In order to make HFC operate within the normal temperature range of 60℃ to 80℃, it needs to be cooled with circulating water through the cooling channels in the bipolar plates. The faster the circulating water flow rate, the more heat energy is taken away. Therefore, the operating temperature of HFC is determined by the circulating water flow rate. and thermal power output The heat output of HFC is divided into the useful heat carried away by the circulating water and the useless heat power discharged into the air In summary, the proportional control block diagram of HFC power and heat output is as follows: Figure 4shown.

[0084] Step 1.3: Build a hydrogen storage device HSD model

[0085] Unlike traditional electrochemical energy storage, hydrogen can be compressed and stored in standard hydrogen tanks, which makes it relatively independent of energy conversion equipment such as electrolyzers and fuel cells, and can be transported to hydrogen refueling stations by truck. Therefore, the relationship between the remaining capacity of the hydrogen storage device (HSD), the hydrogen production rate of WEHP and the hydrogen consumption rate of HFC, the constraint of hydrogen storage capacity, and the constraint that the total hydrogen storage capacity remains unchanged at the beginning and end of the dispatch period are shown in the following equation.

[0086]

[0087] In the formula, and They represent the remaining capacity of the hydrogen storage device at time t and t+1 respectively. Indicates the maximum capacity of the hydrogen storage device. and Respectively represent the remaining capacity of the hydrogen storage device at the beginning and end of the scheduling period.

[0088] At the same time, a hydrogen storage device transportation cost model for coordinated optimization scheduling of the electric-heat-hydrogen integrated energy system was established, which is shown below. The total transportation cost of the hydrogen storage device can be calculated by the total amount of hydrogen energy that needs to be transported at the end of the scheduling period.

[0089]

[0090] Considering the transportation time of the hydrogen storage device, a time period needs to be reserved before the end of the scheduling period to constrain the capacity of the hydrogen storage device and ensure the implementation of the scheduling plan. The transportation time constraint of the hydrogen storage device is shown in the following formula.

[0091]

[0092] is the total transportation cost to the hydrogen refueling station during the dispatch period; is the cost coefficient of hydrogen energy transportation; T is the scheduling period; T tran is the maximum transport time.

[0093] Step 1.4: Build a thermal system model

[0094] Step 1.4.1: Establish a thermal balance model for the thermal energy system

[0095] The electric-heat-hydrogen integrated energy system uses HFC, CHP and EB as heat sources and heat exchangers as media to achieve heat energy transmission through the pipeline network. The above three together constitute a heat energy circulation system, such as Figure 5 The present invention does not consider the heat loss in the pipeline, and its thermal hydraulic model is shown as follows, including the heat load equation and the thermal power conservation equation:

[0096]

[0097] (∑m out )T out =∑(m in T in )

[0098] In the formula, C p 、m q , T s ,T0,m out , T out 、m in and T in They respectively represent the heat load, specific heat capacity of water, water flow rate flowing into the load, water supply temperature, return water temperature, water flow rate flowing out of the pipe, water temperature flowing out of the pipe, water flow rate flowing into the pipe and water temperature flowing into the pipe.

[0099] Step 1.4.2: Establish a thermal balance model for the thermal energy system

[0100] In the electric-heat-hydrogen integrated energy system model, thermoelectric coupling equipment includes HFC, CHP and EB, all of which are controllable devices. Among them, HFC and CHP generate electricity and heat at the same time, and the three together enhance the flexibility of heat and electricity conversion in IES. HFC determines the ratio of electric energy to heat energy output by controlling the hydrogen supply rate and operating temperature. CHP uses a constant heat-to-electricity ratio for energy supply, and its electric power and heat power output are shown in the following formula:

[0101]

[0102] In the formula, and are the thermal power output and electrical power output of CHP respectively. CHP It is the ratio of CHP thermal power output to natural gas consumption, and in the present invention, it is taken as 1.2. is the natural gas consumption of CHP at time t. ξ CHP is the thermoelectric ratio of CHP, which is taken as 1.5 in the present invention.

