Optimal scheduling method and system considering the flexibility of heat and power integrated energy system

Abstract

The present invention relates to an optimization scheduling method considering the flexibility of a heat-electricity coordinated integrated energy system, comprising the following steps: step S1: based on a heat-electricity coordinated integrated energy system model, construct a power system model, a thermal system model considering the heat storage characteristics of a heating network, and further establish a heat network flexibility evaluation model based on a generalized equivalent thermal energy storage model; step S2: based on the model constructed in step S1, and considering the thermal constraints of the heat-electricity coordinated integrated energy system with operational flexibility, construct an optimization scheduling model based on the flexibility of the heat-electricity coordinated integrated energy system; step S3: based on the optimization scheduling model considering the flexibility of the heat-electricity coordinated integrated energy system, and taking the lowest operating cost of the heat-electricity coordinated integrated energy system as the goal, obtain an actual optimization scheduling plan for the heat-electricity coordinated integrated energy system, and realize reasonable scheduling of the heat-electricity coordinated integrated energy system. The present invention can effectively save system operating costs and improve operating efficiency, and can promote the consumption of renewable energy.

Description

Technical Field

[0001] The present invention relates to the field of optimized scheduling of integrated energy systems, and in particular to an optimized scheduling method and system that considers the flexibility of a heat-electricity coordinated integrated energy system. Background Art

[0002] Energy is the foundation of human survival and development and the lifeblood of the national economy. In recent years, as the demand for energy has increased dramatically and fossil energy is non-renewable, how to ensure a continuous, safe and reliable supply of energy has become a hot topic of social concern. The Integrated Energy System (IES) has changed the traditional model of each energy supply and use system operating and planning independently, and has coordinated and optimized the energy supply and use links of electricity, gas and heat, significantly improving the system's energy supply and use efficiency and reliability.

[0003] Energy is the foundation of human survival and development and the lifeblood of the national economy. In recent years, as the demand for energy has increased dramatically and fossil energy is non-renewable, how to ensure a continuous, safe and reliable supply of energy has become a hot topic of social concern. The Integrated Energy System (IES) has changed the traditional model of each energy supply and use system operating and planning independently, and has coordinated and optimized the energy supply and use links of electricity, gas and heat, significantly improving the system's energy supply and use efficiency and reliability. Summary of the invention

[0004] In view of this, the purpose of the present invention is to provide an optimization scheduling method and system that takes into account the flexibility of a heat-power coordinated integrated energy system, which can effectively save system operating costs, improve operating efficiency, and promote the consumption of renewable energy.

[0005] To achieve the above object, the present invention adopts the following technical solution:

[0006] An optimization scheduling method considering the flexibility of a heat and power integrated energy system includes the following steps:

[0007] Step S1: Based on the heat-power synergistic integrated energy system model, a power system model and a thermal system model considering the heat storage characteristics of the heating network are constructed, and a heat network flexibility assessment model is further established based on a generalized equivalent thermal energy storage model;

[0008] Step S2: Based on the model constructed in step S1, and considering the thermal constraints of the heat-power coordinated integrated energy system with operational flexibility, an optimization scheduling model based on the flexibility of the heat-power coordinated integrated energy system is constructed;

[0009] Step S3: Based on the optimization scheduling model considering the flexibility of the heat-power coordinated integrated energy system, and with the goal of minimizing the operating cost of the heat-power coordinated integrated energy system, obtain the actual heat-power coordinated integrated energy system optimization scheduling plan to achieve reasonable scheduling of the heat-power coordinated integrated energy system.

[0010] Furthermore, the power system mathematical model is specifically: based on the composition of the power system, the power transmission network is mathematically described using the node voltage method

[0011]

[0012] Where: is the voltage at node i, is the voltage at node j, is the current flowing through node i, Y ii is called the self-admittance of node i, Y ij It is called the mutual admittance between node i and node j.

[0013] Furthermore, the thermal system model considering the heat storage characteristics of the heating network is as follows:

[0014] Based on the composition of the thermal system, the hydraulic model and thermal model of the power system were constructed respectively.

[0015] The hydraulic model means that for any node in the heating network, the sum of the flow rates from the pipes connected to the node to the node must be equal to the sum of the flow rates out of the node.

[0016] ∑q t,j =∑q t,k (2)

[0017] Where: q t,j and q t,k are the mass flow rates of the working fluid in pipelines j and k during period t, kg / s.

