Electricity and natural gas market clearing simulation method and system for improving flexibility

Abstract

The present invention discloses a method and system for simulating the clearing of an electricity and natural gas market for improving flexibility, and relates to the technical field of multi-energy market collaboration. The method comprises the following steps: constructing a bidding optimization model with gas turbines and power-to-gas equipment as a gas-to-electricity conversion synergist; constructing a bidding strategy model based on two-way energy interaction; designing an aggregate clearing mechanism based on the energy demand and energy price of the electricity load and natural gas load; linearizing the nonlinear equations in the aggregate clearing mechanism, and solving the aggregate clearing mechanism. The present invention bundles gas turbines and power-to-gas equipment to participate in the electrical energy market, jointly responds to flexibility demands, aggregates and clears energy and flexibility, linearizes the nonlinear equations in the natural gas network, and realizes efficient electricity and natural gas market clearing simulation.

Description

Technical Field

[0001] The present invention relates to the field of multi-energy market collaboration technology, and in particular to an electricity and natural gas market clearing simulation method and system for improving flexibility. Background Art

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

[0003] In recent years, with the large-scale integration of renewable energy, its volatility and uncertainty have created a significant flexibility shortfall in the power system. The development and maturity of integrated energy markets has provided a market-based solution to this problem. In the power-gas energy system, gas turbines (GTs) and power-to-gas (P2G) systems offer strong flexibility due to their rapid response rates. Together, they enable bidirectional energy flow between the power and gas systems. Designing bidding strategies and market regulation mechanisms for energy conversion equipment can help leverage the complementary advantages of electricity and natural gas and achieve the optimal allocation of flexible resources in the market.

[0004] As the demand for flexibility in the power system continues to increase, it is necessary to adopt market-based means to optimize the allocation of flexibility resources. However, the losses caused by actual market resource scheduling errors are difficult to recover, and there is currently a lack of available simulation tools for market clearing, which cannot provide a strong basis for the optimal allocation of actual market-based flexibility resources.

[0005] Currently, market-based approaches to regulating power system flexibility should include both market mechanism design and optimization of bidding strategies by market participants. However, existing separate bidding strategies for coupled devices are not conducive to leveraging the complementary and synergistic advantages of different devices, resulting in increased system operational risks and hindering energy efficiency. Existing energy market trading mechanisms are not conducive to the quantification and allocation of flexibility regulation resources, making it difficult to fully address system flexibility shortfalls. Existing market clearing solutions introduce a large number of binary variables (0-1 variables) or require multiple iterations, hindering efficient solutions.

[0006] Several studies have proposed market-based regulatory approaches to enhance operational flexibility. Some focus on optimizing the behavior of a single market player, while others construct joint clearing methods for the electricity and natural gas markets and employ piecewise linearization to address the nonlinear equations of the natural gas grid. These approaches propose joint operation strategies for the electricity and natural gas markets from the perspectives of bidding strategies and clearing rules, respectively, improving system operational flexibility and model accuracy. However, the modeling of coupled constraints between gas turbines and power-to-gas equipment in joint bidding remains unresolved, nor have the institutional barriers to joint clearing of flexibility regulation products and energy markets been overcome. Furthermore, the use of piecewise linearization methods, which introduce a large number of binary variables, to address the nonlinear equations in the natural gas grid results in insufficient potential for equipment synergy, limited market resource allocation efficiency, and difficulty in deriving market clearing results.

[0007] In summary, how to achieve efficient clearing simulation of the electricity and natural gas joint market based on flexibility and energy trading has become a technical problem that needs to be urgently solved by existing technologies. Summary of the Invention

[0008] In view of the shortcomings of the existing technology, the purpose of the present invention is to provide a method and system for simulating the clearing of the electricity and natural gas market for improving flexibility, construct a joint operation simulation framework for gas and electricity-to-gas equipment, propose a two-way dynamic coupling bidding strategy for gas and electricity, propose a unified clearing method for the energy market and the flexibility market, and improve the linearization method of the nonlinear constraints of the natural gas network, avoiding the introduction of binary variables, realizing the flexible operation of the system and the efficient solution of the model, and providing a strong basis for the optimal allocation of actual market-oriented flexibility resources.