[0103] EB can convert electrical energy into thermal energy with a conversion efficiency higher than 90%. EB is installed in IES to meet the heating load demand, which can reduce the consumption of natural gas. The thermal power output of the electric boiler at time t As shown in the following formula:

[0104]

[0105] Where η EB is the thermal energy conversion efficiency of EB, which is taken as 0.9 in the present invention. is the electrical energy consumption of EB at time t.

[0106] At present, the short-term forecasting methods for renewable energy generation include time series forecasting methods, neural network methods and support vector machine (SVM) methods. Support vector machines are based on statistical learning theory and the principle of structural risk minimization. They have good scalability and high accuracy, and can achieve good results even when there is less training set data. Therefore, this paper establishes a support vector machine model based on historical data for short-term forecasting of renewable energy generation. The expression of historical data is shown in the following formula:

[0107]

[0108] Where P RE is the historical data vector of renewable energy generation, RE∈{PV,WT}. T is the scheduling period, and T=24 is taken in the invention. is the renewable energy power generation output of the i-th sampling point, i = 0, 1, ..., K, K is the total number of sampling points. Renewable energy generation is greatly affected by weather changes and has strong uncertainty. Although the support vector machine model has strong learning ability, it cannot express the uncertainty of the prediction results, so errors are inevitable in short-term predictions.

[0109] The idealized wind turbine power model can be expressed as a piecewise function. When the wind speed is less than the rated wind speed, the system adopts maximum power tracking control to maximize the utilization efficiency of wind energy. When the wind speed is greater than the rated wind speed, the constant power operation mode is usually adopted. In the transition zone close to the rated wind speed, the control strategy will switch smoothly. Therefore, the output power model of the wind turbine is as follows:

[0110]

[0111] In the formula, is the wind speed at time t, v in and v out They are the start-up wind speed and the stop wind speed respectively. and are the upper and lower limits of the wind speed transition zone. m and n are the number of segments. and are the polynomial fitting parameters and refer to the test data provided by the equipment manufacturer.

[0112] The output power model of photovoltaic (PV) is expressed by the following formula:

[0113]

[0114] In the formula, It is the maximum output power of photovoltaic under standard test environment. It is the light intensity under standard test environment. is the actual light intensity. T is the coefficient of power versus temperature. T τ is the reference temperature. is the temperature of the photovoltaic cell. is the ambient temperature.

[0115] As can be seen from the above, wind speed and light intensity are the main factors causing uncertainty in renewable energy generation. and light intensity Make forecasts and then revise the forecast values ​​of renewable energy generation.

[0116] Assume that the forecast error of renewable energy generation is ΔP RE , according to the central limit theorem, the normal distribution function can be used to represent the prediction error. If ΔP RE The expected value of μ is RE , the variance is The forecast error of renewable energy generation is ΔP RE Normal distribution If the error is the mean over time, the expected value is 0. The error function f(ΔP RE ) is shown in the following formula:

[0117]

[0118] Energy grid is the trend of future power grid development. Thermal-electric coupled energy suppliers, renewable energy power generators and grid operators cannot just pursue their own economic interests, but should formulate energy grid operation strategies from the perspective of maximizing energy output, utilization efficiency and overall social benefits. The significance of the collaborative optimization scheduling strategy of the electric-thermal-hydrogen integrated energy system studied in this invention is to optimize and control the output of each device, so as to minimize the daily operation cost of the electric-thermal-hydrogen integrated energy system under the premise of ensuring the balance of supply and demand of electricity and thermal energy under differentiated operation modes. The electric-thermal-hydrogen integrated energy system has two operation modes, namely off-grid mode and grid-connected mode. The specific architecture is as follows: Figure 6As shown. In the off-grid operation mode, WEHP and HFC, as controllable devices of the electric-heat-hydrogen integrated energy system, play a role in achieving the "source-load" balance of the system and stabilizing the fluctuation of renewable energy generation. In the grid-connected operation mode, electricity and hydrogen energy participate in market transactions, which can not only improve the energy supply reliability of the electric-heat-hydrogen integrated energy system, but also reduce daily operating costs through energy sales.

