High-proportion renewable energy power system peak regulation economical efficiency optimization method based on hydrogen energy storage

Abstract

The invention relates to a high-proportion renewable energy power system peak regulation economical efficiency optimization method based on hydrogen energy storage, and the method comprises the steps: employing a multi-source combined peak regulation system, and bringing a plurality of power forms into a peak regulation range, such as wind power, photovoltaic, thermal power, hydropower, nuclear power, a hydrogen energy storage system, pumped storage, chemical energy storage, and the like; through a double-layer peak regulation optimization strategy, corresponding upper layer constraint conditions and lower layer constraint conditions are set for an upper layer objective function and a lower layer objective function, so that the fitting degree of a wind-solar comprehensive output curve and a load curve is maximized, and net load fluctuation is reduced; and under the condition of meeting the stable operation constraint of the system, the opportunity and depth of each unit participating in peak regulation are reasonably optimized, the operation strategy of hydrogen energy storage is optimized, and variable cost optimization of system operation is realized.

Description

Technical Field

[0001] The present invention relates to the technical field of optimizing the dispatching of new energy power systems. Specifically, it particularly relates to a method for optimizing the peak shaving economy of a high-proportion renewable energy power system based on hydrogen energy storage. Background Art

[0002] Wind power generation and photovoltaic power generation, as the main forms of renewable energy, have strong volatility and time correlation. Direct grid connection operation poses a huge challenge to the stability of the power grid. Especially the strong time correlation and reverse peak shaving characteristics of photovoltaic power generation lead to serious phenomena of wind and light abandonment when a high proportion of new energy is connected, and both the system economy and flexibility are affected.

[0003] Traditional power grid dispatching strategies mainly rely on load forecasting and flexible thermal power peak shaving. However, with the gradual withdrawal of high-carbon energy from the market and the continuous increase in the penetration rate of new energy, traditional strategies are difficult to adapt to the complex and changeable power grid operation environment. Although the introduction of flexibility resources such as pumped storage power stations and chemical energy storage has enhanced the peak shaving ability, due to problems such as long construction periods, natural condition limitations, short service lives, and high costs, they cannot fully meet the peak shaving requirements.

[0004] In recent years, hydrogen energy storage technology has gradually become an important research direction for peak shaving in new energy power systems due to its characteristics such as large energy density, long storage cycle, and no pollution. Hydrogen energy storage "shaves the peak" through electrolytic water hydrogen production and "fills the valley" through hydrogen gas turbine or fuel cell power generation, showing significant advantages in improving the volatility of new energy and enhancing the consumption capacity. However, the energy conversion efficiency and high operating cost of hydrogen energy storage pose challenges to the economy of the system. Therefore, studying a combined peak shaving optimization method based on hydrogen energy storage is of great significance for improving the overall operating efficiency and stability of the power system. Summary of the Invention

[0005] Aiming at the serious problems of wind and light abandonment, large system peak shaving pressure, high operating cost, and insufficient flexibility of traditional energy storage systems in the current high-proportion renewable energy power system, the present invention proposes a method for optimizing the peak shaving economy of a high-proportion renewable energy power system based on the access of hydrogen energy storage, aiming to enhance the consumption capacity of renewable energy such as wind power and photovoltaic power; suppress the fluctuations of wind and light output and reduce the peak shaving pressure of the system; optimize the operating strategy of hydrogen energy storage and reduce the total operating cost of the system.

[0006] The optimization method specifically includes the following steps:

[0007] Step S1, construct a multi-source combined peak shaving system: The multi-source combined peak shaving system includes renewable energy generating units, thermal power units, nuclear power units, hydrogen energy storage systems, and a dispatching center; the electricity generated by each unit is all connected to the power grid; the hydrogen storage system specifically includes an electrolyzer, a hydrogen gas turbine, a hydrogen fuel cell, and high-pressure gaseous hydrogen storage tanks, which are used to electrolyze water to produce hydrogen and store it for peak shaving under the control of the dispatching center, and generate electricity through a hydrogen gas turbine or a hydrogen fuel cell to fill valleys when the power generation is insufficient.

[0008] Step S2, obtain the variable cost of peak shaving: The dispatching center obtains the peak shaving cost of renewable energy, the peak shaving cost of nuclear power, the variable peak shaving cost of thermal power, and the operating loss costs of chemical energy storage stations and pumped storage power stations.

[0009] Step S21: The renewable energy generating units include wind power generating units, photovoltaic power generating units, and hydropower generating units. While maximizing the peak shaving capacity of hydropower, it is necessary to maximize the consumption of wind power and photovoltaic power. The peak shaving cost of renewable energy is shown in the following formula:

[0010]

[0011] Step S22: The peak shaving cost of nuclear power obtained by the dispatching center is:

[0012]

[0013] Step S23: The variable peak shaving cost of thermal power and gas turbine units obtained by the dispatching center is:

[0014]

[0015] Step S24: The operating loss costs of the chemical energy storage station and the pumped storage power station obtained by the dispatching center are:

[0016]

[0017] Step S3, double-layer peak shaving optimization: Set the upper-layer objective function to optimize the fitting degree between the comprehensive power curve of renewable energy generation and the load curve; set the lower-layer objective function to control the timing and power of each unit participating in peak shaving by the dispatching center under the constraint conditions of stable operation, so as to achieve the optimal variable cost of the peak shaving system operation.