[0018] The thermal model consists of the thermal power equation and the node temperature mixed equation

[0019]

[0020]

[0021]

[0022] Where: and are the set of pipes connected to node n and injecting traffic into node n and the set of pipes that flow out of node n respectively; H t,i is the heat exchange between heat exchange station i and heat load during period t, kJ; m t,iis the mass of the working fluid flowing through heat exchange station i during period t, kg; and are the supply water temperature and return water temperature flowing through heat exchange station i during period t, ℃; is the heat load at heat exchange station i during period t, kW; is the outlet temperature of hot water flowing out of pipe j during period t, °C; is the outlet temperature of the hot water flowing out of pipe k during period t, °C; represents the pipe whose outlet n is connected to the node, Represents a pipe whose inlet is connected to node n.

[0023] Furthermore, the generalized equivalent thermal energy storage model is specifically:

[0024]

[0025] In the formula, is the inlet temperature of hot water in pipe p in the water supply network at time t; is the inlet temperature of hot water in pipe p in the return network at time t; is the heat input from the heat source to the heating network at time τ; is the heat output by the heating network to the heat load at time τ.

[0026] Furthermore, the heat network flexibility assessment model is established based on the generalized equivalent thermal energy storage model, as follows:

[0027] A heat network flexibility assessment model is established based on the heat storage characteristics of the heat supply network, and the operational flexibility of the thermal system is defined as the range in which the heat input power deviates from the benchmark heat input power under the system operation constraints.

[0028] First, build a heat input power model

[0029]

[0030] Where: and They refer to the maximum and minimum thermal energy storage capacity deviations, respectively; and They refer to the maximum and minimum thermal input power deviations, respectively; and Refers to the maximum and minimum thermal input power ramp rates respectively; Refers to the energy storage capacity of the heating network under baseline conditions; Refers to the heat input power under reference conditions;

[0031] Upper limit of thermal input power deviation and lower limit It can be calculated by the following formula:

[0032] Variable flow constant temperature

[0033] Constant flow variable temperature

[0034] Variable flow and variable temperature

[0035] Furthermore, the step S2 is specifically as follows:

[0036] Constructing the power constraints of the heat and power integrated energy system considering the operation flexibility;

[0037]

[0038]

[0039] Where: P in,i and P out,i represents the active power injected by the thermal system into the power system at node i and the active power output by the power system to the thermal system at node i; Q in,i and Q out,i represents the reactive power injected by the thermal system into the power system at node i and the reactive power output by the power system to the thermal system at node i; ΔP i and ΔQ i Respectively represent the deviation of active power and reactive power of node i; ε i represents the flexibility index at node i;

[0040] Construct thermal constraints of a heat-power integrated energy system taking into account operational flexibility;

[0041]

[0042]

[0043]

[0044]

[0045] In the formula, The thermal power output at node n is the thermal energy generated by the coupling of the thermal system and the power system and the internal energy storage device of the thermal system at time t; is the heat energy input from other energy systems to the thermal system at node n at time t, is the heat energy output of the thermal system at node n to other energy systems; ΔΦ n,t Indicates the thermal energy deviation of node n; δ n,t represents the flexibility index at node n;

[0046] The thermal power balance constraint considering the thermal network energy storage performance is:

[0047]

[0048] At the same time, considering that during the dispatching stage of a day, the thermal network in stable operation should be in a state of energy balance, the thermal network balance constraint should also be met:

[0049]

[0050] Furthermore, the optimization scheduling target is to minimize the operating cost of the heat and power coordinated integrated energy system, and the system operation flexibility and the operating constraints of each link in the heat and power coordinated integrated energy system are considered. Based on the MATLAB-YALMIP platform, the optimization scheduling model considering the flexibility of the heat and power coordinated integrated energy system is solved by the CPLEX solver.