[0009] In order to achieve the above object, the present invention is implemented through the following technical solutions:

[0010] A first aspect of the present invention provides a method for simulating electricity and natural gas market clearing for improving flexibility, comprising the following steps:

[0011] Obtain the operating parameters of the integrated energy system to be controlled, the operating parameters of the gas turbine and power-to-gas equipment, the power load, the natural gas load, and the predicted parameters of new energy sources, and construct a bidding optimization model using the gas turbine and power-to-gas equipment as a gas-to-electricity conversion synergy;

[0012] According to the bidding optimization model, a bidding strategy model is constructed based on the two-way energy interaction between the gas-electricity conversion cooperative and the joint operation market;

[0013] A bidding strategy model is constructed based on two-way energy interaction, and an aggregate clearing mechanism is designed according to the energy demand and energy price of electricity load and natural gas load;

[0014] The nonlinear equations in the aggregate clearing mechanism are linearized and the aggregate clearing mechanism is solved.

[0015] Furthermore, the jointly operated market includes the electricity market, the natural gas market and the flexible regulation product market.

[0016] Furthermore, in the aggregate clearing mechanism, the electricity and natural gas energy markets are cleared according to marginal prices, and the flexible adjustment products in the flexible adjustment product market are cleared according to opportunity costs.

[0017] Furthermore, the aggregate clearing mechanism needs to meet the basic constraints of the power system and the operating constraints of the natural gas system.

[0018] Furthermore, the specific steps for linearizing the nonlinear equations in the aggregate clearing mechanism are as follows:

[0019] Introducing a piecewise penalty term into the objective function of the aggregate clearing mechanism;

[0020] The monotonicity of the slope of each segment after the nonlinear equation is segmented is used to constrain the order of continuous variables so that the continuous variables can only take values ​​from left to right, thereby realizing linearization of the nonlinear equation.

[0021] A second aspect of the present invention provides an electricity and natural gas market clearing simulation system for improving flexibility, comprising:

[0022] a data acquisition module configured to acquire operating parameters of the integrated energy system to be controlled, operating parameters of the gas turbine and the power-to-gas equipment, power load, natural gas load, and new energy forecast parameters, and to construct a bidding optimization model using the gas turbine and the power-to-gas equipment as a gas-to-electricity conversion synergy;

[0023] an energy interaction model building module configured to build a bidding strategy model based on the two-way energy interaction between the gas-electricity conversion cooperative and the joint operation market according to the bidding optimization model;

[0024] The clearing mechanism design module is configured to build a bidding strategy model based on two-way energy interaction and design an aggregate clearing mechanism based on the energy demand and energy price of electricity load and natural gas load;

[0025] The solution module is configured to linearize the nonlinear equations in the aggregate clearing mechanism and solve the aggregate clearing mechanism.

[0026] Furthermore, in the energy interaction model construction module, the joint operation market includes the electricity market, the natural gas market and the flexible regulation product market.

[0027] Furthermore, in the clearing mechanism design module, the electricity and natural gas energy markets in the aggregate clearing mechanism are cleared according to marginal prices, and the flexible adjustment products in the flexible adjustment product market are cleared according to opportunity costs.

[0028] Furthermore, in the clearing mechanism design module, the aggregate clearing mechanism needs to meet the basic constraints of the power system and the operation constraints of the natural gas system.

[0029] Furthermore, the solution module is configured as follows:

[0030] Introducing a piecewise penalty term into the objective function of the aggregate clearing mechanism;

[0031] The monotonicity of the slope of each segment after the nonlinear equation is segmented is used to constrain the order of continuous variables so that the continuous variables can only take values ​​from left to right, thereby realizing linearization of the nonlinear equation.

[0032] One or more of the above technical solutions have the following beneficial effects:

[0033] This paper discloses a method and system for simulating the clearing of electricity and natural gas markets to enhance flexibility. It proposes a bidirectional, dynamic, coupled bidding strategy for gas and electricity, enabling gas turbines and power-to-gas equipment to participate in the electricity-gas energy market and jointly respond to flexibility demands. With the goal of maximizing the benefits of collaborative bidding, the system considers the coupling constraints and operational constraints of the two types of equipment to optimize bidding decisions.

[0034] The energy and flexibility aggregation clearing mechanism proposed in the electricity-gas energy market by the present invention is priced according to the node marginal price in the energy market and according to the opportunity cost in the FRP market, thereby achieving the clearing of the energy market and the efficient allocation of flexible adjustment resources.

[0035] The present invention proposes a linearization method for the Weymouth equation without introducing binary variables, introduces a piecewise penalty term in the objective function, and utilizes the monotonicity of the slope of each segment after the Weymouth equation is segmented to constrain the order of continuous variables, so that continuous variables can only take values ​​from left to right, taking into account both the solution accuracy and solution efficiency of the model.