[0018] The step S3 further includes: The upper-layer objective function is used to maximize the fitting degree between the comprehensive power of wind and solar power generation and the load curve, and reduce the load fluctuation; its expression is shown in the following formula:

[0019]

[0020] Step S3 further includes step S31 of constructing upper - layer constraint conditions: set corresponding upper and lower limit values for the electrolyzer power, hydrogen gas turbine power, hydrogen gas turbine power ramp - up power, hydrogen fuel cell power, and hydrogen storage capacity in the upper - layer objective function, and when the hydrogen gas turbine power reaches the upper limit value of the hydrogen gas turbine power or the upper limit value of the hydrogen gas turbine ramp - up power, the hydrogen fuel cell intervenes to supply energy.

[0021] Step S3 further includes: The lower - layer objective function is shown as the following formula:

[0022]

[0023] Step S3 further includes step S32 of constructing lower - layer constraint conditions: set power - balance constraints for the lower - layer objective function, as shown in the following formula:

[0024]

[0025] And set corresponding constraint conditions for the actual power of the wind power generation unit, photovoltaic power generation unit, thermal power generation unit, hydropower unit, hydrogen gas turbine, nuclear power unit, and the capacity of pumped - storage energy and chemical energy storage.

[0026] Step S3 further includes step S33: The dispatching center uses the mixed - integer non - linear programming method to solve the lower - layer objective function, controls the timing and power of each unit participating in peak - shaving, so as to achieve the optimal variable cost of the peak - shaving system operation.

[0027] In summary, the beneficial effects of the present invention are as follows:

[0028] 1. By constructing a multi - source combined peak - shaving system, the present invention incorporates various power sources such as wind power, photovoltaic power, thermal power, hydropower, nuclear power, hydrogen storage, pumped - storage energy, and chemical energy storage into the peak - shaving scope, and realizes the economic operation and stable peak - shaving of the system by optimizing the operation strategies of each unit.

[0029] 2. By setting the penalty cost coefficient, the present invention realizes maximizing the use of the peak - shaving capacity of hydropower while maximizing the accommodation of wind power and photovoltaic power, and avoids power waste caused by water abandonment, wind abandonment, and light abandonment.

[0030] 3. Through the double - layer peak - shaving optimization strategy, by setting corresponding upper - layer constraint conditions and lower - layer constraint conditions for the upper - layer objective function and the lower - layer objective function, the present invention maximizes the fitting degree between the comprehensive output curve of wind and light and the load curve, reduces the net load fluctuation; and under the condition of meeting the system stable operation constraints, reasonably optimizes the timing and depth of each unit participating in peak - shaving, optimizes the operation strategy of hydrogen energy storage, and realizes the optimal variable cost of the system operation. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 The block diagram for the peak shaving optimization participated by the hydrogen energy storage system described in the present invention;

[0032] Figure 2 The peak shaving method of the nuclear power unit described in the present invention;

[0033] Figure 3 The cost model for the thermal power unit participating in peak shaving described in the present invention;

[0034] Figure 4 The simulation example model of the multi-source combined peak shaving system described in the present invention;

[0035] Figure 5 The simulation load prediction diagram of the multi-source combined peak shaving system described in the present invention;

[0036] Figure 6 The block diagram of the proportion of each unit in the multi-source combined peak shaving system described in the present invention;

[0037] Figure 7 The simulation result of the multi-source combined peak shaving system under Configuration 1 described in the present invention;

[0038] Figure 8 The simulation result of the multi-source combined peak shaving system under Configuration 2 described in the present invention;

[0039] Figure 9 The simulation result of the multi-source combined peak shaving system under Configuration 3 described in the present invention. Detailed implementation manners

[0040] In order to enable those skilled in the art to better understand the solution of the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without making creative efforts shall fall within the protection scope of the present application.

[0041] It should be noted that the terms "first", "second", etc. in the description, claims and the above-mentioned drawings of the present application are used to distinguish similar objects, and do not necessarily need to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged under appropriate circumstances, so that the embodiments of the present application described here can be implemented in an order other than those illustrated or described here. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device that includes a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or are inherent to these processes, methods, products or devices.

[0042] Embodiment 1

[0043] In view of the problems existing in the prior art, this embodiment provides an optimization method for the peak shaving economy of a high-proportion renewable energy power system based on hydrogen energy storage access. The method specifically includes the following steps:

[0044] Step S1, construct a multi-source combined peak shaving system: The multi-source combined peak shaving system includes renewable energy generating units, thermal power generating units, nuclear power generating units, hydrogen energy storage systems and a dispatching center; the power generated by each unit is all connected to the power grid; the hydrogen storage system specifically includes an electrolyzer, a hydrogen gas turbine, a hydrogen fuel cell, and a high-pressure gaseous hydrogen storage tank, which are used to electrolyze water to produce hydrogen for storage to eliminate peaks under the control of the dispatching center when there is excess power in the power grid, and generate power through the hydrogen gas turbine or hydrogen fuel cell to fill valleys when the power generation is insufficient.