[0119] Step 2: Off-grid operation mode

[0120] Step 2.1: Establish the objective function for off-grid operation mode

[0121] In the off-grid operation mode, there is no power exchange between IES and the grid, and the supply and demand balance of electricity and thermal energy is maintained by optimizing the output of each device in IES. The objective function to minimize the daily operating cost of IES is as follows:

[0122] minf tot,l =C RE +C cur +C WEHP +C HSD +C HFC +C EB +C gas

[0123]

[0124] In the above formula, in the formula, f tot,l is the daily operating cost of IES in off-grid operation mode. T is the dispatch period. C RE is the electricity generation cost of photovoltaic and wind power. cur It is the penalty cost of “abandoning wind and solar power”. WEHP is the operating cost of WEHP. HSD is the hydrogen storage cost. C HFC , C EB and C CHP are the daily operating cost coefficients of HFC, EB and CHP respectively. PV and λ WT They are the daily operating cost coefficients of photovoltaic and wind power generation, with values ​​of 0.0235 and 0.0196 respectively. and are the output powers of photovoltaic and wind power generation at time t respectively. and are the fixed costs of photovoltaic and wind power generation respectively. and It is the penalty cost coefficient for “abandoning wind and solar power”. and is the power reduction of wind power and photovoltaic power generation at time t. N WEHP is the total number of WEHP modules. is the cost coefficient of the Mth module. is the fixed daily operating cost of the Mth module. HSD is the hydrogen storage cost coefficient. is the fixed maintenance cost of HSD. HFC is the daily operating cost coefficient of HFC. is the output power of the hydrogen fuel cell at time t. η HFC is the operating efficiency of the hydrogen fuel cell. is the fixed maintenance cost of the hydrogen fuel cell. EB It is the daily operating cost coefficient of EB. is the fixed maintenance cost of the electric boiler. gas is the price of natural gas. CHP , b CHP and c CHP is the fuel cost factor for CHP. is the fixed maintenance cost of the combined heat and power plant.

[0125] Step 2.2: According to the actual situation of the off-grid operation mode of the electric-heat-hydrogen integrated energy system, design constraints to ensure the stability and economy of the system.

[0126] Step 2.2.1: Establish power energy balance constraints

[0127]

[0128] In the power energy balance constraint, Indicates the electrical load condition at time t.

[0129] Step 2.2.2: Establish thermal energy balance constraints

[0130]

[0131] In the thermal energy balance constraint, Indicates the thermal energy load at time t.

[0132] Step 2.2.3: Establish output power constraints for controllable devices

[0133]

[0134] In the output power constraints of controllable devices, and are the upper and lower limits of the output power of the controllable device k respectively.

[0135] Step 2.2.4: Establish power change speed constraints for controllable devices

[0136]

[0137] In the power change speed constraint of the controllable device, and are the limits of the power increase rate and decrease rate of the controllable device k respectively.

[0138] Step 2.2.5: Establish minimum time constraints for startup and shutdown of controllable equipment

[0139]

[0140] The minimum time constraints for starting and stopping controllable equipment: and are the minimum continuous shutdown and startup times of controllable device k, respectively. and are the time that the equipment is started and stopped continuously before time t.

[0141] Step 2.2.6: Establish output constraints for PV and WT

[0142]

[0143] In the output constraints of PV and WT, and are the maximum output powers of PV and WT respectively.

[0144] Step 3: Grid-connected operation mode

[0145] Step 3.1: Establish the objective function in grid-connected operation mode

[0146] In the grid-connected operation mode, the integrated energy system (IES) participates in market transactions based on the time-of-use electricity price and hydrogen energy trading price, and its objective function is shown in the following formula. The objective function based on the off-grid operation mode adds additional transaction costs for electricity and hydrogen energy.