[0036] The present invention performs clearing simulation by constructing a joint operation simulation framework of gas and power-to-gas equipment, providing a strong basis for the optimal allocation of actual market-oriented flexibility resources and reducing losses caused by the actual energy scheduling process in the market.

[0037] Advantages of additional aspects of the present invention will be given in part in the following description and in part will be obvious from the following description, or will be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] The accompanying drawings, which constitute a part of the present invention, are used to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute improper limitations on the present invention.

[0039] Figure 1 This is a flow chart of a method for simulating electricity and natural gas market clearing for flexibility improvement in the first embodiment of the present invention;

[0040] Figure 2 Schematic diagram of the improved piecewise linearization in embodiment 1 of the present invention. DETAILED DESCRIPTION

[0041] It should be noted that the following detailed descriptions are exemplary and intended to provide further explanation of the present invention. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which the present invention belongs.

[0042] It should be noted that the terms used herein are only for describing specific embodiments and are not intended to limit the exemplary embodiments according to the present invention. As used herein, unless the context clearly indicates otherwise, the singular form is intended to include the plural form. In addition, it should be understood that when the terms "comprise" and / or "include" are used in this specification, they indicate the presence of features, steps, operations, devices, components and / or their combinations;

[0043] Explanation of terms:

[0044] Flexibility: Flexibility generally refers to the ability of a system to cope with source-load uncertainty fluctuations. In this invention, it refers to the ability of the electricity-natural gas system to cope with source-load uncertainty fluctuations (such as random fluctuations of renewable energy and random disturbances of power load).

[0045] Gas-electricity bidirectional dynamic coupling bidding strategy: refers to the optimization method for the joint bidding of gas turbines (gas-to-electricity) and power-to-gas equipment (power-to-gas) in the electricity / natural gas market. By linking the output of both parties through the energy conversion constraints between the two, it achieves two-way support for multi-energy market coordination and system flexibility.

[0046] Gas-to-electricity conversion complex: A complex consisting of a gas turbine and power-to-gas equipment that operates in a joint bidding manner and can achieve two-way flow of energy.

[0047] Flexible Regulation Product (FRP): Flexible regulation refers to the ability of controllable resources to adjust within a given response time. FRP is an ancillary service market product used to meet changes in net power load in scheduling and market clearing.

[0048] Market joint clearing mechanism considering energy and flexibility: Under the unified market framework, electricity and natural gas energy transactions and flexibility resources are optimized simultaneously to achieve the most economically optimal multi-energy market joint clearing and flexibility service allocation.

[0049] Opportunity cost: The benefits lost when a gas-to-electricity consortium fails to provide electricity due to providing flexible regulation products.

[0050] Operation cost: the loss of benefits caused during the operation of the gas-electricity conversion complex.

[0051] Example 1:

[0052] The first embodiment of the present invention provides a method for simulating the clearing of electricity and natural gas markets for improving flexibility. Figure 1 As shown in the figure, the gas-to-electricity conversion complex composed of gas turbines and power-to-gas equipment provides the electricity bid price, bid electricity volume, natural gas bid price and bid natural gas price to the joint operation market. The electricity load and natural gas load provide energy demand and energy price to the joint operation market. The joint operation market constructs an energy and flexibility aggregation clearing mechanism based on the interactive relationship between the electricity market, natural gas market and FRP market, and clears the electricity price, winning bid electricity volume, natural gas price, winning bid natural gas volume, node FRP price and each unit FRP power to the complex.

[0053] The specific steps include:

[0054] Step 1: Obtain the operating parameters of the integrated energy system to be controlled, the operating parameters of the gas turbine and power-to-gas equipment, the power load, the natural gas load, and the predicted parameters of new energy sources. A bidding optimization model is constructed, treating the gas turbine and power-to-gas equipment as a gas-to-electricity conversion synergy.

[0055] Step 2: Based on the bidding optimization model and the two-way energy interaction between the gas-to-electricity conversion complex and the joint operation market, a bidding strategy model is constructed with the goal of maximizing the bidding benefits of the gas-to-electricity conversion complex. The joint operation market includes the electricity market, the natural gas market, and the flexible regulation product market.

