A method and system for evaluating rational utilization rate of fluctuating renewable energy

Abstract

The application provides a fluctuant renewable energy rational utilization rate evaluation method and system, comprising obtaining a target power system network structure and data parameters; evaluating consumption cost; calculating abandoned power cost; calculating environmental cost; analyzing system operation constraints and physical constraints involved in power system operation, combining renewable energy consumption cost, abandoned power loss and environmental cost to construct a renewable energy rational utilization rate evaluation model; based on a target renewable energy penetration rate, using the evaluation model, solving under system operation constraints and physical constraints to obtain the fluctuant renewable energy rational utilization rate under the renewable energy penetration rate. The application constructs a renewable energy rational utilization rate evaluation model based on analyzing various marginal costs and social benefits of renewable energy generation, realizes renewable energy rational utilization rate evaluation, is helpful for completing a low-carbon target, and guarantees power grid safe dispatching and control.

Description

Technical Field

[0001] This invention belongs to the field of power system operation and control technology, and relates to a method and system for assessing the reasonable utilization rate of fluctuating renewable energy. Background Technology

[0002] The statements in this section are merely background information related to the present invention and do not necessarily constitute prior art.

[0003] With the emergence of problems such as global warming, the large-scale development of wind and solar power is necessary in the coming decades to achieve low-carbon operation goals. High-penetration renewable energy is undoubtedly the future direction of power grid development. However, the grid connection of renewable energy power plants poses significant challenges to power system dispatching and ensuring grid security and stability. Current grid dispatching and control methods are ill-suited to the future power grid with a large influx of renewable energy.

[0004] According to the inventor, current discussions on the development of renewable energy sources such as wind and solar power in the power grid primarily focus on reducing wind and solar curtailment and maximizing renewable energy utilization. This is often aided by flexible resources such as energy storage and adjustable thermal power units to achieve power balance and stable operation of the power grid. However, as the penetration rate of renewable energy in the power grid increases, simply pursuing the complete absorption of renewable energy and maximizing its utilization is unrealistic.

[0005] Renewable energy (NEA) should have different optimal utilization rates at different penetration rates, referred to as reasonable utilization rates. When NEA penetration is low, pursuing near 100% NEA absorption is scientifically sound and achievable. However, as NEA penetration in the grid increases, for example to 30%, 40%, or even over 50%, the relatively smaller share of grid flexibility resources will be insufficient to support full NEA absorption or maintain a high utilization rate. When curtailment is not permitted, the system can only accommodate a moderate share of Variable Renewable Energy (VRE), while when curtailment is allowed, the system can accommodate a higher share of VRE. Actively reducing excess wind and solar power supply to achieve supply-demand balance is crucial for mitigating intermittency and providing robust wind and solar power generation at the lowest cost. Summary of the Invention

[0006] To address the aforementioned issues, this invention proposes a method and system for assessing the rational utilization rate of fluctuating renewable energy. Based on the analysis of various marginal costs and social benefits of renewable energy power generation, this invention constructs a model for assessing the rational utilization rate of renewable energy, thereby enabling the assessment of the rational utilization rate of renewable energy. This contributes to the achievement of low-carbon goals and ensures the safe dispatch and control of the power grid.

[0007] According to some embodiments, the present invention adopts the following technical solution:

[0008] A method for assessing the reasonable utilization rate of fluctuating renewable energy includes the following steps:

[0009] Obtain the target power system network structure and data parameters;

[0010] Analyze the additional system costs caused by renewable energy consumption and assess the consumption costs;

[0011] The value of generating electricity from fluctuating renewable energy sources is evaluated using a linear value curve, and the cost of curtailment is calculated.

[0012] Assess the impact of renewable energy consumption on the system's environmental benefits by calculating environmental costs relative to thermal power generation.

[0013] This paper analyzes the system operation constraints and physical constraints involved in the operation of the power system, and constructs an assessment model for the reasonable utilization rate of renewable energy by combining the renewable energy consumption cost, curtailment loss and environmental cost.

[0014] Based on the target renewable energy penetration rate, the evaluation model is used to solve the problem under system operation constraints and physical constraints, thereby obtaining the reasonable utilization rate of fluctuating renewable energy under the target renewable energy penetration rate.

[0015] As an alternative implementation method, when obtaining the target power system network structure and data parameters, the load forecast results and the maximum power generation capacity per unit capacity of fluctuating renewable energy should be clearly defined.

[0016] As an alternative implementation method, the specific process of analyzing the additional system cost composition caused by renewable energy consumption includes analyzing configuration cost, balancing cost and grid cost, wherein the grid flexibility transformation cost is used as the configuration cost; the grid flexibility transformation cost is used as the balancing cost; and the grid cost is used as the cost of all new renewable energy installed capacity connected to the grid.

[0017] As an alternative implementation method, the specific process of evaluating the power generation value of fluctuating renewable energy using a linear value curve includes determining twice the average power generation of fluctuating renewable energy as the unit cost value point of fluctuating renewable energy, taking the point of maximum load demand as the zero value point, and constructing a linear value curve for fluctuating renewable energy.

[0018] Furthermore, when evaluating using a linear value curve, the original linear calculation method for the cost of curtailment losses is changed to a non-linear quadratic function calculation method, and the quadratic function is further linearized piecewise to re-evaluate the value of curtailment losses of fluctuating renewable energy.