[0147]

[0148] In the formula, f tot,b represents the daily operating cost of the integrated energy system (IES) in the grid-connected operation mode; C Elec,int represents the electricity transaction cost; represents the transaction cost of hydrogen energy; Indicates time-of-use electricity price; It represents the power exchanged between IES and the public grid via the tie line at time t. When IES purchases electricity from the public grid, When IES sells electricity to the utility grid, Represents the trading price of hydrogen energy.

[0149] Step 3.2: In the grid-connected operation mode, in addition to meeting the constraints of the off-grid operation mode, additional power energy balance constraints and the power constraints of the tie line between the public grid and the IES must also be met.

[0150] Step 3.2.1: Establish power energy balance constraints

[0151]

[0152] Compared with the off-grid operation mode, the power energy balance constraint in the grid-connected operation mode takes into account the power exchanged between the IES and the public grid via the tie line at time t.

[0153] Step 3.2.2: Establish the power constraint of the tie line between the public grid and IES

[0154]

[0155] In the power constraint of the tie line between the public grid and IES, and They are the lower and upper limits of the tie line power respectively.

[0156] Step 4: Execute the model solving algorithm

[0157] The collaborative optimization scheduling model of the electric-heat-hydrogen integrated energy system established in this paper belongs to a mixed integer nonlinear model, and its standard solution form is as follows:

[0158]

[0159] In the formula, f(x,y) is the optimization objective function; x is the output variable of the energy supply device, energy conversion device and energy storage device, and x max and x min are the upper and lower limits of the equipment output respectively; y is the optimization variable of the equipment start and stop state; g i (x, y) are equality constraints, including power and thermal balance constraints of the integrated energy system; h j (x, y) are inequality constraints, including energy conversion equipment operation constraints, energy storage equipment operation constraints, and renewable energy power generation output constraints. v and w are the total number of equality constraints and inequality constraints, respectively, and i and j are used to indicate specific equality constraints and inequality constraints.

[0160] In order to solve the above problems, the collaborative optimization scheduling model of the electric-heat-hydrogen integrated energy system is first converted into a mixed integer linear model through the piecewise linearization method. Then, the collaborative optimization scheduling model of the integrated energy system is established based on the MATLAB / Simulink platform and solved. The specific linearization process is described as follows.

[0161] Step 4.1: Linearization of CHP cost function

[0162] According to the design of CHP cost function in the previous article, remove the constant term c in the quadratic function CHP , the CHP cost function can be represented by a quadratic function curve. Divide it into N segments for linear approximation, and the linearized function expression of the CHP cost function is as follows:

[0163]

[0164] In the linearized function expression of the CHP cost function, is the slope of the nth segment CHP cost function curve, is the energy of CHP corresponding to the time t of the nth segment CHP cost function, is the startup and shutdown status of CHP at time t, Indicates that CHP is started. Indicates that the CHP is shut down.

[0165] Step 4.2: Minimum time constraints for startup and shutdown

[0166] The specific processing method for linearizing the minimum time constraints for startup and shutdown mentioned above is as follows.

[0167] Step 4.2.1: Linearization of the minimum time constraint for startup

[0168]

[0169] Step 4.2.2: Linearization of the minimum time constraint for shutdown

[0170]

[0171]

[0172] In the formula, and They represent the initial startup time and initial shutdown time of device k respectively; i represents the duration of the device being started or shut down before time 0; T k and T k ′ are the startup time and shutdown time required for device k, respectively.