[0056] The bidirectional flow of energy is a prominent feature of the electricity-gas energy system. As important energy conversion equipment in the electricity-natural gas energy system, gas turbines and power-to-gas equipment have the characteristics of rapid start and stop and a wide adjustment range, which can quickly respond to the flexibility shortage of the power system. The collaboration between the two can enhance the flexible adjustment capability of the system. The traditional energy market clearing method only considers the separate bidding of the two, which is not conducive to improving the flexibility of bidding and the benefits of both. Therefore, this embodiment proposes a gas-electric bidirectional dynamic coupling bidding strategy, which bundles gas turbines and power-to-gas equipment to participate in the electricity-gas energy market and jointly respond to flexibility needs. With the goal of maximizing the benefits of the coordinated bidding of the two, the coupling constraints and equipment operation constraints of the two types of equipment are considered to make bidding optimization decisions.

[0057] In a specific embodiment, the mathematical expression of the bidding strategy model objective function is:

[0058] (1).

[0059] Where: is the number of gas-to-electricity conversion synergies, is the number of bidding periods the day before, For the A collaborative body, For the The bidding period before the day For the collaborative The number of gas turbines, For the collaborative The number of power-to-gas equipment, m is the mth gas turbine, n is the nth power-to-gas equipment; is the grid node clearing price of cooperative entity i in period t, is the natural gas system node clearing price of cooperative entity i in period t, is the settlement price of the upward flexibility product of cooperative entity i in period t, is the settlement price of the downside flexibility product of consortium i in period t; is the electricity sold by cooperative i in period t, is the gas volume sold by cooperative i in period t; and are the settlement capacities of upstream and downstream flexibility products of consortium i in period t respectively; For gas turbines The operating cost; Power-to-gas equipment operating cost.

[0060] The electricity and natural gas sold by the cooperative meet the following constraints. Equation (2) indicates that the electricity traded by the cooperative in the market is equal to the difference between the gas turbine and the power-to-gas equipment. Formula (3) indicates that the cooperative can calculate the amount of natural gas sold by the electricity sold and the gas-to-electricity conversion efficiency:

[0061] (2),

[0062] (3).

[0063] Where: and are the winning bid electricity of gas turbine m and power-to-gas equipment n in cooperative entity i during period t; is the natural gas volume won by cooperative entity i in period t; and are the gas-to-electricity conversion efficiencies of the gas turbine m and the power-to-gas equipment n in the coordinated entity i, respectively.

[0064] The upstream and downstream flexibility capacity sold by the cooperative is provided by the gas turbine and the power-to-gas equipment. The collaboration between the two can meet the system flexibility shortage while reducing the operating cost. The flexibility capacity constraints and equipment constraints of the gas turbine and the power-to-gas equipment are shown in Equations (4)-(11). The required flexibility capacity of the system is provided by the gas turbine and the power-to-gas equipment:

[0065] (4),

[0066] (5).

[0067] Where: and are the upstream and downstream flexibility product settlement capacities of gas turbine m of cooperative entity i in period t; and are the upstream and downstream flexibility product settlement capacities of the power-to-gas equipment n of cooperative entity i in period t;

[0068] The operation of gas turbines and power-to-gas equipment must meet the upper and lower output constraints (6)-(9) and the maximum ramp power constraints (10)-(13):

[0069] (6),

[0070] (7),

[0071] (8),

[0072] (9),

[0073] (10),

[0074] (11),

[0075] (12),

[0076] (13).

[0077] Where: and are the upper and lower limits of gas turbine output respectively; and are the upper and lower limits of the P2G unit output respectively; and are the maximum values ​​of the upward and downward climbing rates of the power-to-gas equipment, respectively; and are the maximum values ​​of the gas turbine ramp-up and ramp-down rates, respectively.

[0078] The above equations (1)-(13) constitute the bidding strategy model for the gas-to-electricity conversion coordination entity. This model aims to maximize the total benefits of the coordination entity's energy sales and flexibility capacity, taking into account equipment operation constraints, energy coupling constraints, and flexibility constraints to maximize the coordination entity's interests. Compared to strategies where gas turbines and power-to-gas equipment participate in bidding separately, the bidding strategy model for the gas-to-electricity conversion coordination entity in this embodiment can reflect the bidirectional conversion of system energy, fully tap the synergistic potential between energy conversion equipment, and enable the coordination entity to obtain more energy sales benefits. Compared to bidding strategies that simply consider maximizing energy sales benefits, this embodiment considers the settlement benefits of flexibility products, helping to balance the flexible operation of the system and the economic operation of the equipment, thereby solving the problem of insufficient flexible regulation capabilities of the power system.

