A power system dispatching method considering comprehensive evaluation of thermal power unit flexibility

Abstract

The present invention discloses a power system dispatching method that considers the comprehensive evaluation of the flexibility of thermal power units and belongs to the technical field of power system optimization. It includes: step 1: considering the access of thermal power units, new energy power generation and load to the power grid, taking the lowest system operation cost, the smallest network loss and the smallest amount of abandoned wind and light as the optimization goals, and establishing an objective function; step 2: establishing a comprehensive index evaluation model for the flexibility of multiple thermal power units under the conditions of deep peak regulation and large-scale load changes of thermal power units; step 3: considering the constraints on the thermal power unit side, the new energy side and the power grid side, establishing a source-grid-load dispatching model; step 4: using a particle swarm optimization algorithm to solve the source-grid-load dispatching model established in step 3, and obtaining the optimal output of each unit. The present invention comprehensively considers the different technical characteristics and economic characteristics of different units, which is conducive to improving the absorption rate of new energy in the system, alleviating the peak regulation pressure of thermal power units, and guiding the flexibility transformation of thermal power units.

Description

Technical Field

[0001] The present invention relates to the technical field of power system optimization, and in particular to a power system dispatching method considering comprehensive evaluation of the flexibility of thermal power units. Background Art

[0002] In recent years, the installed capacity of renewable wind power and solar power generation in my country has continued to expand and will become the main power source in my country. However, the power generation capacity of new energy is severely limited by external natural conditions, which makes the power system's demand for regulating power capacity increasingly increasing. Therefore, it is imperative to vigorously develop safe and reliable power sources with deep and flexible adjustment characteristics. This is also a historical responsibility that thermal power must and should be able to bear.

[0003] At present, each thermal power unit is undergoing flexibility transformation to fully respond to the fluctuation of the power system and achieve the goals of reducing the minimum output, rapid start and stop, and rapid load increase and decrease. Considering the differences in the operating characteristics and economic characteristics of different units, it is necessary to establish a more complete comprehensive evaluation model considering the flexibility of thermal power units to make the power system dispatch more reasonable and perfect. Summary of the invention

[0004] The purpose of the present invention is to propose a power system dispatching method considering the comprehensive evaluation of the flexibility of thermal power units, characterized in that the method comprises the following steps:

[0005] Step 1: Based on the comprehensive index of the flexibility of multiple thermal power units, considering the access of thermal power units, new energy power generation and loads to the power grid, the objective function is established with the lowest system operation cost, the lowest network loss and the lowest amount of wind and solar power abandonment as the optimization goals;

[0006] Step 2: Under the conditions of deep peak regulation and large-scale load changes of thermal power units, considering the differences in flexibility of different units, a comprehensive index evaluation model for the flexibility of multiple thermal power units is established;

[0007] Step 3: Considering the constraints on the thermal power units, renewable energy and power grid, a source-grid-load dispatch model is established;

[0008] Step 4: Use the particle swarm optimization algorithm to solve the source-grid-load scheduling model established in step 3 to obtain the optimal output of each unit.

[0009] The objective function in step 1 is:

[0010]

[0011] Where F is the objective function; α, β, γ are weight coefficients; G is the total number of thermal power units, C g (t) is the comprehensive cost of unit g at time t, a gis the comprehensive evaluation coefficient of the flexibility of unit g; M is the number of grid nodes, P loss,i is the sum of active power injected into node i; N represents the number of wind farms and photovoltaic farms at time t, P DG,i represents the predicted output value of wind farm and photovoltaic farm at node i at time t, P DG,f,i Represents the actual output value of the wind farm and photovoltaic farm at the i node.

[0012] The comprehensive index evaluation model for the flexibility of multiple thermal power units in step 2 is:

[0013] Comprehensive cost of a single thermal power unit:

[0014] minC g (t) = a g,1 C g,1 (t)+a g,2 C g,2 (t)+a g,3 C g,3 (t) (2)

[0015] In the formula, C g (t) is the comprehensive cost of unit g at time t, a g,1 , a g,2 , a g,3 is the weight coefficient; C g,1 (t) is the coal burning cost of unit g at time t, C g,2 (t) is the ramp cost of unit g at time t, C g,3 (t) is the pollutant emission penalty cost of unit g at time t; where the coal burning cost of unit g at time t is as shown in formula (3):

[0016]

[0017] In the formula, is the coal consumption coefficient of thermal power unit g; P g (t) represents the output power of thermal power unit g at time t; P g,max , P g,min Indicates the maximum and minimum output power of unit g, P g,b It is the dividing point between deep peak regulation and basic peak regulation of unit g;