[0173] The actual model considered in this invention adopts a coupled system of a six-node power grid, a six-node heating network and a three-node natural gas pipeline network. Since the load in the considered area is relatively stable, the uncertainty of electricity, heat and hydrogen loads is not considered in this model. The simulation step size in this invention is set to 1 hour and the scheduling cycle is 24 hours. With the lowest daily operating cost of the integrated energy system (IES) as the goal, a collaborative optimization scheduling strategy for each device in the IES is formulated under a differentiated operating mode. Considering the maturity of the three WEHP technologies, the unified module power is 100kW. N WEHP The number of modules is 3, one for each module.

[0174] Simulation results:

[0175] This example verifies the effectiveness of the proposed scheduling strategy by simulating the coordinated optimization scheduling strategy of the electric-heat-hydrogen integrated energy system under differentiated operation modes. As flexible and controllable equipment for energy balance between supply and demand in off-grid operation mode, WEHP and HFC can eliminate the power abandonment of photovoltaic and wind power, play the role of peak shaving and valley filling, and stabilize the output fluctuation of renewable energy. In the off-grid operation mode, the hydrogen stored in the IES is consumed only by HFC. In the grid-connected operation mode, more revenue can be obtained by selling hydrogen to hydrogen refueling stations compared with HFC consumption. The detailed thermal-electric coupling result analysis of the scheduling scheme is shown below.

[0176] In the off-grid operation mode, electricity and hydrogen are not involved in market transactions, and CHP, EB, and HFC must meet output power constraints and ramp rate constraints. Therefore, the simulation results of the case are the optimal solutions under the given cost coefficients and constraints. The results show that photovoltaic (PV) is not available and wind turbines (WT) cannot meet the power load demand during the period from 1:00 to 6:00 in the morning and from 9:00 to midnight. Due to the high cost of natural gas, CHP stops operating. At this time, IES uses EB and HFC to achieve a balance between supply and demand of electricity and heat, which greatly reduces the consumption of natural gas by IES during the dispatch period. Since the cost of natural gas consumption accounts for a large proportion of the daily operating cost of IES, considering the "co-generation" characteristics of HFC has a significant effect on reducing the daily operating cost of IES. During the period from 10:00 to 14:00, the PV output power is large, and the power load demand is mainly met by PV, WT, and CHP. At this time, HFC is mainly used for heating, and the thermal power output of EB is significantly reduced. During the period from 17:00 to 20:00, the demand for electricity and heating loads increases, while the PV output power gradually decreases to 0. At this time, IES mainly relies on WT, CHP and HFC to achieve a balance between supply and demand of electricity and heat.

[0177] The operating costs of WEHP, hydrogen storage costs, and HFC operating costs make the power output ratio of WEHP and HFC in IES relatively small, but their total amount cannot be ignored. As flexible and controllable equipment for balancing energy supply and demand, WEHP and HFC can eliminate the power abandonment of photovoltaic and wind power, play the role of peak shaving and valley filling, and stabilize the output fluctuation of renewable energy.

[0178] The daily operating costs of each device in IES are shown in Table 1. System simulation shows that the daily operating cost of IES in off-grid operation mode is 2158.386. Among them, the amount of power abandoned by PV and WT is 0, so the penalty cost of "abandoning wind and solar power" is 0. Compared with the economic losses caused by the abandonment of PV and WT, IES is more inclined to use excess electricity to produce hydrogen through WEHP to reduce energy waste. In the off-grid operation mode, WEHP and HFC realize the time transfer of energy. In addition, due to the high cost of natural gas fuel, the daily operating cost of CHP accounts for the highest proportion of the daily operating cost of IES.