[0045] The renewable energy generating units include wind power generating units, photovoltaic power generating units, and hydropower generating units. As Figure 1 shown, the power generated by the wind power generating units and photovoltaic power generating units is transmitted to the grid side. When there is surplus power generation, the excess power in the power grid is used to electrolyze water to produce hydrogen in the electrolyzer and store it in the high-pressure gaseous hydrogen storage tank; when the power generation is insufficient, power is generated through the hydrogen gas turbine or hydrogen fuel cell to fill valleys; the thermal power generating units, nuclear power generating units, chemical energy storage stations, pumped storage power stations and the dispatching center are not shown in the figure.

[0046] Step S2, obtain the variable cost of peak shaving: The dispatching center obtains the peak shaving cost of renewable energy, the peak shaving cost of nuclear power, the variable peak shaving cost of thermal power, and the operating loss costs of chemical energy storage stations and pumped storage power stations.

[0047] When a hydropower unit participates in the peak shaving of the power system, it is similar to a pumped-storage power station. Although it does not have a load characteristic, it can change the reservoir capacity by adjusting the motor power and the drainage volume. By predicting the water flow through the station and reasonably arranging the power generation plan, it can complete the peak shaving task of the power system while avoiding water resource waste as much as possible. The losses caused by the hydropower station participating in the peak shaving of the power system are mainly the power waste caused by peak shaving with water abandonment, which is no different from wind and photovoltaic curtailment, and both are a waste of renewable energy. During the conventional operation and conventional peak shaving stages, the power generation cost is a fixed value, so it is no longer considered. Hydropower, as a regulating power source but also a renewable energy source, should be utilized to the greatest extent. Therefore, the water abandonment penalty coefficient is only slightly lower than the penalty coefficients of wind power (W) and photovoltaic power (PV). The present invention adopts the same penalty cost coefficient to maximize the utilization of the peak shaving capacity of hydropower while maximizing the accommodation of wind power and photovoltaic power.

[0048] The step S2 further includes a step S21: The renewable energy generating units include wind power generating units, photovoltaic power generating units, and hydropower generating units. While maximizing the utilization of the peak shaving capacity of hydropower, it is necessary to maximize the accommodation of wind power and photovoltaic power. The peak shaving cost of renewable energy is shown by the following formula:

[0049]

[0050] Wherein, T is the scheduling time period; t is the set moment within the scheduling time period T; f t Ab is the peak shaving cost of renewable energy at the moment t; P t W 、 P t PV 、 P t H are respectively the predicted maximum power and the actual power of the wind power generating unit, the photovoltaic power generating unit, and the hydropower generating unit at the moment t; θ is the penalty cost coefficient.

[0051] Nuclear power has a peak shaving rate of 0.25%-5% FP / min while having a high peak shaving depth, which can appropriately meet the peak shaving requirements of the power grid. It not only plays a positive role in the accommodation of wind power and photovoltaic power, enhances the anti-risk ability of the power grid, improves the operation safety margin of the power grid, but also reduces the operation pressure of other peak shaving units. The fuel replacement cycle of nuclear power is generally relatively fixed, and the cost of replacing fuel within the cycle is not included in the variable cost as an invariant cost. As a kind of clean energy, the participation of nuclear power in the power system peak shaving will cause waste of nuclear fuel, and the insufficiently utilized nuclear fuel will also increase the processing cost during replacement. In addition, frequent power changes in nuclear power will cause instability in the operation of the reactor to a certain extent, increasing the operation and safety costs. The participation of nuclear power in system peak shaving mainly considers stability and safety, as well as fuel utilization and subsequent processing, which are also the main costs of nuclear power peak shaving. In the actual operation process, nuclear power generally uses control rods and boron concentration to control the rapid and slow changes of the reactor respectively, in order to achieve the purpose of controlling the total power output to track the load, and the adjustment range is generally 30%-100% of the rated capacity. The peak shaving method is as Figure 2 shown.

[0052] The step S2 further includes a step S22: The nuclear power peak shaving cost obtained by the dispatching center is:

[0053]

[0054] where, f t N is the nuclear power peak shaving cost at time t; C N is the peak shaving cost coefficient of the nuclear power unit, including the lost electricity and the subsequent processing cost caused by insufficient utilization; C S is the safety cost of nuclear power peak shaving; θ N is the nuclear power safety value coefficient; P t N is the rated operating power of nuclear power and the actual power at time t.

[0055] The standard coal consumption per unit of electricity of the thermal power unit (C) increases with the decrease of the power generation power, and the power and coal consumption cost are represented by a continuous quadratic function. In addition, when the thermal power enters deep peak shaving, the method of injecting oil to stabilize combustion will be adopted to stabilize the power, further increasing the peak shaving fuel cost. The power and cost of the thermal power unit participating in the system peak shaving are as Figure 3 shown.

[0056] The step S2 further includes a step S23: The peak shaving variable cost of the thermal power and gas turbine units obtained by the dispatching center is:

[0057]

[0058] where, is the variable cost of thermal power peak shaving for the i-th thermal power generator at time t; the first part is the quadratic function of the coal consumption characteristics during normal operation, are the coal consumption characteristic coefficients of the i-th thermal power generator respectively, represent the rated power and the current operating power of the i-th thermal power generator at time t respectively; the second part is the total start-stop cost of each thermal power generator, is the single start-stop cost of the i-th thermal power generator, represents the start-stop state of the i-th thermal power generator at time t, represents the start-stop state of the i-th thermal power generator at time t - 1; the third part is the additional cost of fuel injection for deep peak shaving, is the fuel injection cost of the i-th thermal power generator, g C represents the deep peak shaving coefficient of the coal-fired unit;

[0059]

[0060] Among them, is the fuel cost of the j-th gas turbine unit at time t; is the gas turbine cost coefficient; represents the operating power of the j-th gas turbine unit at time t.