[0019] As an alternative implementation, the constraints include power balance constraints at each node, line transmission capacity constraints, line power flow calculation constraints, and unit generating capacity constraints.

[0020] As an alternative implementation method, the specific process of constructing a renewable energy rational utilization rate assessment model by combining renewable energy consumption costs, curtailment losses and environmental costs includes constructing a mathematical model for assessing the rational utilization rate of renewable energy with the objective function of optimizing the total cost composed of renewable energy consumption costs, curtailment costs and environmental costs.

[0021] As an alternative implementation method, based on the target renewable energy penetration rate, the evaluation model is used to set the penetration rate during the solution process under system operation constraints and physical constraints. The penetration rate calculation formula is used as a constraint and incorporated into the overall system cost optimization model corresponding to the renewable energy rational utilization rate evaluation. The optimal system cost and the rational utilization rate of each renewable energy source are evaluated under the penetration rate.

[0022] Iteratively set the penetration rate, solve for the optimal system cost and the reasonable utilization rate of each renewable energy source under each penetration rate, form the system penetration rate-utilization rate curve and the penetration rate-optimal system cost curve, and determine the optimal reasonable utilization rate among the reasonable utilization rates.

[0023] A system for assessing the rational utilization rate of fluctuating renewable energy sources, comprising:

[0024] The data initialization module is configured to acquire the target power system network structure and data parameters;

[0025] The renewable energy consumption cost calculation module is configured to analyze the additional system cost composition caused by renewable energy consumption and to assess the consumption cost.

[0026] The curtailment cost calculation module is configured to evaluate the generation value of fluctuating renewable energy using a linear value curve and calculate the curtailment cost.

[0027] The environmental cost calculation module is configured to assess the impact of renewable energy consumption on the system's environmental benefits and calculate environmental costs relative to thermal power generation.

[0028] The total cost optimization solution module is configured to analyze the system operation constraints and physical constraints involved in the operation of the power system, and to construct an evaluation model for the reasonable utilization rate of renewable energy by combining the renewable energy consumption cost, curtailment loss and environmental cost.

[0029] The reasonable utilization rate output module is configured to solve, based on the target renewable energy penetration rate, the evaluation model under system operation constraints and physical constraints to obtain the fluctuating renewable energy reasonable utilization rate under the renewable energy penetration rate.

[0030] A computer-readable storage medium storing a plurality of instructions adapted for loading by a processor of a terminal device and executing steps in the method.

[0031] A terminal device includes a processor and a computer-readable storage medium, the processor being configured to implement instructions; the computer-readable storage medium being configured to store a plurality of instructions adapted to be loaded by the processor and executed in accordance with the steps of the method described therein.

[0032] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0033] This invention addresses the issue of reduced system efficiency in power systems due to the additional system costs incurred in absorbing fluctuating renewable energy inputs. It conducts research on the rational utilization rate of renewable energy applicable to different power systems. Unlike approaches that simply consider renewable energy efficiency as the utilization rate, this invention defines the impact of renewable energy absorption on power system efficiency as the system efficiency of renewable energy, based on the overall interests of the power system. A rational utilization rate assessment method for improving renewable energy efficiency is provided, accurately evaluating the optimal utilization rate of renewable energy in the system, maximizing system efficiency, and optimizing the overall system cost.

[0034] This invention improves the method for assessing the fixed value of fluctuating renewable energy to a linear value assessment method, and further improves the linear calculation method for the cost of curtailment losses of fluctuating renewable energy to a quadratic function calculation method for the cost of curtailment costs of fluctuating renewable energy. By comprehensively considering both system load demand and renewable energy generation capacity, this invention more reasonably assesses the value of renewable energy and its curtailment losses, thereby improving the accuracy of the assessment results.

[0035] This invention addresses the problem of solving large-scale quadratic programming problems arising from the improved calculation method for curtailment losses of fluctuating renewable energy. By using a piecewise linear approximation method for quadratic functions, each quadratic function is represented piecewise linearly, transforming the quadratic programming problem into a mixed-integer linear programming problem. This allows the nonlinear problem of the rational utilization rate of renewable energy to be solved linearly, simplifying the solution process and ensuring the efficiency of the entire evaluation process.

[0036] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, preferred embodiments are described below in detail with reference to the accompanying drawings. Attached Figure Description

[0037] The accompanying drawings, which form part of this invention, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an improper limitation of the invention.

[0038] Figure 1 This is a flowchart of a method for assessing the rational utilization rate of renewable energy provided in Embodiment 1 of the present invention.

[0039] Figure 2 This is a design diagram for the unit cost of fluctuating renewable energy provided in Embodiment 1 of the present invention.

[0040] Figure 3 This is a schematic diagram illustrating the calculation of curtailment losses for fluctuating renewable energy provided in Embodiment 1 of the present invention.

[0041] Figure 4 This is an improved assessment process for the rational utilization rate of renewable energy provided in Embodiment 1 of the present invention.

[0042] Figure 5 This is a schematic diagram of the HRP-9 system network structure provided in Embodiment 1 of the present invention.

[0043] Figure 6 This is a schematic diagram of the HRP-38 system network structure provided in Embodiment 1 of the present invention.

[0044] Figure 7 The optimal system cost penetration rate curves for the HRP-9 system under different scenarios provided in Embodiment 1 of the present invention.