[0179] Table 1. Operating costs of IES equipment in off-grid operation mode

[0180] Daily operating costs PV WT WEHP HFC result 65.051 102.44 338.87 160.957 Daily operating costs HSD CHP EB The cost of penalties for curtailing wind and solar power result 617.73 743.302 130.035 0

[0181] In the grid-connected operation mode, electric energy and hydrogen energy can participate in market transactions, thereby increasing the energy sources and transmission channels of IES. Under the guidance of electricity prices and hydrogen trading prices, the output of each device is optimized, with the goal of minimizing the daily operating cost of IES. System simulation results show that since the fuel cost of CHP is much higher than the electricity purchase cost, the output power of CHP in the grid-connected operation mode is lower than that in the off-grid operation mode. After the thermal power output of CHP is reduced, the heating load demand of IES is mainly met by EB, which has advantages in low daily operating costs. In the grid-connected operation mode, due to the reliable support of the power grid, the role of WEHP and HFC as flexible resources is significantly weakened, and the thermal power output of HFC also shows a downward trend at this time. Considering that the two periods from 6h to 12h and from 22h to 24h are low electricity price periods, most of the line power at this time is positive, that is, IES mainly purchases electricity from the power grid. In other periods, the line power is mostly negative, that is, IES sells electricity to the power grid to reduce daily operating costs. It can be seen that the changes in line power are generally consistent with the changes in electricity prices.

[0182] In off-grid operation mode, the hydrogen stored in IES is only consumed by HFC. In grid-connected operation mode, more income can be obtained by selling hydrogen to hydrogen stations than directly supplying HFC. The daily operating costs of each device in IES in grid-connected operation mode are shown in Table 2.

[0183] As can be seen from Table 2, the daily operating cost of IES in the grid-connected operation mode is 1833.489. Compared with the off-grid operation mode, the daily operating cost of IES is reduced by 15.05%. On the one hand, the fuel cost of CHP is reduced, and on the other hand, IES obtains considerable income through the sale of hydrogen, thereby reducing the daily operating cost. Compared with the fuel price, the cost of purchasing electricity is relatively low, so the daily operating cost of EB in the grid-connected operation mode is higher than that in the off-grid operation mode.

[0184] Table 2. Operating costs of IES equipment in grid-connected operation mode

[0185]

[0186]

Claims

1. A collaborative optimization scheduling strategy for an electric-heat-hydrogen integrated energy system under a differentiated operation mode, characterized in that: Establish a mathematical model of an electric-heat-hydrogen integrated energy system, including: Energy supply link (such as renewable energy generation (RE) and public power grid (UG)), energy conversion link (such as combined heat and power unit (CHP), electric boiler (EB), hydrogen fuel cell (HFC) and WEHP) and energy storage link (such as hydrogen storage device HSD); This section mainly establishes the analysis model of WEHP model, "combined heat and power" HFC characteristic model, hydrogen storage device model and thermal system model in the integrated power-heat-hydrogen energy system, and the specific contents are as follows; A unified operation model of WEHP modules applicable to the three electrolysis technologies, a hydrogen production model of WEHP, and three working states and power consumption models of WEHP modules were established; To establish the HFC model, in order to make the HFC output the required power, the invention considers N HFC The hydrogen fuel cells are connected in series; the operation process of HFC generates more heat energy while generating electricity; the transportation cost model of hydrogen storage device for coordinated optimization scheduling of electric-heat-hydrogen integrated energy system is established as shown below, the total transportation cost of hydrogen storage device can be calculated by the total amount of hydrogen energy that needs to be transported at the end of the scheduling period; considering the transportation time of hydrogen storage device, a time period needs to be reserved before the end of the scheduling period to constrain the capacity of hydrogen storage device and ensure the implementation of scheduling plan; Establish a thermal energy system model; first establish a thermal balance model of the thermal energy system. The electric-heat-hydrogen integrated energy system uses HFC, CHP and EB as heat sources and heat exchangers as media to achieve thermal energy transmission through the pipeline network; the above three together constitute a thermal energy circulation system; then establish a thermal balance model of the thermal energy system. In the electric-heat-hydrogen integrated energy system model, the thermoelectric coupling equipment includes HFC, CHP and EB, all of which are controllable devices; among them, HFC and CHP generate electricity and heat at the same time, and the three together enhance the flexibility of heat and electricity conversion in IES; HFC determines the ratio of electricity and heat output by controlling the hydrogen supply rate and operating temperature; CHP uses a constant heat-to-electricity ratio for energy supply; EB can convert electricity into heat, and its conversion efficiency is higher than 90%; EB is installed in IES to meet the heating load demand, which can reduce the consumption of natural gas; Based on historical data, a support vector machine model is established for short-term forecasting of renewable energy generation. Then, an idealized wind turbine power model is established and expressed as a piecewise function. At the same time, a photovoltaic (PV) output power model is established. Since wind speed and light intensity are the main factors causing uncertainty in renewable energy generation, predictions are made in combination with the predicted sampling points of renewable energy generation, and then the predicted values ​​of renewable energy generation are corrected. The electric-heat-hydrogen integrated energy system has two operating modes, namely off-grid mode and grid-connected mode; in the off-grid operating mode, WEHP and HFC, as controllable equipment of the electric-heat-hydrogen integrated energy system, play a role in achieving the "source-load" balance of the system and stabilizing the fluctuations in renewable energy power generation; in the grid-connected operating mode, electricity and hydrogen energy participate in market transactions, which can not only improve the energy supply reliability of the electric-heat-hydrogen integrated energy system, but also reduce daily operating costs through energy sales.