[0079] Step 3: Construct a bidding strategy model based on two-way energy interaction, and design an aggregate clearing mechanism based on the energy demand and energy price of electricity load and natural gas load with the goal of maximizing market operation benefits.

[0080] The uncertain fluctuations in net power load have brought a high flexibility deficit to the power system. Traditional market mechanisms and auxiliary services are difficult to fully compensate for this deficit, which limits the efficient allocation of flexible resources in the integrated energy system. Flexible regulation products (FRPs) have been used in the power market as a market-based means to enhance flexibility. However, the mechanism barriers for the integrated clearing of energy and flexibility resources have not yet been broken through, and the clearing mechanism and application prospects of flexibility resources in the integrated energy market have yet to be explored. Therefore, this embodiment proposes an energy and flexibility aggregation clearing mechanism in the electricity-gas energy market, pricing according to the node marginal price in the energy market and pricing according to the opportunity cost in the FRP market, thereby achieving the clearing of the energy market and the efficient allocation of flexible regulation resources.

[0081] In a specific implementation, this embodiment proposes an aggregated clearing mechanism for the energy and flexibility markets, with the goal of maximizing market operating efficiency. The objective function formula is:

[0082] (14).

[0083] Where: is the number of power loads, The amount of natural gas load, is the electricity bidding price of power node j in period t, is the natural gas bidding price of the natural gas node g in period t; is the power load of power node j in period t, is the natural gas load of node g in the natural gas system during period t; is the electricity bidding price of cooperative i in period t, is the natural gas bidding price of cooperative entity i in period t; is the upward flexibility bid price of cooperative i in period t, is the downward flexibility bid price of cooperative entity i in period t.

[0084] In the aggregate clearing mechanism, the electricity and natural gas energy markets are cleared according to marginal prices, while for flexible adjustment products, market entities do not need to quote them, and flexible adjustment products are cleared according to opportunity costs.

[0085] The aggregate clearing mechanism needs to meet the basic constraints of the power system and the operating constraints of the natural gas system.

[0086] The basic constraints of the power system in the clearing model are shown in Equations (15)-(20), including power balance constraint (15), DC power flow equation (16), flexibility supply and demand constraints (17)-(18), line power flow constraint (19), wind power output upper and lower limit constraints (20) and node phase angle constraint (21):

[0087] (15),

[0088] (16),

[0089] (17),

[0090] (18),

[0091] (19),

[0092] (20),

[0093] (twenty one).

[0094] Where: e represents the power system node e, is the transmitted active power of power line l in period t; is the conductance of the power line l; Forecast output of wind power wf in period t; is the phase angle of the power line node l, is the phase angle of the last node of power line l; is the upward flexibility demand of the power system in period t; is the downstream flexibility demand of the power system in period t; and are the upper and lower limits of the transmission power of line l in period t; and The upper and lower limits of wind power wf output in period t; is the phase angle of node e in the power system during period t;

[0095] The flexibility requirement on the right side of constraints (17)-(18) is calculated as follows:

[0096] (twenty two),

[0097] (twenty three).

[0098] Where: For power load t Upward flexibility requirements for time periods, For power load t Downward flexibility requirements for time periods, For power load j exist t The forecast value for the time period.

[0099] (twenty four),

[0100] (25).

[0101] Where: wind represents the set of wind power nodes, For wind power t Upward flexibility requirements for time periods, For wind power t Downward flexibility requirements during the time period. For wind power wf t The forecast value for the time period.

[0102] (26),

[0103] (27).

[0104] The operating constraints of the natural gas system are shown in Equations (28)-(31), including (28) node flow balance constraints, (29) Weymouth equation, (30) pipeline average flow expression, and (31) pipeline flow upper and lower limit constraints.

[0105] (28),

[0106] (29),

[0107] (30),

[0108] (31).

[0109] Where: g represents the natural gas system node g, is the gas flow transmitted by the natural gas pipeline gl during period t; Indicates that g is the source node of pipeline gl, Indicates that g is the destination node of pipeline gl; and are the flow rates at the inlet and outlet of pipeline gl during period t; and are the pressures at the beginning and end of the pipeline gl during period t; is the pipeline constant, which is related to factors such as pipeline length, cross-sectional area and temperature; is the gas flow of natural gas source w in period t; is the gas load flow of the natural gas system node g in period t; and They are the upper and lower limits of the gl flow rate of the natural gas pipeline respectively.