[0045] Figure 8 The permeability-RES utilization curves of the HRP-9 system under different scenarios provided in Embodiment 1 of the present invention are shown.

[0046] Figure 9 The curves showing the renewable energy penetration rate and reasonable utilization rate of the HRP-9 system in various scenarios provided in Embodiment 1 of the present invention.

[0047] Figure 10The penetration rate-optimal system cost curve of the HRP-38 system provided in Embodiment 1 of the present invention.

[0048] Figure 11 The penetration rate-RES utilization rate curve of the HRP-38 system provided in Embodiment 1 of the present invention. Detailed Implementation

[0049] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0050] It should be noted that the following detailed description is illustrative and intended to provide further explanation of the invention. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0051] Where there is no conflict, the embodiments and features in the embodiments of the present invention can be combined with each other.

[0052] Example 1

[0053] As introduced in the background section, by comprehensively considering the system benefits such as the cost of renewable energy generation, curtailment losses, and environmental costs, the impact of renewable energy consumption on the overall system benefits is defined as the renewable energy system efficiency. To maximize the renewable energy system efficiency, a method for evaluating the rational utilization rate of renewable energy is proposed. First, the additional system costs brought about by the grid connection of fluctuating renewable energy generation are analyzed, identifying the composition of these additional system costs, i.e., consumption costs, and constructing a consumption cost calculation model. Second, the VRE (Volatile Renewable Energy) value assessment method is improved, and a VRE curtailment loss cost calculation model is constructed. Third, an environmental cost calculation model is constructed based on thermal power generation and corresponding unit environmental costs. Finally, a renewable energy rational utilization rate evaluation model is constructed in conjunction with grid constraints, and the evaluation method flow is given. By iteratively setting the renewable energy penetration rate k, the rational utilization rate of fluctuating renewable energy under different penetration rates is solved, and their relationship curves are plotted.

[0054] For specific embodiments, please refer to the appendix. Figure 1 As shown, a method for assessing the reasonable utilization rate of fluctuating renewable energy includes the following steps:

[0055] Step 1: Determine the power system network structure and data parameters for which renewable energy utilization rate assessment is required, initialize the power supply structure, and clarify the load forecasting results P. load and the maximum power generation capacity per unit capacity of fluctuating renewable energy P base .

[0056] Step 2: Analyze the composition of additional system costs caused by renewable energy consumption, and analyze the calculation methods of configuration costs, flexible costs and grid costs in the additional system costs;

[0057] Step 2.1: The configuration cost within the renewable energy consumption cost refers to the additional costs incurred by other adjustable generating units due to renewable energy consumption. This includes more unit start-ups and shutdowns, more frequent cycles, steeper ramp-up requirements, lower power generation efficiency, and increased power generation costs due to aging equipment. Referring to the numerous flexible retrofits of thermal power units undertaken in recent years in China to promote renewable energy consumption and improve the grid's power supply security, the cost of these flexible retrofits within the grid is taken as the main configuration cost, written as...

[0058]

[0059] In the formula, c1 is the unit cost of flexibility modification. TG represents the capacity for flexible retrofitting of unit i, where TG is the set of thermal power units and i represents the i-th unit.

[0060] Step 2.2: The balancing cost in the grid integration cost refers to the increased spinning reserve cost due to the uncertainty and forecasting deviation of new energy sources. Forecasting deviations of a high proportion of new energy sources will require the system to configure more spinning reserves. The cost of the increased spinning reserves in the grid is considered the main part of the balancing cost. Here, the increased spinning reserves are mainly reserves from new thermal power plants, denoted as...

[0061]

[0062] In the formula, c2 is the unit cost of flexibility modification. This refers to the additional installed capacity of unit i.

[0063] Step 2.3: For grid costs within the absorption cost, this refers to the increased transmission and distribution grid costs due to the geographical dispersion of new energy power plants and the need to address interconnection limitations, as well as the grid connection costs for integrating new energy power plants into the grid. This includes grid expansion and upgrades, and also includes increased transmission and distribution network losses. Because large-scale power system planning often involves too many power sources and simplifies the system's line network, it is difficult to measure the specific construction costs of transmission lines. Furthermore, power source planning and transmission line planning are often carried out separately in practice. Therefore, line modification costs are not included in the grid cost. The grid cost is written as...

[0064]

[0065] In the formula, c3 and c4 are the grid connection costs per unit capacity of wind power and photovoltaic power, respectively.

[0066] Step 3: Improve the commonly used fixed value assessment method for VRE by assessing the power generation value of VRE using a linear value curve, and construct an improved method for assessing renewable energy curtailment losses.

[0067] Step 3.1: The linear calculation method for renewable energy curtailment costs treats each kilowatt-hour of renewable energy as having equal value, which is reasonable to some extent for controllable renewable energy sources such as hydropower. However, for highly volatile renewable energy sources such as wind and solar power, which are difficult to absorb and incur additional system costs, their value is not constant. The value of VRE (Volatile Renewable Energy) generation is evaluated using a linear value curve. First, a value of 2P is defined as twice the annual average power generation of the renewable energy source. ave The unit cost value point is as follows: Figure 2 As shown, this characterizes the tendency of the power system to receive power in a 2P configuration. ave Fluctuating power generation within a certain range; defining the point at which the system load demand power is at a certain moment as the zero-value point of renewable energy, characterizing that the portion of renewable energy generation exceeding load demand has no value. Based on the mathematical theorem of "two points and one line," the value curve of fluctuating renewable energy is constructed as follows:

[0068]

[0069] In the formula, c cur For the fixed unit cost of renewable energy, P load The system load demand is represented by η, where η is the ratio of generator capacity to the total capacity of this type of generator, P represents the actual power generation, and f is the total load demand. c (P) represents a piecewise linear renewable energy value curve, as shown in the attached figure. Figure 3 As shown in the image.