2. According to the collaborative optimization scheduling strategy of the electric-heat-hydrogen integrated energy system under the differentiated operation mode of claim 1, the objective function and constraint conditions under the off-grid operation state are established, characterized in that: The off-grid coordinated optimization scheduling strategy designed according to the mathematical model of the electric-heat-hydrogen integrated energy system is calculated as follows: In the off-grid operation mode, there is no power exchange between IES and the grid, and the supply and demand balance of electricity and heat energy is maintained by optimizing the output of each device in IES; the objective function to minimize the daily operation cost of IES is as follows: minf tot,l =C RE +C cur +C WEHP +C HSD +C HFC +C EB +C gas In the above formula, in the formula, f tot,l is the daily operating cost of IES in off-grid operation mode; T is the dispatch period; C RE is the power generation cost of photovoltaic and wind power; C cur is the penalty cost of "abandoning wind and solar power"; C WEHP is the operating cost of WEHP; C HSD is the hydrogen storage cost; C HFC , C EB and C CHP are the daily operating cost coefficients of HFC, EB and CHP respectively; λ PV and λ WT are the daily operating cost coefficients of photovoltaic and wind power generation, with values ​​of 0.0235 and 0.0196 respectively; and are the output power of photovoltaic and wind power generation at time t respectively; and are the fixed costs of photovoltaic and wind power generation, respectively; and is the penalty cost coefficient for "abandoning wind and solar power"; and is the power reduction of wind power and photovoltaic power generation at time t; N WEHP is the total number of WEHP modules; is the cost coefficient of the Mth module; is the fixed daily operating cost of the Mth module; HSD is the hydrogen storage cost coefficient; is the fixed maintenance cost of HSD; HFC is the daily operating cost coefficient of HFC; is the output power of the hydrogen fuel cell at time t; η HFC is the operating efficiency of the hydrogen fuel cell; is the fixed maintenance cost of the hydrogen fuel cell; EB is the daily operating cost coefficient of EB; is the fixed maintenance cost of the electric boiler; gas is the natural gas price; a CHP , b CHP and c CHP is the fuel cost factor of CHP; is the fixed maintenance cost of the combined heat and power; According to the actual situation of the off-grid operation mode of the electric-heat-hydrogen integrated energy system, constraints are designed to ensure the stability and economy of the system.