[0018] The ramp cost of unit g at time t is as follows:

[0019]

[0020] In the formula, σ g is the ramp cost factor of unit g;

[0021] The pollutant emission penalty cost of unit g at time t is as follows:

[0022] C g,3 (t) = Q g,SO2 +Q g,NOx +Q g,TSP (5)

[0023]

[0024]

[0025] Q g,TSP =q 3 ×M g ×μ×(1-η g,c ) (8)

[0026] M g =u g (P g (t)) 2 +v g P g (t)+w g (9) In the formula, Q g,SO2 , Q g,NOx , Q g,TSP Respectively represent SO 2 、NO x and dust emission costs;q 1 Indicates SO 2 Emissions charging standards; Indicates SO 2 The molecular weight ratio of M to S; g Indicates the coal consumption of unit g; S g,ar Indicates the sulfur content of the coal fired by unit g as received; K g,SO2 Indicates the SO during the combustion process of the unit g 2 The conversion rate of g,SO2 is the desulfurization efficiency of unit g; q 2 Indicates NO x Emissions charging standards; Indicates NO x The molecular weight ratio of N g,ar represents the nitrogen content of the coal as received; k represents the NO generated by nitrogen in the fuel x Accounts for all NO x The proportion of emissions; K g,NOx Indicates the NO in the combustion process of the unit g x The conversion rate of g,N is the denitration efficiency of the denitration device of unit g; q 3 represents the dust emission charging standard; η represents the dust emission coefficient; η g,c Indicates dust removal efficiency; u g 、v g、w g Both represent the coal consumption coefficient of unit g;

[0027] The flexibility comprehensive evaluation coefficient a of unit g in the objective function g as follows:

[0028]

[0029] S g =P g,max -P g,min (11)

[0030] V g =min{R g,u ,R g,d} (12)

[0031] Where b g,1 、b g,2 Adjustment capacity index for unit g and adjust speed indicator The weight coefficient, S g is the regulating capacity of the unit g, that is, the stable regulating range of the unit output power under normal operation of the unit; V g is the speed adjustment of unit g, i.e. the upward climbing speed of the unit R g,u and the downward climbing speed R g,d The minimum value of .

[0032] The source-grid-load scheduling model in step 3 is the objective function of formula (1) and the following constraints:

[0033] Output constraints of thermal power units:

[0034] P g,min ≤P g (t)≤P g,max (13)

[0035] Thermal power unit ramp rate constraints:

[0036] -R g,d △t≤P g (t)-P g (t-1)≤R g,u △t (14)

[0037] New energy output constraints:

[0038] 0≤P DG,i (t)≤P DG,f,i (t) (15)

[0039] System power balance constraints:

[0040]

[0041] Where P g (t) is the output of unit g during period t, P DG (t) is the actual output of renewable energy in period t, P load (t) represents the load value during period t;

[0042] Grid voltage upper and lower limit constraints:

[0043] V m,min ≤V m ≤V m,max (17)

[0044] Where V m is the voltage amplitude of node m, V m,max , V m,min are the upper and lower limits of the voltage amplitude of node m respectively;

[0045] Branch flow constraints:

[0046]

[0047] In the formula, G ii G is the self-conductance; ij is mutual conductance; B ij is the mutual susceptance; θ ij is the phase angle difference between node i and node j; P g,i is the output value of the thermal power unit g connected to the power grid at node i; P DG,i is the predicted value of the new energy output connected to node i; P load,i is the load at node i;

[0048] Branch current upper limit constraint:

[0049]

[0050] In the formula, I ij,max is the maximum current value allowed to pass between node i and node j; E represents the power grid branch.

[0051] The beneficial effects of the present invention are:

[0052] The method proposed in the present invention comprehensively considers the different technical characteristics and economic characteristics of different units, which is conducive to improving the system's new energy consumption rate, alleviating the peak load pressure of thermal power units, and guiding the flexibility transformation of thermal power units. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] Figure 1 The present invention is a flow chart of a method for dispatching a power system taking into account comprehensive evaluation of the flexibility of thermal power units. DETAILED DESCRIPTION

[0054] The present invention proposes a power system dispatching method considering comprehensive evaluation of the flexibility of thermal power units. The present invention is further described below in conjunction with the accompanying drawings and specific embodiments.