[0061] The constructed chemical energy storage power station and pumped storage power station should not only serve a certain power source according to the load, but also be more flexibly incorporated into the combined peak shaving of power sources to maximize their peak shaving value. However, their frequent start-up will cause a certain amount of power loss.

[0062] The step S2 further includes step S24: The operating loss cost of the chemical energy storage power station and the pumped storage power station obtained by the dispatching center is:

[0063]

[0064] Among them, f t L is the operating loss cost of the chemical energy storage power station and the pumped storage power station at time t; θ K 、θ E are the operating cost loss coefficients of the pumped storage power station and the chemical energy storage power station respectively; P t K 、P t E are the operating powers of the pumped storage power station and the chemical energy storage power station at time t respectively.

[0065] Step S3, Double - layer peak - shaving optimization: Set the upper - layer objective function to optimize the fitting degree between the comprehensive power curve of renewable energy generation and the load curve. The upper - layer objective function is used to maximize the fitting degree between the comprehensive power of wind and solar power generation and the load curve, and reduce the load fluctuation; its expression is as follows:

[0066]

[0067] where, \(P\) t Hy 、\(P\) t HG 、\(P\) t HF represent the power of the electrolyzer, hydrogen gas turbine, and hydrogen fuel cell at time \(t\) respectively; is a 0 - 1 variable used to limit the startup scenario of the hydrogen fuel cell; represent the startup state and stop state of the hydrogen fuel respectively; are the maximum power of the wind turbine generator and photovoltaic generator at time \(t\) respectively, and \(P\) t D is the load demand of the system in time period \(t\).

[0068] Step S3 further includes Step S31, constructing the upper - layer constraint conditions: Set corresponding upper and lower limit values for the electrolyzer power, hydrogen gas turbine power, hydrogen gas turbine power ramp rate, hydrogen fuel cell power, and hydrogen storage capacity in the upper - layer objective function, and when the hydrogen gas turbine power reaches the upper limit value of the hydrogen gas turbine power or the upper limit value of the hydrogen gas turbine ramp rate, the hydrogen fuel cell intervenes to supply energy.

[0069] Step S3 further includes setting the lower - layer objective function to control the timing and power of each unit participating in peak - shaving by the dispatching center under the constraint conditions of stable operation, so as to achieve the optimal variable cost of the peak - shaving system operation. The lower - layer objective function is as follows:

[0070]

[0071] where, \(I\) is the number of thermal power generating units; \(J\) is the number of gas turbine units.

[0072] Step S3 further includes Step S32, constructing the lower - layer constraint conditions: Set the power balance constraint for the lower - layer objective function, as follows:

[0073]

[0074] And set corresponding constraint conditions for the actual power of the wind turbine generator, photovoltaic generator, thermal power generating unit, hydro - power generating unit, hydrogen gas turbine, nuclear power generating unit, and the capacity of pumped - storage energy and chemical energy storage.

[0075] Step S3 further includes step S33: The dispatching center uses a mixed-integer non-linear programming method to solve the lower-layer objective function, and controls the timing and power of each unit participating in peak shaving to achieve the optimal variable cost of the peak shaving system operation.

[0076] This application uses a two-layer peak shaving optimization strategy. By setting corresponding upper-layer constraints and lower-layer constraints for the upper-layer objective function and the lower-layer objective function, the fitting degree of the integrated wind-solar output curve and the load curve is maximized, and the net load fluctuation is reduced; and under the condition of meeting the system stable operation constraints, the timing and depth of each unit participating in peak shaving are reasonably optimized, and the operation strategy of the hydrogen energy storage is optimized to achieve the optimal variable cost of the system operation.

[0077] Embodiment 2

[0078] On the basis of Embodiment 1, this embodiment provides a peak shaving economy optimization method for a high-proportion renewable energy power system based on hydrogen energy storage access. The method specifically includes that in step S31, the upper-layer constraints specifically include:

[0079] Step S311, set the electrolyzer (Hy) constraint:

[0080]

[0081] Wherein, P t Hy , are respectively the actual power and the power upper limit value of the electrolyzer at time t.

[0082] Step S312, set the hydrogen gas turbine (HG) constraint:

[0083]

[0084] Wherein, P t HG , ±ΔP HG are respectively the actual power of the hydrogen gas turbine at time t, the upper and lower limit values of the hydrogen gas turbine power, and the upper and lower limit values of the hydrogen gas turbine ramp power.

[0085] Step S313, set the hydrogen fuel cell (HF) constraint:

[0086]

[0087] Wherein: P t HF , respectively represent the actual power and the maximum power of the hydrogen fuel cell at time t.

[0088] Step S314, set the energy storage constraint:

[0089]

[0090] Among them, respectively represent the hydrogen storage amount and the upper and lower limits of the hydrogen energy storage capacity at time t; respectively represent the hydrogen energy storage capacities at the initial time and the end time; respectively represent the hydrogen production and consumption at time t; η Hy 、η HG 、η HF respectively represent the electro-hydrogen conversion efficiencies of the electrolyzer, hydrogen gas turbine unit, and hydrogen fuel cell; θ Hy is the electro-hydrogen conversion coefficient, with the unit of Nm 3 / (MW·h).