[0110] Therefore, Equations (14)-(31) form a joint market clearing mechanism that considers both energy and flexibility. This mechanism aims to maximize market operational benefits, considers basic system operational constraints, and achieves aggregate clearing of electricity, natural gas, and flexible regulation products. Compared to traditional energy market clearing, the joint market clearing mechanism of this embodiment helps fully exploit the flexibility resources of the natural gas system, reduces reliance on traditional backup power resources such as thermal power and hydropower, and improves system operational flexibility.

[0111] Step 4: Linearize the nonlinear equations in the aggregate clearing mechanism and solve the aggregate clearing mechanism.

[0112] The Weymouth equation in the natural gas system equation is a nonlinear equation. In order to simplify the solution, it is necessary to linearize it. Traditional piecewise linearization methods require the introduction of a large number of binary variables, which increases the difficulty of solving the model and limits the solution rate. Therefore, this embodiment proposes a Weymouth equation linearization method that does not introduce binary variables. By introducing a piecewise penalty term in the objective function of the aggregate clearing mechanism, the monotonicity of the slope of each segment after the Weymouth nonlinear equation is segmented is used to constrain the order of continuous variables. This allows continuous variables to only take values ​​from left to right, thereby achieving linearization of the nonlinear equation and taking into account both the solution accuracy and solution efficiency of the model.

[0113] In a specific embodiment, the Weymouth equation in the natural gas system operation constraint is a nonlinear equation, that is, equation (29), first introducing two variables and Acts as an intermediate variable to replace the square term and , preprocess it:

[0114] (32),

[0115] (33).

[0116] Thus the Weymouth equation can be transformed into

[0117] (34).

[0118] In the formula, the symbolic function on the right side of the equation can be simplified using the implies statement in MATLAB, which solves the problem of difficulty in solving the function on the right side of the equation. However, the left side of the equation is still nonlinear, so the function on the left side of the equation needs to be linearized, that is, Linearization, its function graph is as shown in the attached Figure 2 As shown. For the pipeline gl in period t, let the number of segments be N, and the continuous variable of the rth segment be , the linearization constraints of the pipeline gl in period t are as follows:

[0119] (35),

[0120] (36),

[0121] (37),

[0122] (38),

[0123] (39),

[0124] (40),

[0125] (41).

[0126] Where: is the slope of the rth segment, is the function value at the segmentation point r, is the length of the rth segment. Equations (35) and (36) are the calculation formulas for the horizontal and vertical coordinates of the segment points, Equations (37) and (38) are the calculation formulas for the slopes of each segment, Equations (39) and (40) are the expressions of the linearized function values, and Equation (41) is the constraint on the continuous variable values ​​of each segment.

[0127] Formulas (29)-(33) are piecewise linearization processes, Figure 2 It can be seen that arrive The slope is monotonically increasing. In order to ensure that the continuous variables in each segment are taken from left to right, that is, the continuous variables on the left side can only have values ​​after the continuous variables on the left side reach the upper limit, a segmented penalty term is introduced in the objective function of the clearing model. , It is a penalty factor, which needs to be adjusted according to the solution situation. is the number of gas network pipelines. This ensures the order of values ​​of continuous variables, and the improved objective function (42) is expressed as:

[0128] (42).

[0129] Therefore, Equations (32)-(33), (35)-(42) realize the piecewise linearization process without introducing binary variables. If the traditional piecewise linearization method is used, in addition to introducing continuous variables In addition, binary variables need to be introduced , compared with the method proposed in this embodiment, each pipeline will introduce more The binary variables will also make the model become a mixed integer programming model, which greatly increases the difficulty of solving. The mathematical characteristic that the segmented slope increases with the horizontal axis avoids the introduction of binary variables and has great advantages in improving the efficiency of solving power and natural gas system optimization problems.

[0130] In order to prove the rationality of this method, the monotonicity of the slope is proved. , then the function is a convex function, then:

[0131] (43).

[0132] Then the function The slope of the equation increases monotonically, thus verifying the rationality of the method of this embodiment. The model of the present invention is a two-layer optimization model. When solving, the Weymouth equation is first linearized. Then, the lower-layer energy and flexibility aggregate clearing model is transformed into the Kuhn-Tucker condition (KKT). This is solved jointly with the upper-layer gas-electricity bidirectional dynamic coupling bidding strategy model to obtain the bidding results and market clearing results for gas turbines and power-to-gas equipment. The method for solving the two-layer optimization model is relatively mature and does not constitute the innovation of the present invention, so it will not be repeated here.