[0070] Step 3.2: Piecewise linear value curve f based on renewable energy c (P) uses the area corresponding to the integral of the value of renewable energy curtailment and the amount of renewable energy curtailment as the cost of renewable energy curtailment loss. A specific demonstration is attached. Figure 3 The formula for calculating the quadratic function of renewable energy curtailment loss is as follows:

[0071] f(P actual )=a2(P actual ) 2 +a1P actual -a0 (5)

[0072] In the formula, P actual The actual power generation is given by a0, a1, and a2, which are the coefficients of a quadratic function. The calculation formula is as follows:

[0073]

[0074]

[0075]

[0076] In the formula, P forecase This represents the theoretical prediction of the maximum generating capacity of fluctuating renewable energy sources.

[0077] Step 3.3: Calculate the curtailment loss cost of fluctuating renewable energy sources such as wind power and photovoltaics based on equations (5) to (8). Substitute the corresponding predicted values ​​and average values ​​to obtain the corresponding quadratic functions. When calculating the curtailment loss for a whole year, let c5 and c6 be the unit curtailment cost of wind power and photovoltaics, respectively. Calculate the curtailment loss cost of wind power and photovoltaics respectively.

[0078]

[0079]

[0080] In the formula, F cur_wind For the cost of wind power curtailment losses, F cur_PV For the cost of solar power curtailment losses, f i,t (P i,t Let t represent the cost of power curtailment for unit i at time t, where T is the total number of hours in a year, which is 8760 hours in a year, i.e., T = 8760.

[0081] Step 3.3: Due to the improved calculation method for curtailment losses of fluctuating renewable energy, a nonlinear quadratic function calculation method has been formed, transforming the optimization problem into a large-scale quadratic programming problem. The objective function contains a large number of different quadratic functions for different systems. For example, when evaluating the reasonable utilization rate of a system with 33 fluctuating renewable energy units, the objective function for optimizing the total system cost will contain 33 × 8760 = 289080 different quadratic functions, making the optimization problem extremely difficult to solve. Therefore, a piecewise linear approximation method is used to represent each quadratic function piecewise linearly, transforming the quadratic programming problem into a mixed-integer linear programming problem. This transforms the curtailment loss cost from linear to quadratic nonlinearity to piecewise linearization of quadratic functions. For the quadratic function f(P) = a²P... 2 Piecewise linearization of +a1P+a0 begins by determining the parameters of each quadratic function as shown below. Here, η represents the ratio of a certain generator's capacity to the total capacity of that type of generator. i With the total load value P t load for

[0082]

[0083]

[0084] In the formula, I represents a set of a certain type of wind power or photovoltaic units. Let N be the load demand of node n at time t, and N be the number of nodes.

[0085] Average annual power generation of renewable energy P ave for

[0086]

[0087] In the formula, This is the theoretical prediction of the maximum generating capacity of the fluctuating renewable energy unit i at time t.

[0088] If the number of segmentation points is uniformly X, then the segmentation point b of the quadratic function is determined. x as follows:

[0089]

[0090] Corresponding to the number of segmentation points, X continuous variables w are introduced. x And introduce X-1 0-1 variables, and the introduced variables meet the following constraints:

[0091]

[0092] By introducing variables, the piecewise linear approximation of the quadratic function is constructed as follows:

[0093]

[0094]

[0095] In the above, by adding new variables and constraints, the piecewise linearization of the quadratic function for calculating the cost of curtailment losses from fluctuating renewable energy was achieved.

[0096] Step 3.4: Calculate the cost of hydropower curtailment. Since hydropower is relatively controllable among renewable energy sources, the cost of renewable energy curtailment is calculated using a linear calculation method as follows:

[0097]

[0098] In the formula, c7 represents the unit cost of abandoned hydropower, HG represents the set of hydropower units, and P i hy_mean This represents the theoretical average output value of hydropower unit i.

[0099] Step 3.5: Finally, by combining the curtailment costs of wind power, solar power, and hydropower, the total curtailment cost of renewable energy is constructed as follows:

[0100]

[0101] Step 4: Calculate the environmental cost of renewable energy. Since renewable energy generation is complementary to non-renewable energy generation, in systems with only thermal power and renewable energy, the environmental cost of renewable energy is equivalent to that of thermal power, and the calculation is based on the environmental cost of thermal power. For thermal power units in adjustable generating units, compared to renewable energy, thermal power consumes fossil fuels, causing environmental pollution and exacerbating the greenhouse effect. This part can be described as the environmental cost of thermal power. Under the premise of ensuring sufficient absorption capacity of the power system and guaranteeing the operating environment of thermal power regulating units, it is more advisable to use renewable energy for power generation, improve the power generation efficiency of renewable energy, and reduce the environmental cost of thermal power. The environmental cost calculation for thermal power is as follows:

[0102]

[0103] In the formula, c8 represents the unit environmental cost of thermal power, and P i,t This represents the actual output of unit i at time t.