[0091] Step S315, constraint on the call relationship between the hydrogen gas turbine and the hydrogen fuel cell:

[0092]

[0093] Among them, ΔP t HG represents the power change amount of the hydrogen gas turbine at time t. When the ramp flexibility of the hydrogen gas turbine is insufficient, the hydrogen fuel cell intervenes.

[0094] In the said step S32, the lower-layer constraint conditions further include:

[0095] Step S321, set the power constraints of the wind turbine generator set (W) and the photovoltaic generator set (PV):

[0096]

[0097] Among them, are respectively the maximum values of the predicted powers of the wind turbine generator set and the photovoltaic generator set at time t.

[0098] Step S322, set the power constraint of the thermal power unit:

[0099]

[0100] Among them, in the on-state, the current actual power of the i-th thermal power generator at time t should be between the maximum and minimum rated powers, where are respectively the upper and lower limits of the power of the i-th thermal power generator technically, and U i,t C represents the start-stop state of the i-th unit at time t.

[0101]

[0102] Among them, are the upward and downward power change rate constraints of the i-th thermal power generator respectively, is the current actual power of the i-th thermal power generator at time t-1;

[0103]

[0104] Among them, Y i is the maximum number of start-stop times of the i-th thermal power generator, and it is ensured that the thermal power generator has and only has one operating state at the same time;

[0105]

[0106] Among them, is the minimum start-stop time of the i-th thermal power generator, represents the start-stop state of the i-th thermal power generator at time t+1, represents the total start-stop state of the unit within the T time period.

[0107] Step S323, set the power constraint of the gas turbine unit:

[0108]

[0109] Among them, represents the maximum power of the j-th gas unit; represents the upward and downward power change rate constraints of the j-th gas unit.

[0110] Step S324, set the power constraint of the hydroelectric unit:

[0111]

[0112] That is, the total power generation during the day at time t should be less than the predicted total power generation.

[0113]

[0114] Among them, is the actual power of the hydroelectric unit at time t-1, △P u H , △P d H represents the upward and downward power change rate constraints of the hydroelectric unit.

[0115] Step S325, set the power constraint of the nuclear power unit:

[0116] To ensure the safe operation of nuclear power units, only one peak-shaving operation is carried out during the day, with continuous operation at full power for no less than 12 hours, and peak-shaving low-power operation for no less than 2 hours. The peak-shaving operation time is 3 hours (downward) + 3 hours (upward) to complete a peak-shaving cycle.

[0117]

[0118] in, There are four operating states for nuclear power units: full power, high power, low power, and peak power; are the state variables of the four operating states of the nuclear power unit at time t, all of which are 0-1 variables.

[0119] Step S326, setting pumped storage capacity constraints:

[0120]

[0121] in, Indicates the upper and lower limits of the power of the pumped storage power station; Provide power variation constraints for pumped storage power plants; is the available capacity of the pumped storage power station at time t; The capacity of the pumped storage power station during the peak load start period; is the change of power station capacity within the time period; is the total capacity of the chemical energy storage power station; The charging and discharging efficiency of the energy storage power station. The available capacity is the total capacity. The daily clearing constraint requires the same initial capacity every day to prepare capacity for peak load regulation on the second day.

[0122] The step S326 further includes setting chemical energy storage constraints:

[0123]

[0124]

[0125] in, Indicates the upper and lower limits of the power of the chemical energy storage power station; is the available capacity of the chemical energy storage power station at time t; The capacity of the chemical energy storage power station during the peak load start period; is the change of power station capacity within the time period; is the total capacity of the chemical energy storage power station; the charging and discharging efficiency is similar to the constraints of the pumped storage power station, but because of its fast climbing speed, there is no climbing constraint.

[0126] The difficulty of the upper-level constraint conditions of the upper-level objective function lies in how to handle the sequential call relationship between the hydrogen gas turbine and the hydrogen fuel cell. Due to the characteristics of the hydrogen fuel cell, such as low power upper limit, high usage cost, and low efficiency, it is required that the access coefficient is only used to quickly supplement power when the flexibility of the hydrogen gas turbine is insufficient, that is, as a sensitive reserve in the peak shaving system. At this time, it is necessary to linearize the call relationship constraint between the hydrogen gas turbine and the hydrogen fuel cell. Here, a 0-1 variable is introduced to process the piecewise function, and M is a maximum value used for assistance, with a value of 10,000 here. At the same time, a very small amount ε is used to assist in segmentation, with a value of 0.0001 here.

[0127] The step S33 further includes setting the call relationship between the hydrogen gas turbine and the hydrogen fuel cell:

[0128]

[0129] Among them, Z t HF1 When taking 1, ΔP t HG is less than the constraint value, When taking 0, ΔP t HG is equal to the constraint value, so as to distinguish the climbing state of the hydrogen gas turbine. When the hydrogen gas turbine cannot meet the sensitivity requirements, the hydrogen fuel cell can be started. Therefore, the overall power of the hydrogen energy storage system is:

[0130]

[0131] The lower-level objective function and the lower-level constraint conditions contain complex mathematical models of quadratic function piecewise functions, which are difficult to solve directly. The nonlinear part is linearized, and the mixed integer nonlinear programming (MINP) method is used to solve it, so as to reasonably configure the operating conditions of each unit to achieve the optimal variable cost of the peak shaving system operation.