[0055] Figure 1 The flowchart of the power system dispatching method considering the comprehensive evaluation of the flexibility of thermal power units in the present invention. The present invention considers the different operating characteristics and economic characteristics of different thermal power units connected to the power grid under the working conditions of adapting to large fluctuations in output and responding quickly to various changes, and establishes a comprehensive evaluation model for the flexibility of multiple units. The optimization goals are to minimize system operating costs, minimize network losses, and minimize wind and solar power abandonment, and the particle swarm algorithm is used for optimization and solution to obtain the best unit dispatching plan. Specifically, the following steps are included:

[0056] (1) Based on the comprehensive flexibility index of multiple thermal power units, considering the access of thermal power units, new energy generation and loads to the power grid, the objective function is established with the lowest system operation cost, the lowest network loss and the lowest amount of wind and solar power abandonment as the optimization goals;

[0057] (2) Under the conditions of deep peak load regulation and large-scale load changes of thermal power units, the flexibility comprehensive index evaluation model of multiple thermal power units is established by considering the differences in flexibility of different units;

[0058] (3) Considering the constraints on the thermal power units, renewable energy and power grid, a source-grid-load dispatching model is established;

[0059] (4) The particle swarm optimization algorithm is used to solve the established source-grid-load multi-objective optimization scheduling model to obtain the optimal output of each unit.

[0060] The objective function in step (1) is as follows:

[0061] The present invention considers the optimal scheduling of thermal power units, new energy power generation and load access to the M-node power grid, and has the following objective function:

[0062]

[0063] Among them, F is the objective function, which should be minimized; α, β, γ are weight coefficients, which are determined by the dispatcher according to the hierarchical analysis method; G is the total number of thermal power units, C g (t) is the comprehensive cost of unit g at time t, a g is the comprehensive evaluation coefficient of the flexibility of unit g; M is the number of grid nodes, P loss,i is the sum of active power injected into node i, which represents the grid loss; N represents the number of wind farms and photovoltaic farms at time t, P DG,i represents the predicted output value of wind farm and photovoltaic farm at node i at time t, P DG,f,iIt represents the actual output value of the wind farm and photovoltaic farm at the i-node. The last item represents the amount of wind and solar power abandoned.

[0064] The comprehensive evaluation model of multi-unit flexibility in step (2) is as follows:

[0065] The first item in the objective function in step (1) is to construct a comprehensive evaluation model for the flexibility of multiple units by comprehensively considering the differences in the operating characteristics and economic characteristics of different thermal power units connected to the power grid. The specific steps are as follows:

[0066] 1) Comprehensive cost model of a single thermal power unit:

[0067] Considering the coal burning cost of thermal power units, the ramping cost of thermal power units, and the penalty cost of pollutant emissions, the cost model of unit g is as follows:

[0068] minC g (t) = a g,1 C g,1 (t)+a g,2 C g,2 (t)+a g,3 C g,3 (t) (2)

[0069] Where C g (t) is the comprehensive cost of unit g at time t, a g,1 , a g,2 , a g,3 is the weight coefficient, determined by the analytic hierarchy process; C g,1 (t) is the coal burning cost of unit g at time t, C g,2 (t) is the ramp cost of unit g at time t, C g,3 (t) is the pollutant emission penalty cost of unit g at time t.

[0070] Among them, the coal burning cost of a single unit is as follows:

[0071]

[0072] In the formula, is the coal consumption coefficient of thermal power unit g, which is related to unit type, combustion quality and coal price; P g (t) represents the output power of thermal power unit g at time t; P g,max , P g,min Indicates the maximum and minimum output power of unit g, P g,b It is the dividing point between deep peak regulation and basic peak regulation of unit g.

[0073] The ramp cost of a single unit is as follows:

[0074]

[0075] Among them, σ g is the ramp cost factor of unit g.

[0076] The pollution penalty cost for a single unit is as follows:

[0077] C g,3 (t) = Q g,SO2 +Q g,NOx +Q g,TSP (5)

[0078]

[0079]

[0080] Q g,TSP =q 3 ×M g ×μ×(1-η g,c ) (8)

[0081] M g =u g (P g (t)) 2 +v g P g (t)+w g (9) In the formula, Q g,SO2 , Q g,NOx , Q g,TSP Respectively represent SO 2 、NO x and dust emission costs. 1 Indicates SO 2 Emissions charging standards; Indicates SO 2 The molecular weight ratio of M to S; g Indicates the coal consumption of unit g; S g,ar Indicates the sulfur content of the coal fired by unit g as received; K g,SO2 Indicates the SO during the combustion process of the unit g 2 The conversion rate of g,SO2 is the desulfurization efficiency of unit g; q 2 Indicates NO x Emissions charging standards; Indicates NO x The molecular weight ratio of N g,ar represents the nitrogen content of the coal as received; k represents the NO generated by nitrogen in the fuel x Accounts for all NO x The proportion of emissions; K g,NOx Indicates the NO in the combustion process of the unit g x The conversion rate of g,N is the denitration efficiency of the denitration device of unit g; q3 represents the dust emission charging standard; μ represents the dust emission coefficient; η g,c Indicates dust removal efficiency; u g 、v g 、w g Both represent the coal consumption coefficient of unit g.