[0051] Furthermore, the optimization scheduling model considering the flexibility of the heat and power coordinated integrated energy system is as follows:

[0052]

[0053] The constraints are as follows:

[0054] P t unit +P t CHP +P t WT +P t PV -P t EB =P t load (19)

[0056]

[0057]

[0058]

[0059]

[0060]

[0061]

[0062]

[0063]

[0064]

[0065]

[0066]

[0067] 0≤P t WT ≤P t WT,pre (31)

[0068] P t WT +P t WT,loss =P t WT,pre (32)

[0069] 0≤P t PV ≤P t PV,pre (33)

[0070] P t PV +P t PV,loss =P t PV,pre (34)

[0071]

[0072]

[0073]

[0074] P t,i =-B'θ t,i (38)

[0075]

[0076] P l,min <P l <P l,max (40)

[0077] Where P t unit P is the electric power generated by the thermal power generator unit during period t, kW; t CHP is the electric power generated by CHP during period t, kW; P t WT is the electric power generated by the fan during period t, kW; P t PV is the power generated by photovoltaic power in period t, kW; Pt EB P is the power consumed by the electric boiler during period t, kW; t load is the electrical load during period t, kW; is the thermal power generated by CHP during period t, kW; is the thermal power generated by the electric boiler during period t, is the heat load of the system during period t, kW; and refers to the maximum and minimum heat input power deviation respectively; ε is the CHP thermal-to-electricity ratio; η is the CHP gas-to-heat conversion efficiency; η CHP is CHP efficiency; b v The calorific value of natural gas combustion and Respectively represent the upper and lower limits of CHP output, kW; and Respectively represent the maximum upward and downward climbing rates, kW; η EB is the electricity-heat conversion efficiency of the electric boiler; and Respectively represent the upper and lower limits of EB output, kW; and Respectively represent the maximum upward and downward climbing rates, kW; P t WT,pre and P t PV,pre Respectively represent the predicted output value of wind turbine and photovoltaic power in period t, kW; P t WT,loss , P t PV,loss They represent the abandoned wind power and abandoned solar power in period t, kW; B' is the susceptance matrix of the grid branch; P t,i is the active power injected into the system by node i at time t, kW; θ t,i is the voltage phase angle of node i at time t; P l is the transmission power capacity of transmission line l, P l,min , P l,max They are respectively the lower and upper limits of the transmission power capacity of transmission line l.

[0078] An optimization scheduling system considering the flexibility of a heat-power synergistic integrated energy system includes a data acquisition and processing module for acquiring and processing temperature parameters in a water supply network;

[0079] The model building module is used to construct an optimal dispatching model that takes into account the flexibility of the heat-power coordinated integrated energy system, including constructing a power system model, a thermal system model that takes into account the heat storage characteristics of the heating pipeline network, and then establishing a heat network flexibility evaluation model based on a generalized equivalent thermal energy storage model; constructing a system operation model that takes into account the flexibility of the heat-power coordinated integrated energy system; and constructing an optimal dispatching model for the heat-power coordinated integrated energy system with the goal of minimizing the operating cost of the heat-power coordinated integrated energy system.

[0080] The evaluation module is used to obtain the flexibility evaluation index value of the heat and power coordinated integrated energy system, and to evaluate the optimal scheduling method of the heat and power coordinated integrated energy system to determine a reasonable optimal scheduling method.

[0081] Compared with the prior art, the present invention has the following beneficial effects:

[0082] The present invention can effectively utilize the flexibility of the heating pipeline network by optimizing the scheduling of the heat-power coordinated integrated energy system. On the one hand, it can improve the economy of the system and reduce the total operating cost of the system; on the other hand, it can promote the system's ability to absorb renewable energy, further reduce the amount of wind and solar power abandoned in the system, thereby improving energy utilization efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0083] Figure 1 is a flow chart of a method according to an embodiment of the present invention;

[0084] Figure 2 The heat and power synergistic integrated energy system structure of the embodiment of the present invention;

[0085] Figure 3 A schematic diagram of system load and wind and solar power forecast output according to an embodiment of the present invention;

[0086] Figure 4 This is a schematic diagram of electrical and thermal power balance in scenario 1 of an embodiment of the present invention;

[0087] Figure 5 This is a schematic diagram of electrical and thermal power balance in scenario 2 of an embodiment of the present invention;

[0088] Figure 6 A schematic diagram of flexibility evaluation according to an embodiment of the present invention;

[0089] Figure 7 This is a schematic diagram of electrical and thermal power balance in scenario 3 of an embodiment of the present invention;

[0090] Figure 8 This is a schematic diagram of electrical and thermal power balance in scenario 4 of an embodiment of the present invention;

[0091] Fig. 9 Schematic diagram of wind power abandonment in scenario 3 and scenario 4 of the embodiment of the present invention;