[0132] The step S33 further includes step S331, linearization of the deep peak shaving piecewise function of the thermal power unit:

[0133]

[0134] Among them, is a 0-1 variable to judge whether the thermal power unit is in the deep peak shaving state; M is a relatively large number (set to 10,000 here), which is multiplied by the relevant 0-1 variable to provide an upper bound constraint for the variable.

[0135] The step S33 further includes step S332, linearization of the peak shaving of the nuclear power unit:

[0136]

[0137] Among them, respectively represent the state variables of the four operating states of the nuclear power unit at times t-1 and t+1. First, impose operating trend constraints on the operating nuclear power unit to ensure that the unit is only in one operating state at a certain moment. When changing the power, strictly follow the direction or the reverse direction to complete the operation.

[0138]

[0139] This constraint is to achieve 1 daytime power change for the unit.

[0140] The step S33 further includes step S333 of linearizing the relationship between the positive and negative output and the capacity of the pumped storage power station:

[0141]

[0142] Among them, use the 0-1 variable to represent the charge and discharge operating state of the chemical energy storage, and transmit the information to the capacity side to make the capacity change correctly with the output. The chemical energy storage power station is processed similarly.

[0143] Embodiment III

[0144] Based on Embodiments I and II, this embodiment provides a method for optimizing the peaking economy of a high-proportion renewable energy power system with hydrogen energy storage access. The method further includes:

[0145] Taking an actual system in a certain area as the simulation object, the simulation example is as Figure 4 shown. Among them, the units supplying power to this area are 2 coal-fired units of 390 MW, 1 nuclear power unit of 100 MW, 1 hydroelectric unit of 240 MW, the total capacity of the wind farm is 700 MW, the total capacity of the photovoltaic power station is 800 MW, and the load prediction is mainly for time-sharing peaking. Among them, the load prediction and the proportion of each unit are as Figure 5 、 6 shown. An operation plan with pumped storage and chemical batteries for flexible auxiliary peaking as the supplement is adopted to calculate the overall variable cost of the system operation. The optimization effects of the integrated wind and solar power output by three different capacity hydrogen energy storage devices and the optimized output combinations of other units for the optimized curve are shown. The detailed data is shown in Table 1.

[0146] Table 1 Hydrogen energy storage configuration plan

[0147]

[0148] In the case of hydrogen energy configuration 1, in order to suppress the fluctuations in the combined output of new energy caused by the concentrated power generation of photovoltaic during the daytime, the electrolyzer operates at full power of 150 MW from 9 to 15 hours, creating space for the integration and grid connection of new energy, reducing the low-power operation pressure of the remaining units and the phenomena of wind and light curtailment. When the reverse peak shaving phenomenon occurs between the predicted wind power value and the predicted load value at 6 hours, the electrolyzer also operates at full power of 150 MW. At 2 hours, 7 hours, 18 hours, 23 hours, and 24 hours, the hydrogen fuel cell is supplemented and started due to the insufficient peak shaving capacity of the hydrogen gas turbine, comprehensively optimizing the output of new energy. Under this configuration capacity, 1698.31 MWh of new energy power is "moved", accounting for 10.14% of the total new energy power generation. The peak-valley difference of the net load curve is reduced from 1161.81 MW before optimization to 901.80 MW after optimization. However, the fitting degree between the combined output curve and the load curve is not high, the net load curve fluctuates greatly, and each unit still bears a huge peak shaving pressure and there are still phenomena of wind and light curtailment. Wind and light curtailment occur concentratedly from 11h to 16h. At this time, both the coal-fired unit and the hydropower unit are at the constraint boundary. The operating power of the coal-fired unit reaches the lower limit, and the hydropower unit cannot further decrease to achieve the daily cleared power. Due to insufficient peak shaving resources, the lost electricity is 455.63 MWh. Further increasing the hydrogen energy configuration capacity will reduce wind and light curtailment and improve the overall peak shaving flexibility of the system. The simulation results are as Figure 7 shown.

[0149] In the case of hydrogen energy configuration 2, the electrolyzer also operates at full power of 300 MW from 9 to 15 hours. At 6 hours, the electrolyzer also operates at full power of 300 MW to optimize the fluctuations in the net load curve. The electrolyzer, hydrogen gas turbine, and hydrogen fuel cell work together, and the initial fitting effect between the combined output of wind, light, and hydrogen and the load curve appears. Under this configuration capacity, 3234.73 MWh of new energy power is "moved", accounting for 19.31% of the total new energy power generation. The peak-valley difference of the net load curve is reduced from 1161.81 MW before optimization to 662.21 MW after optimization. The fluctuations in the net load curve decrease. Each unit still bears part of the peak shaving pressure, but the phenomena of wind and light curtailment have been significantly improved. The total amount of wind and light curtailment is 19.64 MWh, and basically zero wind and light curtailment is achieved. The simulation results are as Figure 8 shown.