[0104] Step 5: Combining the operational and physical constraints of the power system, construct a mathematical model for evaluating the rational utilization rate of renewable energy with the objective function of optimizing the total cost consisting of renewable energy consumption cost, curtailment cost, and environmental cost.

[0105] Step 5.1: First, based on the characteristics of the power system, analyze the constraints in the total system cost optimization model. For a power system, the relevant planning problems are inevitably subject to the operational constraints of the power system and the objective physical constraints existing in the power grid. These include power balance constraints at each node, transmission capacity constraints of lines, power flow calculation constraints of lines, and generating capacity constraints of generating units.

[0106] The nodal power balance constraint is written as

[0107]

[0108] In the formula, Let P be the load of node n at time t, where i ~ n represent generators i connected to node n. mn,t It is the transmission power of the power transmission line mn.

[0109] In power system planning problems, DC power flow is usually used instead of AC power flow for calculations; therefore, the constraints for line power flow calculation are as follows:

[0110] P mn,t =-b mn (θ m,t -θ n,t ) (twenty two)

[0111] Among them, b mn It is the line susceptance, θ m,t θn,t Let m and n represent the phase angles of nodes m and n at time t, respectively.

[0112] When a power transmission line is in operation, it is constrained by the line's transmission capacity:

[0113]

[0114] In the formula, It is the maximum transmission capacity of the transmission line mn.

[0115] Generator units are constrained by their power generation capacity when operating. Thermal power, wind power, photovoltaic power, and hydropower have different power generation capacity constraints. The output constraints of different types of generator units are as follows:

[0116]

[0117]

[0118]

[0119] In the formula, This is the minimum output of generator i. This represents the maximum output of generator i, numerically equivalent to the generator's installed capacity. Mon represents the set of times corresponding to each month. This represents the average monthly hydropower output capacity of unit i in the month containing time t.

[0120] Since generator sets do not absorb power from the grid, their minimum output should be greater than zero.

[0121]

[0122] During planning, to prevent dispatchable power plants such as thermal power from losing their market competitiveness and investment intentions due to the priority effect, which would lead to a lack of regulatory resources such as thermal power and a loss of the ability to consume fluctuating renewable energy and support power balance, the utilization hours of each power plant should be greater than a certain value to ensure the profitability of dispatchable power plants or various types of power plants. Each power plant should be subject to a minimum annual utilization hour constraint as follows:

[0123]

[0124] In the formula, H Profit This represents the minimum number of hours of utilization per year.

[0125] The renewable energy penetration rate of a system is often difficult to measure and control in actual production. However, in advance planning simulations, the penetration rate calculation can be incorporated into the constraints to measure the optimal system cost and reasonable utilization rate of renewable energy at various penetration rates. The penetration rate is calculated as follows:

[0126]

[0127] In the formula, RES represents the set of renewable energy units, and ALL represents the combination of all power sources.

[0128] Step 5.2: Based on the cost functions constructed in Steps 2-4 and the constraints and introduced constraints involved in Step 5.1, construct the overall system cost optimization model corresponding to the assessment of the reasonable utilization rate of renewable energy as follows:

[0129]

[0130] st(14)(15)(21)~(29) (30)

[0131] Step 6: Based on the overall system cost optimization model corresponding to the assessment of the reasonable utilization rate of renewable energy, introduce penetration rate constraints to construct the assessment process of the reasonable utilization rate of renewable energy, and realize the assessment of the reasonable utilization rate of renewable energy.

[0132] Step 6.1: Set the penetration rate k and incorporate the penetration rate calculation formula as a constraint into the overall system cost optimization model corresponding to the assessment of the reasonable utilization rate of renewable energy. Evaluate the optimal system cost and the reasonable utilization rate of each renewable energy source under the penetration rate k.

[0133] Step 6.2: Iteratively set the penetration rate k and solve for the optimal system cost and the reasonable utilization rate of each renewable energy source according to Step 6.1, forming the system penetration rate-utilization rate curve and the penetration rate-optimal system cost curve. Find the optimal reasonable utilization rate among the reasonable utilization rates. The iterative process is as follows: Figure 4 As shown.

[0134] Case Analysis

[0135] The simulation examples were performed on a PC platform with a 12th Gen Intel® Core™ i7-12700 CPU and 64GB of memory. The simulation system mainly includes a 9-node system with high renewable energy penetration: the HRP-9 system; and a 38-node test system based on the 750kV Northwest my country power grid, designed for transmission network planning and operation through grid simplification and data anonymization: the HRP-38 system. In the simulation system, the HRP-9 and HRP-38 systems under different initial power supply structures were simulated and their renewable energy penetration and utilization rates were demonstrated according to the reasonable utilization rate assessment model and process in steps 5 and 6. Because the grid structure of the large-scale Northwest power grid has been simplified, a large amount of detailed line structure has been lost. Simulation calculations were performed and the renewable energy penetration and utilization rate relationship was demonstrated without considering the specific grid line modification costs. The structures of the HRP-9 and HRP-38 systems are as follows: Figure 5 , Figure 6 As shown.

[0136] This study investigates the relationship between high renewable energy penetration and renewable energy system costs in the HRP-9 system, comparing the relationship curves between additional renewable energy system costs and penetration rates under different systems. By changing the system's power supply structure, the simulation examples are conducted under three different initial power supply structures. With a total installed capacity of 44160 MVA, the installed capacity ratios of thermal power, photovoltaic power, wind power, and hydropower are adjusted to simulate three different initial power supply structures of the power system, as shown in the table below.