[0092] Fig.10 Schematic diagram of abandoned optical power in scenario 3 and scenario 4 of the embodiments of the present invention. DETAILED DESCRIPTION

[0093] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0094] Please refer to Figure 1 The present invention provides an optimization scheduling method considering the flexibility of a heat-power coordinated integrated energy system, comprising the following steps:

[0095] Step S1: Based on the heat-power synergistic integrated energy system model, a power system model and a thermal system model considering the heat storage characteristics of the heating network are constructed, and a heat network flexibility assessment model is further established based on a generalized equivalent thermal energy storage model;

[0096] Step S2: Based on the model constructed in step S1, and considering the thermal constraints of the heat-power coordinated integrated energy system with operational flexibility, an optimization scheduling model based on the flexibility of the heat-power coordinated integrated energy system is constructed;

[0097] Step S3: Based on the optimization scheduling model considering the flexibility of the heat-power coordinated integrated energy system, and with the goal of minimizing the operating cost of the heat-power coordinated integrated energy system, obtain the actual heat-power coordinated integrated energy system optimization scheduling plan to achieve reasonable scheduling of the heat-power coordinated integrated energy system.

[0098] In this embodiment, the mathematical model of the power system is specifically: based on the composition of the power system, the power transmission network is mathematically described using the node voltage method.

[0099]

[0100] Where: is the voltage at node i, is the voltage at node j, is the current flowing through node i, Y ii is called the self-admittance of node i, Y ij It is called the mutual admittance between node i and node j.

[0101] In this embodiment, the thermal system model considering the heat storage characteristics of the heating network is as follows:

[0102] Based on the composition of the thermal system, the hydraulic model and thermal model of the power system were constructed respectively.

[0103] The hydraulic model means that for any node in the heating network, the sum of the flow rates from the pipes connected to the node to the node must be equal to the sum of the flow rates out of the node.

[0104] ∑q t,j =∑qt,k (2)

[0105] Where: q t,j and q t,k are the mass flow rates of the working fluid in pipelines j and k during period t, kg / s.

[0106] The thermal model consists of the thermal power equation and the node temperature mixed equation

[0107]

[0108]

[0109]

[0110] Where: and are the set of pipes connected to node n and injecting traffic into node n and the set of pipes that flow out of node n respectively; H t,i is the heat exchange between heat exchange station i and heat load during period t, kJ; m t,i is the mass of the working fluid flowing through heat exchange station i during period t, kg; and are the supply water temperature and return water temperature flowing through heat exchange station i during period t, ℃; is the heat load at heat exchange station i during period t, kW; is the outlet temperature of hot water flowing out of pipe j during period t, °C; is the outlet temperature of the hot water flowing out of pipe k during period t, °C; represents the pipe whose outlet n is connected to the node, Represents a pipe whose inlet is connected to node n.

[0111] In this embodiment, based on the generalized equivalent thermal energy storage model, specifically:

[0112]

[0113] In the formula, is the inlet temperature of hot water in pipe p in the water supply network at time t; is the inlet temperature of hot water in pipe p in the return network at time t; is the heat input from the heat source to the heating network at time τ; is the heat output by the heating network to the heat load at time τ.

[0114] In this embodiment, a heat network flexibility assessment model is established based on a generalized equivalent thermal energy storage model, as follows:

[0115] A heat network flexibility assessment model is established based on the heat storage characteristics of the heat supply network, and the operational flexibility of the thermal system is defined as the range in which the heat input power deviates from the benchmark heat input power under the system operation constraints.

[0116] First, build a heat input power model

[0117]

[0118] Where: and They refer to the maximum and minimum thermal energy storage capacity deviations, respectively; and They refer to the maximum and minimum thermal input power deviations, respectively; and Refers to the maximum and minimum thermal input power ramp rates respectively; Refers to the energy storage capacity of the heating network under baseline conditions; Refers to the heat input power under reference conditions;

[0119] Upper limit of thermal input power deviation and lower limit It can be calculated by the following formula:

[0120] Variable flow constant temperature

[0121] Constant flow variable temperature

[0122] Variable flow and variable temperature

[0123] In this embodiment, step S2 is specifically as follows:

[0124] Constructing the power constraints of the heat and power integrated energy system considering the operation flexibility;

[0125]

[0126]