[0150] In the case of Configuration 3, it can be seen from the operation point where the electrolyzer operates at full power of 450 MW only from 11 to 14 hours that the regulation focus shifts from liberating the new energy consumption space to reducing the system peak shaving pressure, increasing the fitting degree of the comprehensive output curve and the load curve, and reducing the fluctuation of the net load curve. Under this configuration capacity, 4150.81 MWh of new energy power is "moved", accounting for 24.77% of the total new energy power generation, and the utilization rate decreases significantly. The peak-valley difference of the net load curve decreases from 1161.81 MW before optimization to 415.49 MW after optimization, the curve fitting degree is significantly improved, the curtailment of wind and light is 0, the power operation of the coal-fired units is stable, and the number of power regulation times is reduced by 10 times and 4 times respectively compared with Configuration 1 and Configuration 2. The obvious peak shaving pressure borne by each unit is significantly reduced. However, due to the frequent participation of hydrogen energy storage in the system peak shaving, power losses occur during the conversion process, reaching 1163.63 MWh in Configuration 3. It can be seen that when meeting the system peak shaving demand, the regulation of the hydrogen energy storage system should be minimized to reduce power losses. The simulation results are as Figure 9 shown.

[0151] Setting hydrogen energy storage devices with a higher capacity can significantly increase the fitting degree of the comprehensive output curve of the wind-solar-hydrogen system and the load curve, and the electrolyzer power has a greater impact on the effect. Hydrogen energy storage peak shaving causes relatively large power losses. The deviation degree of the comprehensive output curve and the load curve in Configuration 1 is reduced by 23.6%, and the power loss is 580.66 MW·h; the fitting degree in Configuration 2 increases and the deviation degree is reduced by 45.2%, and the power loss is 1078.15 MWh; the deviation degree in Configuration 3 is reduced by 64.2%, and the power loss is 1363.64 MWh.

[0152] With the addition of hydrogen energy to the system peak shaving, the consumption degree of wind and photovoltaic power generation is significantly improved. During the process of increasing the capacity from Configuration 1 to Configuration 3, the curtailment of wind and light decreases, and the peak shaving cost of energy storage such as pumped storage power stations also decreases accordingly. From Configuration 1 to Configuration 2, due to the reduction of wind and light curtailment, the total variable cost of the system decreases. However, due to a certain amount of power losses occurring during the regulation process of hydrogen energy, this part of the losses is borne by the coal-fired units, so the cost of the coal-fired units does not decrease significantly. From Configuration 2 to Configuration 3, the cost of wind and light curtailment is further reduced to 0. Due to the large intervention of hydrogen energy, the cost of the coal-fired units further increases, which is not conducive to reducing the total variable cost of the system. The detailed data are shown in Table 2.

[0153] Table 2 Comparison of the variable costs of unit peak shaving in the power system

[0154]

[0155] The present invention significantly improves the utilization efficiency of new energy, reduces the curtailment of wind and light, effectively reduces the system operation cost, and improves the regulation ability and operation stability of the power grid by reasonably optimizing the combined operation of hydrogen energy storage and other power sources.

[0156] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented in whole or in part in the form of a computer program product, the computer program product includes one or more computer instructions. When the computer program instructions are loaded or executed on a computer, the processes or functions described in the embodiments of the present invention are generated in whole or in part. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions may be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions may be transmitted from one website, computer, server, or data center to another website, computer, server, or data center by wire (such as coaxial cable, optical fiber, digital subscriber line (DSL)) or wirelessly (such as infrared, wireless, microwave, etc.). The computer-readable storage medium may be any available medium that can be accessed by a computer or a data storage device such as a server or a data center that includes one or more integrated available media. The available medium may be a magnetic medium (such as a floppy disk, hard disk, magnetic tape), an optical medium (such as a DVD), or a semiconductor medium (such as a solid state disk (SSD)).

[0157] Although the present disclosure has been described in connection with specific embodiments thereof, many alternatives, modifications, and variations of these embodiments will be apparent to those of ordinary skill in the art in light of the foregoing description. Therefore, any omissions, modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the embodiments of the present disclosure shall be included within the protection scope of the present disclosure.

Claims

1. A method for optimizing the peak load economic performance of a high-proportion renewable energy power system based on hydrogen energy storage, characterized in that: The method comprises the following steps: Step S1, constructing a multi-source joint peak-shaving system: the multi-source joint peak-shaving system includes renewable energy generator sets, thermal power units, nuclear power units, hydrogen energy storage systems and dispatching centers; the power generated by each unit is all connected to the power grid; the hydrogen storage system specifically includes an electrolyzer, a hydrogen gas turbine, a hydrogen fuel cell, and a high-pressure gaseous hydrogen storage tank, which is used to electrolyze water to produce hydrogen and store the excess power of the power grid under the control of the dispatching center for peak shaving, and to generate electricity through hydrogen gas turbines or hydrogen fuel cells to fill the valley when the power generation is insufficient; Step S2, obtaining peak-shaving variable costs: the dispatch center obtains renewable energy peak-shaving costs, nuclear power peak-shaving costs, thermal power and gas-fired units peak-shaving variable costs, and operating loss costs of chemical energy storage stations and pumped storage power stations; Step S3, double-layer peak-shaving optimization: set the upper objective function to optimize the fit between the comprehensive power curve of renewable energy power generation and the load curve; the lower objective function is used to control the timing and power of each unit participating in the peak-shaving by the dispatching center under the constraint of meeting the stable operation, so as to achieve the optimal variable cost of the peak-shaving system operation.