[0137] Table 1. Three different power supply structures (MW) for the HRP-9 system

[0138]

[0139] Simulations were conducted for initial installed capacity under scenarios I, II, and III, and the results were evaluated based on the renewable energy rational utilization rate assessment model. Figure 4 The process exploration system and the relationship between penetration rate and optimal system cost, and the relationship between penetration rate and reasonable utilization rate. The model (30) was solved using the YALMIP toolbox and CPLEX solver in Matlab. The curves of the relationship between renewable energy penetration rate and optimal system cost in different scenarios are shown below. Figure 7 As shown.

[0140] In Scenario I, the optimal system cost is 589.5 million yuan when the renewable energy penetration rate is 49%. In Scenario II, the optimal system cost is 546.44 million yuan when the renewable energy penetration rate is 53%. In Scenario III, the optimal system cost is 522.83 million yuan when the renewable energy penetration rate is 55%. Comparing Scenario I to Scenario III, firstly, Scenario I and Scenario II have the same hydropower resources, which can be used as flexible adjustment resources for fluctuating renewable energy. The difference lies in that Scenario I has a larger initial thermal power capacity, while Scenario II has a larger initial proportion of fluctuating renewable energy capacity. The optimal system cost for both decreases slowly with the penetration rate when the penetration rate is low. After reaching the optimal system cost, the optimal system cost maintains a relatively stable growth with the increase in penetration rate. However, when the penetration rate exceeds a certain limit, the system cost will increase rapidly exponentially, and the demand for system flexibility resources will increase rapidly. When the system's thermal power flexibility adjustment capacity is exhausted and not decommissioned, the renewable energy penetration rate will not be able to continue to grow. The extreme value of system penetration rate growth in Scenario I is 61%, and the extreme value of penetration rate growth in Scenario II is 69%. For Scenario II and Scenario III, both have the same thermal power capacity, but the latter has more hydropower resources available for flexible adjustment. Similarly, the optimal system cost for both decreases slowly with low penetration rates. After reaching the optimal system cost, the system cost maintains a relatively stable increase with increasing penetration rates. However, when the penetration rate exceeds a certain limit, the system cost will increase rapidly exponentially, leading to a rapid increase in the demand for flexible system resources. Scenario III has more flexible adjustment resources, thus supporting a higher system penetration rate, with an achievable maximum penetration rate of 73%. The adjustable resources in the system determine the maximum renewable energy penetration rate that the system can achieve. However, conversely, as the system penetration rate increases, the corresponding system cost will increase rapidly.

[0141] Analysis of the penetration rate and rational utilization rate of renewable energy in different scenarios, the curves of penetration rate and rational utilization rate of RES are as follows: Figure 8As shown, the highest reasonable utilization rates for scenarios I through III are 97.62%, 97.02%, and 100%, respectively, corresponding to system penetration rates of 33%, 39%, and 33%. After reaching the peak of the reasonable utilization rate of renewable energy, the system's reasonable utilization rate will decrease rapidly with the increase in renewable energy penetration, and when approaching the extreme value of renewable energy penetration achievable by the system, the utilization rate of renewable energy drops to near zero. Corresponding to the optimal system cost under each scenario, when the system cost reaches its optimum, the system penetration rates are 49%, 51%, and 53%, respectively, and the reasonable utilization rates of renewable energy for scenarios I through III are 81.5%, 83.1%, and 83.8%, respectively. Therefore, when the system penetration rate is low, increasing the utilization rate of renewable energy will help reduce the overall system cost and improve the efficiency of renewable energy in the system. However, when the system penetration rate is high, the high utilization rate of renewable energy will reduce the efficiency of renewable energy in the system and increase the system cost of renewable energy. Appropriately reducing the utilization rate of renewable energy and implementing reasonable wind and solar curtailment to maintain renewable energy at a reasonable utilization rate will help improve the efficiency of renewable energy in the system and reduce the overall system cost.

[0142] The reasonable utilization rate curves for different types of renewable energy in scenarios I to III are as follows: Figure 9 As shown, readily controllable and adjustable renewable energy sources such as hydropower serve as a support for system flexibility adjustment. After approaching 100% utilization, they will maintain a high utilization rate. However, renewable energy sources with randomness and volatility, such as wind and solar power, are the main cause of increased system costs. Their penetration rate-rational utilization rate curves are highly consistent with the overall renewable energy penetration rate-rational utilization rate curve. Under high renewable energy penetration rates, it is necessary to manage the generation of volatile renewable energy sources such as wind and solar power, and appropriately implement reasonable curtailment of volatile renewable energy to improve the efficiency of volatile renewable energy in the system, increase its effectiveness, and reduce system costs. For controllable and adjustable renewable energy, its flexibility adjustment role should be maximized to reduce system costs and promote the increase of renewable energy penetration.

[0143] Furthermore, through the above scenario comparisons, it is evident that determining the reasonable utilization rate is only meaningful when the penetration rate of renewable energy in the power grid is relatively high. When the penetration rate is low, the system cost of absorbing renewable energy is far lower than the cost of curtailment, in which case the power grid should be modified to fully absorb renewable energy. Generally, when the wind power penetration rate exceeds 35%, or the photovoltaic penetration rate exceeds 30%, the cost of renewable energy absorption is greater than the cost of curtailment, and only then is discussing the reasonable utilization rate of renewable energy meaningful. Of course, this data is not fixed. In different scenarios, the system has different grid structures and different initial power supply structures, and the cost of acquiring renewable energy is not necessarily the same. Therefore, the assessment of the reasonable utilization rate of renewable energy will inevitably show different results and lead to different conclusions.