[0133] Example 2:

[0134] A second embodiment of the present invention provides an electricity and natural gas market clearing simulation system for improving flexibility, including:

[0135] A data acquisition module is configured to obtain operating parameters of the integrated energy system to be controlled, operating parameters of the gas turbine and the power-to-gas equipment, power load, natural gas load, and new energy forecast parameters, and to construct a bidding optimization model using the gas turbine and the power-to-gas equipment as a gas-to-electricity conversion synergy;

[0136] an energy interaction model building module configured to build a bidding strategy model based on the two-way energy interaction between the gas-electricity conversion cooperative and the joint operation market according to the bidding optimization model;

[0137] In the energy interaction model construction module, the joint operation market includes the electricity market, natural gas market and flexible regulation product market.

[0138] The clearing mechanism design module is configured to build a bidding strategy model based on two-way energy interaction and design an aggregate clearing mechanism based on the energy demand and energy price of electricity load and natural gas load;

[0139] In the clearing mechanism design module, the aggregate clearing mechanism clears the electricity and natural gas energy markets based on marginal prices, while the flexible adjustment products in the flexible adjustment product market are cleared based on opportunity costs. The aggregate clearing mechanism must meet the basic constraints of the power system and the operational constraints of the natural gas system.

[0140] The solution module is configured to linearize the nonlinear equations in the aggregate clearing mechanism and solve the aggregate clearing mechanism.

[0141] The solution module is also configured to: introduce a piecewise penalty term into the objective function of the aggregate clearing mechanism; use the monotonicity of the slope of each segment after the nonlinear equation is segmented to constrain the order of values ​​of continuous variables, so that continuous variables can only take values ​​from left to right, thereby realizing linear processing of nonlinear equations.

[0142] The steps involved in the above embodiment 2 correspond to those in the method embodiment 1. For the specific implementation method, please refer to the relevant description part of the embodiment 1.

[0143] Those skilled in the art will appreciate that the modules or steps of the present invention described above can be implemented using a general-purpose computer device. Alternatively, they can be implemented using program code executable by a computing device, which can then be stored in a storage device and executed by the computing device. Alternatively, they can be fabricated into separate integrated circuit modules, or multiple modules or steps can be fabricated into a single integrated circuit module for implementation. The present invention is not limited to any specific combination of hardware and software.

[0144] Although the above describes the specific embodiments of the present invention in conjunction with the accompanying drawings, it 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 on the basis of the technical solution of the present invention without any creative work are still within the scope of protection of the present invention.

Claims

1. A method for simulating the clearing of electricity and natural gas markets for improving flexibility, characterized by: The following steps are involved: Obtain the operating parameters of the integrated energy system to be controlled, the operating parameters of the gas turbine and power-to-gas equipment, the power load, the natural gas load, and the predicted parameters of new energy sources, and construct a bidding optimization model using the gas turbine and power-to-gas equipment as a gas-to-electricity conversion synergy; According to the bidding optimization model, a bidding strategy model is constructed based on the two-way energy interaction between the gas-electricity conversion cooperative and the joint operation market; A bidding strategy model is constructed based on two-way energy interaction, and an aggregate clearing mechanism is designed based on the energy demand and energy price of electricity load and natural gas load; Linearize the nonlinear equations in the aggregate clearing mechanism and solve the aggregate clearing mechanism; The specific steps for linearizing the nonlinear equations in the aggregate clearing mechanism are: Introducing a piecewise penalty term into the objective function of the aggregate clearing mechanism; The monotonicity of the slope of each segment after the nonlinear equation is segmented is used to constrain the order of continuous variables so that the continuous variables can only take values ​​from left to right, thus realizing the linearization of the nonlinear equation. The joint operation market includes the electricity market, natural gas market and flexible regulation product market; The objective function of the bidding strategy model is: Where, is the number of gas-to-electricity conversion synergies, is the number of bidding periods the day before, For the A collaborative body, For the The bidding period before the day For the collaborative The number of gas turbines, For the collaborative The number of power-to-gas equipment, m is the mth gas turbine, n is the nth power-to-gas equipment; is the grid node clearing price of cooperative entity i in period t, is the natural gas system node clearing price of cooperative entity i in period t, is the settlement price of the upward flexibility product of cooperative entity i in period t, is the settlement price of the downside flexibility product of consortium i in period t; is the electricity sold by cooperative i in period t, is the gas volume sold by cooperative i in period t; and are the settlement capacities of upstream and downstream flexibility products of consortium i in period t respectively; For gas turbines The operating cost; Power-to-gas equipment The operating cost; The bidding strategy model of the gas-to-electricity conversion complex takes into account equipment operation constraints, energy coupling constraints, and flexibility constraints; The objective function of the aggregate clearing mechanism is: Where, is the number of power loads, The amount of natural gas load, is the electricity bidding price of power node j in period t, is the natural gas bidding price of the natural gas node g in period t; is the power load of power node j in period t, is the natural gas load of node g in the natural gas system during period t; is the electricity bidding price of cooperative i in period t, is the natural gas bidding price of cooperative entity i in period t; is the upward flexibility bid price of cooperative i in period t, is the downward flexibility bid price of cooperative entity i in period t; The aggregate clearing mechanism needs to meet the basic constraints of the power system and the operating constraints of the natural gas system; Segment penalty terms: ; in, is the penalty factor, is the number of gas network pipelines; ; is the gas flow transmitted by the natural gas pipeline gl during period t.