3. According to the collaborative optimization scheduling strategy of the electric-thermal-hydrogen integrated energy system under the differentiated operation mode of claim 1, the objective function and constraint conditions under the grid-connected operation state are established, characterized in that: The coordinated optimization dispatch strategy designed according to the mathematical model of the electric-heat-hydrogen integrated energy system under the grid-connected state is calculated as follows: In the grid-connected operation mode, the integrated energy system (IES) participates in market transactions based on the time-of-use electricity price and hydrogen energy trading price, and its objective function is shown in the following formula; the objective function based on the off-grid operation mode adds additional transaction costs for electricity and hydrogen energy; In the formula, f tot,b represents the daily operating cost of the integrated energy system (IES) in the grid-connected operation mode; C Elec,int represents the electricity transaction cost; represents the transaction cost of hydrogen energy; Indicates time-of-use electricity price; represents the power exchanged between IES and the public grid via the tie line at time t; when IES purchases electricity from the public grid, When IES sells electricity to the utility grid, represents the hydrogen energy transaction price; In the grid-connected operation mode, in addition to meeting the constraints of the off-grid operation mode, additional power energy balance constraints and power constraints of the interconnection line between the public grid and the IES must also be met.

4. According to the collaborative optimization scheduling strategy of the electric-thermal-hydrogen integrated energy system under the differentiated operation mode of claim 2 or claim 3, a collaborative optimization scheduling model of the electric-thermal-hydrogen integrated energy system is established, characterized in that: The collaborative optimization scheduling model is a mixed integer nonlinear model. The collaborative optimization scheduling model of the electric-thermal-hydrogen integrated energy system is transformed into a mixed integer linear model through the piecewise linearization method. Then, the collaborative optimization scheduling model of the integrated energy system is established and solved based on the MATLAB / Simulink platform. In order to solve the above problems, the collaborative optimization scheduling model of the electric-heat-hydrogen integrated energy system is first converted into a mixed integer linear model through the piecewise linearization method. Then, the collaborative optimization scheduling model of the integrated energy system is established based on the MATLAB / Simulink platform and solved.

5. The coordinated optimization scheduling strategy of the electric-heat-hydrogen integrated energy system under the differentiated operation mode according to claim 4 is characterized in that: The collaborative optimization scheduling model of the electricity-heat-hydrogen integrated energy system belongs to a mixed integer nonlinear model, and its standard solution form is as follows: In the formula, f(x,y) is the optimization objective function; x is the output variable of the energy supply device, energy conversion device and energy storage device, and x max and x min are the upper and lower limits of the device output respectively; y is the optimization variable of the equipment start and stop state; g i (x, y) are equality constraints, including power and thermal balance constraints of the integrated energy system; h j (x, y) are inequality constraints, including energy conversion equipment operation constraints, energy storage equipment operation constraints, and renewable energy power generation output constraints; v and w are the total number of equality constraints and inequality constraints, respectively, and i and j are used to indicate specific equality constraints and inequality constraints.

6. The coordinated optimization scheduling strategy of the electric-heat-hydrogen integrated energy system under the differentiated operation mode according to claim 4 is characterized in that: The linearization process is as follows: Step 4.1: Linearization of CHP cost function According to the design of CHP cost function in the previous article, remove the constant term c in the quadratic function CHP , the CHP cost function can be represented by a quadratic function curve; it is divided into N segments for linear approximation, and the linearized function expression of the CHP cost function is as follows: In the linearized function expression of the CHP cost function, is the slope of the nth segment CHP cost function curve, is the energy of CHP corresponding to the time t of the nth segment CHP cost function, is the startup and shutdown status of CHP at time t, Indicates that CHP is started. Indicates that the CHP is shut down; Step 4.2: Minimum time constraints for startup and shutdown.

7. The coordinated optimization scheduling strategy of the electric-heat-hydrogen integrated energy system under the differentiated operation mode according to claim 6 is characterized in that: The specific processing method for linearizing the minimum time constraints for startup and shutdown is as follows; Step 4.2.1: Linearization of the minimum time constraint for startup Step 4.2.2: Linearization of the minimum time constraint for shutdown In the formula, and They represent the initial startup time and initial shutdown time of device k, respectively; i represents the duration of the device being started or shut down before time 0; T k and T k ′ are the startup time and shutdown time required for device k, respectively.

Images