[0144] For another HRP-38 simulation system, simulations of the HRP-38 system were conducted with initial non-hydro renewable energy installed capacity ratios of 30.89% and 47.2%, respectively. The initial power supply ratio configurations of the system under the two different scenarios are shown in the table below.

[0145] Table 2. Initial Installation Percentage of HRP-38 Power Supplies in Different Scenarios

[0146]

[0147] The curves showing the relationship between system cost components and penetration rate for the HRP-38 system under two different initial installations are as follows: Figure 10 As shown, with 47.2% non-hydro renewable energy installed capacity, the optimal system cost is 55,076.65 million yuan, corresponding to a renewable energy penetration rate of 53%. As the system's renewable energy penetration rate continues to increase, the optimal system cost will rise more rapidly. With a fixed system power capacity, systems with a relatively low proportion of non-hydro renewable energy installed capacity have relatively abundant adjustable resources such as thermal power and hydropower. As wind and solar power installed capacity continues to rise, the system's renewable energy penetration rate continues to increase, and the additional system cost caused by the absorption of renewable energy accelerates. However, relatively speaking, systems with abundant thermal and hydropower resources experience a slower increase in system cost.

[0148] The HRP-38 system has different system costs and energy penetration rate-optimal utilization rate curves under two different initial installation conditions, as shown in the figure. Figure 11 As shown. Although the period of highest reasonable utilization rate of renewable energy corresponds to a renewable energy penetration rate between 40% and 48%, and in Figure 11The system achieves a peak utilization rate of 93.46% at a penetration rate of 48%. However, corresponding to the optimal system cost, at a penetration rate of 53%, the utilization rate of renewable energy in the system is only 89.04%. At this point, the utilization rate of photovoltaic power is 86.21%, wind power is 90.70%, and hydropower consistently maintains a high utilization rate close to 100%. Wind power, due to its lower volatility compared to photovoltaic power generation, has a smaller negative impact on the system, thus its utilization rate is consistently higher than that of photovoltaic power at the same penetration rate. In the annual electricity consumption from fluctuating renewable energy sources such as photovoltaic and wind power, attention should be paid to maintaining a certain reasonable utilization rate, avoiding excessive pursuit of high utilization rates while also avoiding excessive pressure to reduce them. Ensuring the utilization level of renewable energy, maximizing the effectiveness of fluctuating renewable energy in the system, improving the system efficiency of renewable energy, minimizing system costs, and maximizing the social value, economic benefits, and system efficiency of renewable energy are crucial.

[0149] Furthermore, the relationship between renewable energy system penetration rate and optimal system cost, as well as the relationship between system penetration rate and reasonable utilization rate of renewable energy, are applied in the power system's power balance planning. This provides reference and support for power system power planning and generation plans. The reasonable utilization rate first increases and then decreases with increasing penetration rate. This is because when the installed capacity of renewable energy in the system is sufficient, a decision based on a low penetration rate will inhibit renewable energy generation. However, if the penetration rate is to be increased, the system will increase the installed capacity of renewable energy, while the relative proportion of adjustable resources in the system will decrease, making it impossible to support a high penetration rate of renewable energy in the system. Under certain circumstances, appropriate decisions should be made based on the current grid resource status to ensure that the grid's renewable energy penetration rate and utilization rate are both at a high level in the following year, thus maintaining the healthy development of renewable energy.

[0150] Example 2

[0151] Embodiment 2 of the present invention provides a system for assessing the reasonable utilization rate of fluctuating renewable energy, comprising:

[0152] The data initialization module is configured to acquire the target power system network structure and data parameters;

[0153] The renewable energy consumption cost calculation module is configured to analyze the additional system cost composition caused by renewable energy consumption and to assess the consumption cost.

[0154] The curtailment cost calculation module is configured to evaluate the generation value of fluctuating renewable energy using a linear value curve and calculate the curtailment cost.

[0155] The environmental cost calculation module is configured to assess the impact of renewable energy consumption on the system's environmental benefits and calculate environmental costs relative to thermal power generation.

[0156] The total cost optimization solution module is configured to analyze the system operation constraints and physical constraints involved in the operation of the power system, and to construct an evaluation model for the reasonable utilization rate of renewable energy by combining the renewable energy consumption cost, curtailment loss and environmental cost.

[0157] The reasonable utilization rate output module is configured to solve, based on the target renewable energy penetration rate, the evaluation model under system operation constraints and physical constraints to obtain the fluctuating renewable energy reasonable utilization rate under the renewable energy penetration rate.

[0158] Example 3

[0159] Embodiment 3 of the present invention provides a computer-readable storage medium having a program stored thereon, which, when executed by a processor, implements the steps in the method for assessing the reasonable utilization rate of fluctuating renewable energy as described in Embodiment 1 of the present invention.

[0160] Example 4

[0161] Embodiment 4 of the present invention provides an electronic device, including a memory, a processor, and a program stored in the memory and executable on the processor. When the processor executes the program, it implements the steps in the method for assessing the reasonable utilization rate of fluctuating renewable energy as described in Embodiment 4 of the present invention.