2. The method for simulating electricity and natural gas market clearing for flexibility improvement according to claim 1, characterized in that: In the aggregate clearing mechanism, the electricity and natural gas energy markets are cleared according to marginal prices, and the flexible adjustment products in the flexible adjustment product market are cleared according to opportunity costs.

3. A power and natural gas market clearing simulation system for improving flexibility, characterized by: include: A data acquisition module is configured to obtain operating parameters of the integrated energy system to be controlled, operating parameters of the gas turbine and the power-to-gas equipment, power load, natural gas load, and new energy forecast parameters, and to construct a bidding optimization model using the gas turbine and the power-to-gas equipment as a gas-to-electricity conversion synergy; an energy interaction model building module configured to build a bidding strategy model based on the two-way energy interaction between the gas-electricity conversion cooperative and the joint operation market according to the bidding optimization model; The clearing mechanism design module is configured to build a bidding strategy model based on two-way energy interaction and design an aggregate clearing mechanism based on the energy demand and energy price of electricity load and natural gas load; a solving module configured to linearize the nonlinear equations in the aggregate clearing mechanism and solve the aggregate clearing mechanism; The solver module is also configured to: Introducing a piecewise penalty term into the objective function of the aggregate clearing mechanism; The monotonicity of the slope of each segment after the nonlinear equation is segmented is used to constrain the order of continuous variables so that the continuous variables can only take values ​​from left to right, thus realizing the linearization of the nonlinear equation. In the energy interaction model construction module, the joint operation market includes the electricity market, natural gas market and flexible regulation product market; The objective function of the bidding strategy model is: Where, is the number of gas-to-electricity conversion synergies, is the number of bidding periods the day before, For the A collaborative body, For the The bidding period before the day For the collaborative The number of gas turbines, For the collaborative The number of power-to-gas equipment, m is the mth gas turbine, n is the nth power-to-gas equipment; is the grid node clearing price of cooperative entity i in period t, is the natural gas system node clearing price of cooperative entity i in period t, is the settlement price of the upward flexibility product of cooperative entity i in period t, is the settlement price of the downside flexibility product of consortium i in period t; is the electricity sold by cooperative i in period t, is the gas volume sold by cooperative i in period t; and are the settlement capacities of upstream and downstream flexibility products of consortium i in period t respectively; For gas turbines The operating cost; Power-to-gas equipment The operating cost; The bidding strategy model of the gas-to-electricity conversion complex takes into account equipment operation constraints, energy coupling constraints, and flexibility constraints; The objective function of the aggregate clearing mechanism is: Where, is the number of power loads, The amount of natural gas load, is the electricity bidding price of power node j in period t, is the natural gas bidding price of the natural gas node g in period t; is the power load of power node j in period t, is the natural gas load of node g in the natural gas system during period t; is the electricity bidding price of cooperative i in period t, is the natural gas bidding price of cooperative entity i in period t; is the upward flexibility bid price of cooperative i in period t, is the downward flexibility bid price of cooperative entity i in period t; In the clearing mechanism design module, the aggregate clearing mechanism needs to meet the basic constraints of the power system and the operation constraints of the natural gas system; Segment penalty terms: ; in, is the penalty factor, is the number of gas network pipelines; ; is the gas flow transmitted by the natural gas pipeline gl during period t.

4. The power and natural gas market clearing simulation system for improving flexibility according to claim 3, characterized in that: In the clearing mechanism design module, the electricity and natural gas energy markets in the aggregate clearing mechanism are cleared according to marginal prices, and the flexible adjustment products in the flexible adjustment product market are cleared according to opportunity costs.

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