2. According to claim 1, a method for optimizing the peak load economic performance of a high-proportion renewable energy power system based on hydrogen energy storage, characterized in that: The step S2 further includes step S21: the renewable energy generator set includes a wind generator set, a photovoltaic generator set, and a hydropower generator set. While maximizing the peak-shaving capacity of hydropower, it is necessary to consume wind power and photovoltaic power to the maximum extent. The peak-shaving cost of renewable energy is shown in the following formula: Where T is the scheduling time period; t is the set time in the scheduling time period T; f t Ab is the peak load cost of renewable energy at time t; are the predicted maximum power and actual power of wind turbine, photovoltaic generator and hydropower generator at time t respectively; θ is the penalty cost coefficient.

3. According to claim 2, a method for optimizing the peak load economic performance of a high-proportion renewable energy power system based on hydrogen energy storage, characterized in that: The step S2 further includes step S22: the nuclear power peak load regulation cost obtained by the dispatching center is: Among them, f t N is the peak-shaving cost of nuclear power at time t; C N is the peak load regulation cost coefficient of nuclear power units, including the lost electricity and the subsequent processing costs caused by the failure to fully utilize the electricity; C S is the safety cost of nuclear power peak regulation; θ N is the nuclear power safety value coefficient; P t N is the rated operating power of nuclear power and the actual power at time t.

4. According to claim 3, a method for optimizing the peak load economic performance of a high-proportion renewable energy power system based on hydrogen energy storage, characterized in that: The step S2 further includes step S23: the variable cost of peak load regulation of the thermal power and gas units obtained by the dispatching center is: in, is the variable cost of thermal power peak regulation of the i-th thermal power generator at time t; the first part is the quadratic function of the coal consumption characteristics of conventional operation, are the coal consumption characteristic coefficients of the i-th thermal generator, They are respectively represented as the rated power and current operating power of the i-th thermal generator at time t; the second part is the total start-up and shutdown cost of each thermal generator, is the single start-stop cost of the i-th thermal generator, represents the start and stop status of the i-th thermal generator at time t, represents the start and stop status of the i-th thermal generator at time t-1; the third part is the additional cost of deep peak load regulation. is the oil cost of the i-th thermal generator, g C Indicates the deep peak regulation coefficient of coal-fired units; in, is the fuel cost of the j-th gas generator set at time t; is the gas engine cost coefficient; Represents the operating power of the jth gas generator set at time t.

5. According to claim 4, a method for optimizing the peak load economic performance of a high-proportion renewable energy power system based on hydrogen energy storage is characterized in that: The step S2 further includes a step S24: the operation loss costs of the chemical energy storage power station and the pumped storage power station obtained by the dispatching center are: Among them, f t L is the operating loss cost of the chemical energy storage power station and the pumped storage power station at time t; θ K ,θ E are the operating cost loss coefficients of the hydropower station and the chemical energy storage power station respectively; P t K , P t E are the operating powers of the hydropower station and the chemical energy storage power station at time t respectively.

6. The method for optimizing the peak load economic performance of a high-proportion renewable energy power system based on hydrogen energy storage according to claim 5 is characterized in that: The step S3 further includes: the upper objective function is used to maximize the fitting degree of the wind and solar power generation integrated power and the load curve to reduce load fluctuations; its expression is shown in the following formula: in, They are respectively represented as the power of the electrolyzer, hydrogen gas turbine, and hydrogen fuel cell at time t; It is a 0-1 variable used to limit the startup scenario of the hydrogen fuel cell; Respectively indicate the start state and stop state of hydrogen fuel; are the maximum power of wind turbine generator set and photovoltaic generator set at time t, P t D is the load demand of the system in time period t.

7. The method for optimizing the peak load economic performance of a high-proportion renewable energy power system based on hydrogen energy storage according to claim 6 is characterized in that: The step S3 further includes: the lower layer objective function is as follows: Among them, I is the number of thermal power generating units; J is the number of gas turbine units.

8. The method for optimizing the peak load economic performance of a high-proportion renewable energy power system based on hydrogen energy storage according to claim 7 is characterized in that: The step S3 further includes a step S31, constructing an upper-level constraint condition: in the upper-level objective function, corresponding upper and lower limits are set for the electrolyzer power, the hydrogen gas turbine power, the hydrogen gas turbine power climbing power, the hydrogen fuel cell power, and the hydrogen storage capacity; and when the hydrogen gas turbine power reaches the upper limit value of the hydrogen gas turbine power or the upper limit value of the hydrogen gas turbine power climbing power, the hydrogen fuel cell intervenes to supply energy.

9. The method for optimizing the peak load economic performance of a high-proportion renewable energy power system based on hydrogen energy storage according to claim 8 is characterized in that: The step S3 further includes a step S32 of constructing a lower-level constraint condition: setting a power balance constraint on the lower-level objective function, as shown in the following formula: And set corresponding constraints on the actual power of wind turbines, photovoltaic turbines, thermal power generators, hydropower generators, hydrogen gas turbines, nuclear power generators and the capacity of pumped storage and chemical energy storage.

10. The method for optimizing the peak load economic performance of a high-proportion renewable energy power system based on hydrogen energy storage according to claim 9, characterized in that: The step S3 further includes a step S33: the dispatching center uses a mixed integer nonlinear programming method to solve the lower-level objective function, and controls the timing and power of each unit participating in the peak load regulation to achieve the optimal variable cost of the peak load regulation system operation.

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