[0162] While the specific embodiments of the present invention have been described above in conjunction with the accompanying drawings, this is not intended to limit the scope of protection of the present invention. Those skilled in the art should understand that various modifications or variations that can be made by those skilled in the art without creative effort based on the technical solutions of the present invention are still within the scope of protection of the present invention.

Claims

1. A method for assessing the rational utilization rate of fluctuating renewable energy, characterized in that, Includes the following steps: Obtain the target power system network structure and data parameters; Analyze the additional system costs caused by renewable energy consumption and assess the consumption costs; The value of generating electricity from fluctuating renewable energy sources is evaluated using a linear value curve, and the cost of curtailment is calculated. Assess the impact of renewable energy consumption on the system's environmental benefits by calculating environmental costs relative to thermal power generation. This paper analyzes the system operation constraints and physical constraints involved in the operation of the power system, and constructs an assessment model for the reasonable utilization rate of renewable energy by combining the renewable energy consumption cost, curtailment loss and environmental cost. Based on the target renewable energy penetration rate, the evaluation model is used to solve the problem under system operation constraints and physical constraints to obtain the reasonable utilization rate of fluctuating renewable energy under the target renewable energy penetration rate. The specific process of evaluating the value of generating electricity from fluctuating renewable energy sources using a linear value curve includes determining twice the average electricity generation of fluctuating renewable energy sources as the unit cost value point, treating the point of maximum load demand as the zero value point, and constructing a linear value curve for fluctuating renewable energy sources. Alternatively, when evaluating using a linear value curve, the original linear calculation method for the cost of curtailment losses can be changed to a non-linear quadratic function calculation method, and the quadratic function can be further linearized piecewise to re-evaluate the value of curtailment losses of fluctuating renewable energy. Based on the target renewable energy penetration rate, the evaluation model is used to solve the problem under system operation constraints and physical constraints. The penetration rate is set and the penetration rate calculation formula is used as a constraint and incorporated into the overall system cost optimization model corresponding to the evaluation of the reasonable utilization rate of renewable energy. The optimal system cost and the reasonable utilization rate of each renewable energy source are evaluated under the penetration rate. Iteratively set the penetration rate, solve for the optimal system cost and the reasonable utilization rate of each renewable energy source under each penetration rate, form the system penetration rate-utilization rate curve and the penetration rate-optimal system cost curve, and determine the optimal reasonable utilization rate among the reasonable utilization rates.

2. The method for assessing the reasonable utilization rate of fluctuating renewable energy as described in claim 1, characterized in that, When obtaining the target power system network structure and data parameters, it is necessary to clarify the load forecast results and the maximum power generation capacity per unit capacity of fluctuating renewable energy.

3. The method for assessing the reasonable utilization rate of fluctuating renewable energy as described in claim 1, characterized in that, The specific process of analyzing the additional system costs caused by renewable energy consumption includes analyzing configuration costs, balancing costs, and grid costs. The configuration cost is the cost of upgrading the grid for flexibility; the balancing cost is the cost of upgrading the grid for flexibility; and the grid cost is the cost of connecting all new renewable energy capacity to the grid.

4. The method for assessing the reasonable utilization rate of fluctuating renewable energy as described in claim 1, characterized in that, The constraints include power balance constraints at each node, transmission capacity constraints of the lines, power flow calculation constraints of the lines, and generating capacity constraints of the generating units.

5. The method for assessing the reasonable utilization rate of fluctuating renewable energy as described in claim 1, characterized in that, The specific process of constructing a renewable energy rational utilization rate assessment model by combining renewable energy consumption costs, curtailment losses and environmental costs includes constructing a mathematical model for assessing the rational utilization rate of renewable energy with the objective function of optimizing the total cost composed of renewable energy consumption costs, curtailment costs and environmental costs.

6. A system for assessing the rational utilization rate of fluctuating renewable energy, using the method described in any one of claims 1-5, characterized in that, include: The data initialization module is configured to acquire the target power system network structure and data parameters; The renewable energy consumption cost calculation module is configured to analyze the additional system cost composition caused by renewable energy consumption and to assess the consumption cost. The curtailment cost calculation module is configured to evaluate the generation value of fluctuating renewable energy using a linear value curve and calculate the curtailment cost. The environmental cost calculation module is configured to assess the impact of renewable energy consumption on the system's environmental benefits and calculate environmental costs relative to thermal power generation. The total cost optimization solution module is configured to analyze the system operation constraints and physical constraints involved in the operation of the power system, and to construct an evaluation model for the reasonable utilization rate of renewable energy by combining the renewable energy consumption cost, curtailment loss and environmental cost. The reasonable utilization rate output module is configured to solve, based on the target renewable energy penetration rate, the evaluation model under system operation constraints and physical constraints to obtain the fluctuating renewable energy reasonable utilization rate under the renewable energy penetration rate.

7. A computer-readable storage medium, characterized in that, It stores multiple instructions adapted for loading by the processor of a terminal device and executing the steps of the method according to any one of claims 1-5.

8. A terminal device, characterized in that, It includes a processor and a computer-readable storage medium, the processor being used to implement various instructions; the computer-readable storage medium being used to store a plurality of instructions adapted to be loaded by the processor and executed in the steps of the method of any one of claims 1-5.

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