[0127] Where: P in,i and P out,i represents the active power injected by the thermal system into the power system at node i and the active power output by the power system to the thermal system at node i; Q in,i and Q out,i represents the reactive power injected by the thermal system into the power system at node i and the reactive power output by the power system to the thermal system at node i; ΔP i and ΔQ i Respectively represent the deviation of active power and reactive power of node i; ε i represents the flexibility index at node i;

[0128] Construct thermal constraints of a heat-power integrated energy system taking into account operational flexibility;

[0129]

[0130]

[0131]

[0132]

[0133] In the formula, The thermal power output at node n is the thermal energy generated by the coupling of the thermal system and the power system and the internal energy storage device of the thermal system at time t; is the heat energy input from other energy systems to the thermal system at node n at time t, is the heat energy output of the thermal system at node n to other energy systems; ΔΦ n,t Indicates the thermal energy deviation of node n; δ n,t represents the flexibility index at node n;

[0134] The thermal power balance constraint considering the thermal network energy storage performance is:

[0135]

[0136] At the same time, considering that during the dispatching stage of a day, the thermal network in stable operation should be in a state of energy balance, the thermal network balance constraint should also be met:

[0137]

[0138] In this embodiment, the optimal scheduling model considering the flexibility of the heat and power coordinated integrated energy system is as follows:

[0139]

[0140] 1. Power balance constraints

[0141] (1) Electric power balance constraints

[0142] Ignoring grid losses, the production and use of system power should be balanced in real time:

[0143] P t unit +P t CHP +P t WT +P t PV -P t EB =P tload (twenty one)

[0145] Where: P t unit P is the electric power generated by the thermal power generator unit during period t, kW; t CHP is the electric power generated by CHP during period t, kW; P t WT is the electric power generated by the fan during period t, kW; P t PV is the power generated by photovoltaic power in period t, kW; P t EB P is the power consumed by the electric boiler during period t, kW; t load is the electrical load during period t, kW.

[0146] (2) Thermal power balance constraints

[0147] Ignoring the heat network losses, the system heat output should always be equal to the heat load:

[0148]

[0149] Where: is the thermal power generated by CHP during period t, kW; is the thermal power generated by the electric boiler during period t, is the heat load of the system during period t, kW.

[0150] The thermal power balance constraints of the thermal-electric coupled IES considering the energy storage characteristics of the thermal network are (18)-(19).

[0151] (II) Energy equipment constraints

[0152] (1) CHP constraints

[0153] The constraints of CHP include heat-to-electricity ratio constraints and energy conversion constraints:

[0154]

[0155]

[0156]

[0157] Where: ε is the CHP thermal-electric ratio; η is the CHP gas-heat conversion efficiency; η CHP is CHP efficiency; b v is the calorific value of natural gas combustion.

[0158] The upper and lower limits of CHP output are:

[0159]

[0160] Where: and Respectively represent the upper and lower limits of CHP output, kW.

[0161] The ramp constraint of the output change of the CHP unit in two adjacent dispatching periods is:

[0162]

[0163] Where: and Represents the maximum upward and downward climbing rates, kW respectively.

[0164] (2) Electric boiler constraints

[0165] The operation constraints of electric boilers include the constraints of electricity-heat conversion efficiency, which is the ratio of the heating capacity of the electric boiler to the power consumption:

[0166]

[0167] Where: η EB is the electricity-heat conversion efficiency of the electric boiler.

[0168] The upper and lower limits of the electric boiler output are:

[0169]

[0170] Where: and Respectively represent the upper and lower limits of EB output, kW.

[0171] The ramp constraint of the output change of the electric boiler in two adjacent dispatching periods is:

[0172]

[0173] Where: and Represents the maximum upward and downward climbing rates, kW respectively.

[0174] (3) Renewable energy output constraints

[0175] The output of renewable energy is limited by the predicted value of renewable energy. If the system's renewable energy absorption capacity is insufficient, wind and solar power abandonment will occur. The constraints are:

[0176] 0≤P t WT ≤P t WT,pre (31)

[0178] P t WT +P t WT,loss =P t WT,pre (32)

[0180] 0≤P t PV ≤P t PV,pre (33)

[0182] P t PV +P t PV,loss =P t PV,pre (34)

[0184] Where: P t WT,pre and P t PV,pre Respectively represent the predicted output value of wind turbine and photovoltaic power in period t, kW; P t WT,loss , P t PV,loss They represent the wind power and solar power abandonment in period t, kW respectively.

[0185] (III) Heating network constraints

[0186] The heating network constraints include heat exchange constraints (3)-(4) and node temperature mixing constraints (5).

[0187] (IV) Grid constraints

[0188] In order to simplify the calculation, only the active power flow distribution in the power grid is considered, and the constraints are:

[0189] P t,i =-B'θ t,i (35)

[0191] B' ij =1 / x ij ,

[0192] Where: B' is the susceptance matrix of the power grid branch; P t,i is the active power injected into the system by node i at time t, kW; θ t,i is the voltage phase angle of node i at time t.

[0193] The capacity constraint of the transmission line is:

[0194] P l,min <P l <P l,max (37)

[0196] Where: P l is the transmission power capacity of transmission line l, P l,min , P l,max They are respectively the lower and upper limits of the transmission power capacity of transmission line l.

[0197] Based on the MATLAB-YALMIP platform, the above linear programming model is solved by the CPLEX solver.

[0198] Example:

[0199] This embodiment selects the IEEE 14-node power distribution system and the improved 32-node central heating network (see Appendix Figure 2 ), the energy equipment included in the system include thermal power generating units, cogeneration units, electric boilers, fans, and photovoltaics. Their detailed operating parameters are shown in Table 1, and the heating system pipeline parameters are shown in Table 2.

[0200] Table 1 Energy equipment operating parameters

[0201]

[0202] Table 2 Heating system pipeline parameters

[0203]

[0204]

[0205] In this embodiment, four scheduling scenarios are constructed to analyze the improvement of the operating flexibility of the heat and power coordinated integrated energy system on the system economy, renewable energy absorption capacity and other performance.

[0206] 1) Scenario 1: The flexibility provided by the thermal network energy storage is not considered. In this scenario, the thermal output of the system is equal to the thermal load. This scenario is the basic operation scenario of the thermal power coordinated integrated energy system;

[0207] 2) Scenario 2: Consider the flexibility provided by thermal network energy storage. When considering the supply and demand balance of the thermal system, the energy storage characteristics of the thermal network are taken into account. Scenario 2 is compared with Scenario 1 to analyze the impact of system operation flexibility on system economics;

[0208] 3) Scenario 3: The flexibility provided by thermal network energy storage is not considered, but a high proportion of renewable energy is connected to the system. In Scenario 3, the predicted output of wind turbines and photovoltaics is increased to 1.5 times the original, and the system begins to abandon wind and solar power;

[0209] 4) Scenario 4: Considering the flexibility provided by thermal network energy storage, and considering a high proportion of renewable energy access to the system. When considering the balance of system supply and demand, the energy storage characteristics of the thermal network are taken into account, and scenario 4 is compared with scenario 3 to analyze the impact of system operation flexibility on the system's renewable energy absorption capacity.

[0210] First, optimize the scheduling of Scenario 1 and Scenario 2, and analyze the effect of system operation flexibility on improving system economy. The total operating cost and various expenses of the system in the two scenarios are shown in the following table.

[0211] Table 3 Comparison of operating costs between scenario 1 and scenario 2

[0212]

[0213] The total cost of IES operation in scenario 2 is 4.0065 million yuan within one day, which is about 0.34% less than 4.0200 million yuan in scenario 1. Among them, the cost of thermal power generation in scenario 2 is about 7% less than that in scenario 1, and the operating cost of CHP is about 1.8% higher than that in scenario 1. The scheduling scheme of scenario 2 reduces the total operating cost of the system, among which the cost of thermal power generation has dropped significantly, while the operating cost of CHP has increased slightly. The electric power generated by the energy production equipment of the system in scenarios 1 and 2 is equal to the electric load of the system. The thermal power generated by the energy production equipment of the system in scenario 1 is equal to the thermal load of the system. In scenario 2, the heat-electricity coordinated integrated energy system that takes into account the energy storage characteristics of the heat network breaks the constraint of determining electricity by heat. The heating power of the system does not have to follow the changes in the heat load in real time, realizing the translation of thermal energy in time and space.

[0214] Optimize the scheduling of Scenario 3 and Scenario 4, and analyze the effect of system flexibility on the system's renewable energy absorption capacity. The total operating cost and various expenses of the system in the two scenarios are shown in the following table.

[0215] Table 4 Comparison of operating costs between scenario 1 and scenario 2

[0216]

[0217] In scenarios 3 and 4, the predicted output of wind turbines and photovoltaics increased to 1.5 times the original output, and wind and solar power were abandoned in both scenarios. The total operating cost of IES in scenario 4 was 3.182 million yuan within one day, which was about 4.9% less than the 3.3473 million yuan in scenario 3. Among them, the penalty fee for wind and solar power abandonment in scenario 4 was reduced by about 53.1% compared with scenario 3, greatly improving the absorption capacity of renewable energy.

[0218] The above description is only a preferred embodiment of the present invention. All equivalent changes and modifications made according to the scope of the patent application of the present invention should fall within the scope of the present invention.

Claims

1. An optimization scheduling method considering the flexibility of a heat-power integrated energy system, characterized in that: The following steps are involved: Step S1: Based on the heat-power synergistic integrated energy system model, a power system model and a thermal system model considering the heat storage characteristics of the heating network are constructed, and a heat network flexibility assessment model is established based on a generalized equivalent thermal energy storage model; Step S2: Based on the model constructed in step S1, and considering the thermal constraints of the heat-power coordinated integrated energy system with operational flexibility, an optimization scheduling model based on the flexibility of the heat-power coordinated integrated energy system is constructed; Step S3: Based on the optimization scheduling model considering the flexibility of the heat-power coordinated integrated energy system and taking the lowest operating cost of the heat-power coordinated integrated energy system as the goal, an actual heat-power coordinated integrated energy system optimization scheduling scheme is obtained to achieve reasonable scheduling of the heat-power coordinated integrated energy system; The mathematical model of the power system is specifically: based on the composition of the power system, the power transmission network is mathematically described using the node voltage method. Where: is the voltage at node i, is the voltage at node j, is the current flowing through node i, Y ii is called the self-admittance of node i, Y ij It is called the mutual admittance between nodes i and j; The thermal system model considering the heat storage characteristics of the heating network is as follows: Based on the composition of the thermal system, the hydraulic model and thermal model of the power system were constructed respectively. The hydraulic model means that for any node in the heating network, the sum of the flow rates from the pipes connected to the node to the node must be equal to the sum of the flow rates out of the node. Sq t,j =Σq t,k (2) Where: q t,j and q t,k are the mass flow rates of the working fluid in pipelines j and k during period t, kg / s; The thermal model consists of the thermal power equation and the node temperature mixed equation Where: and are the set of pipes connected to node n and injecting traffic into node n and the set of pipes that flow out of node n respectively; H t,i is the heat exchange between heat exchange station i and heat load during period t, kJ; m t,i is the mass of the working fluid flowing through heat exchange station i during period t, kg; and are the supply water temperature and return water temperature flowing through heat exchange station i during period t, ℃; is the heat load at heat exchange station i during period t, kW; is the outlet temperature of hot water flowing out of pipe j during period t, °C; is the outlet temperature of the hot water flowing out of pipe k during period t, °C; represents the pipe whose outlet n is connected to the node, represents a pipe whose inlet is connected to node n; The generalized equivalent thermal energy storage model is specifically: In the formula, is the inlet temperature of hot water in pipe p in the water supply network at time t; is the inlet temperature of hot water in pipe p in the return network at time t; is the heat input from the heat source to the heating network at time τ; is the heat output of the heating network to the heat load at time τ; The heat network flexibility assessment model is established based on the generalized equivalent thermal energy storage model, as follows: A heat network flexibility assessment model is established based on the heat storage characteristics of the heat supply network, and the operational flexibility of the thermal system is defined as the range in which the heat input power deviates from the benchmark heat input power under the system operation constraints. First, build a heat input power model Where: and They refer to the maximum and minimum thermal energy storage capacity deviations, respectively; and They refer to the maximum and minimum thermal input power deviations, respectively; and Refers to the maximum and minimum thermal input power ramp rates respectively; Refers to the energy storage capacity of the heating network under baseline conditions; Refers to the heat input power under reference conditions; Upper limit of thermal input power deviation and lower limit It can be calculated by the following formula: The step S2 is specifically as follows: Constructing the power constraints of the heat and power integrated energy system considering the operation flexibility; Where: P in,i and P out,i represents the active power injected by the thermal system into the power system at node i and the active power output by the power system to the thermal system at node i; Q in,i and Q out,i represents the reactive power injected by the thermal system into the power system at node i and the reactive power output by the power system to the thermal system at node i; ΔP i and ΔQ i Respectively represent the deviation of active power and reactive power of node i; ε i represents the flexibility index at node i; Construct thermal constraints of a heat-power integrated energy system taking into account operational flexibility; In the formula, The thermal power output at node n is the thermal energy generated by the coupling of the thermal system and the power system and the internal energy storage device of the thermal system at time t; is the heat energy input from other energy systems to the thermal system at node n at time t, is the heat energy output of the thermal system at node n to other energy systems; ΔΦ n,t Indicates the thermal energy deviation of node n; δ n,t represents the flexibility index at node n; The thermal power balance constraint considering the thermal network energy storage performance is: At the same time, considering that during the dispatching stage of a day, the thermal network in stable operation should be in a state of energy balance, the thermal network balance constraint should also be met: The optimization scheduling objective is to minimize the operation cost of the heat-power coordinated integrated energy system, and the operation flexibility of the system and the operation constraints of each link in the heat-power coordinated integrated energy system are considered. Based on the MATLAB-YALMIP platform, the optimization scheduling model considering the flexibility of the heat-power coordinated integrated energy system is solved by the CPLEX solver; The optimization scheduling model considering the flexibility of the heat and power coordinated integrated energy system is as follows: The constraints are as follows: 0≤P t WT ≤P t WT,pre (31) P t WT +P t WT,loss =P t WT,pre (32) 0≤P t PV ≤P t PV,pre (33) P t PV +P t PV,loss =P t PV,pre (34) P t,i =-B'θ t,i (38) P l,min <P l <P l,max (40) Where P t unit P is the electric power generated by the thermal power generator unit during period t, kW; t CHP is the electric power generated by CHP during period t, kW; P t WT is the electric power generated by the fan during period t, kW; P t PV is the power generated by photovoltaic power in period t, kW; P t EB P is the power consumed by the electric boiler during period t, kW; t load is the electrical load during period t, kW; is the thermal power generated by CHP during period t, kW; is the thermal power generated by the electric boiler during period t, is the heat load of the system during period t, kW; and They refer to the maximum and minimum heat input power deviations, respectively; ε is the CHP thermal-to-electric ratio; η is the CHP gas-to-heat conversion efficiency; η CHP is CHP efficiency; b v The calorific value of natural gas combustion and Respectively represent the upper and lower limits of CHP output, kW; and Respectively represent the maximum upward and downward climbing rates, kW; η EB is the electricity-heat conversion efficiency of the electric boiler; and Respectively represent the upper and lower limits of EB output, kW; and Respectively represent the maximum upward and downward climbing rates, kW; P t WT,pre and P t PV,pre Respectively t The predicted output value of wind turbine and photovoltaic power in the period, kW; P t WT,loss , P t PV,loss They represent the abandoned wind power and abandoned solar power in period t, kW; B' is the susceptance matrix of the grid branch; P t,i is the active power injected into the system by node i at time t, kW; θ t,i is the voltage phase angle of node i at time t; P l is the transmission power capacity of transmission line l, P l,min , P l,max They are respectively the lower and upper limits of the transmission power capacity of transmission line l.

2. An optimization scheduling system considering the flexibility of a heat-power integrated energy system, characterized in that: The system is implemented by an optimization scheduling method considering the flexibility of a heat-power coordinated integrated energy system as described in claim 1, comprising: Data acquisition and processing module, used to collect and process temperature parameters in the water supply network; The model building module is used to construct an optimal dispatching model that takes into account the flexibility of the heat-power coordinated integrated energy system, including constructing a power system model, a thermal system model that takes into account the heat storage characteristics of the heating pipeline network, and then establishing a heat network flexibility evaluation model based on a generalized equivalent thermal energy storage model; constructing a system operation model that takes into account the flexibility of the heat-power coordinated integrated energy system; and constructing an optimal dispatching model for the heat-power coordinated integrated energy system with the goal of minimizing the operating cost of the heat-power coordinated integrated energy system. The evaluation module is used to obtain the flexibility evaluation index value of the heat and power coordinated integrated energy system, and to evaluate the optimal scheduling method of the heat and power coordinated integrated energy system to determine a reasonable optimal scheduling method.

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