[0082] 2) Calculation of comprehensive evaluation coefficient of multi-unit flexibility index:

[0083] The output of each unit is determined by considering the flexibility index of the operating characteristics of each unit. The present invention calculates the weight coefficient of the comprehensive evaluation of unit flexibility based on the two technical indicators of adjustment capacity and adjustment speed, so that the constraints of units with relatively large adjustment capacity and relatively fast adjustment speed are relaxed, and the output is relatively high; the constraints of units with relatively small adjustment capacity and relatively slow adjustment speed become strict, and the output is relatively low. In the objective function, the comprehensive evaluation coefficient ag of unit flexibility is calculated as follows:

[0084]

[0085] S g =P g,max -P g,min (11)

[0086] V g =min{R g,u ,R g,d} (12) In the formula, b g,1 、b g,2 Adjustment capacity index for unit g and adjust speed indicator The weight coefficient, S g is the regulating capacity of the unit g, that is, the stable regulating range of the unit output power under normal operation of the unit; V g is the speed adjustment of unit g, i.e. the upward climbing speed of the unit R g,u and the downward climbing speed R g,d The minimum value of .

[0087] 1) and 2) together constitute a comprehensive evaluation model for multi-unit flexibility.

[0088] The source-grid-load scheduling model in step (3) is established as follows:

[0089] Output constraints of thermal power units:

[0090] P g,min ≤P g (t)≤P g,max (13)

[0091] Thermal power unit ramp rate constraints:

[0092] -R g,d △t≤P g (t)-P g (t-1)≤R g,u △t (14)

[0093] New energy output constraints:

[0094] 0≤P DG,i (t)≤P DG,f,i (t) (15)

[0095] System power balance constraints:

[0096]

[0097] Where P g (t) is the output of unit g during period t, P DG (t) is the actual output of new energy in period t, P load (t) represents the load value during period t.

[0098] Grid voltage upper and lower limit constraints:

[0099] V m,min ≤V m ≤V m,max (17)

[0100] Among them, V m is the voltage amplitude of node m, V m,max , V m,min are the upper and lower limits of the voltage amplitude at node m respectively.

[0101] Branch flow constraints:

[0102]

[0103] Among them, G ii G is the self-conductance; ij is mutual conductance; B ij is the mutual susceptance; θ ij is the phase angle difference between node i and node j; P g,i is the output value of the thermal power unit g connected to the power grid at node i; P DG,i is the predicted value of the new energy output connected to node i; P load,i is the load at node i.

[0104] Branch current upper limit constraint:

[0105]

[0106] Among them, I ij,max is the maximum current value allowed to pass between node i and node j. E represents the power grid branch.

[0107] Step (4): The above objective function (1) and constraint conditions (13) to (19) constitute the source-grid-load multi-objective optimization scheduling model. The particle swarm optimization algorithm can be used to solve the nonlinear programming method to obtain the optimal output of each unit.

[0108] This embodiment comprehensively considers the different technical characteristics and economic characteristics of different units, which is conducive to improving the system's new energy absorption rate, alleviating the peak load pressure of thermal power units, and guiding the flexibility transformation of thermal power units.

[0109] This embodiment is only a preferred specific implementation of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily thought of by a person skilled in the art within the technical scope disclosed by the present invention should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. A power system dispatching method considering comprehensive evaluation of thermal power unit flexibility, characterized in that: The method comprises the following steps: Step 1: Based on the comprehensive index of the flexibility of multiple thermal power units, considering the access of thermal power units, new energy power generation and loads to the power grid, the objective function is established with the lowest system operation cost, the lowest network loss and the lowest amount of wind and solar power abandonment as the optimization goals; The objective function in step 1 is: Where F is the objective function; α, β, γ are weight coefficients; G is the total number of thermal power units, C g (t) is the comprehensive cost of unit g at time t, a g is the comprehensive evaluation coefficient of the flexibility of unit g; M is the number of grid nodes, P loss，i is the sum of active power injected into node i; N represents the number of wind farms and photovoltaic farms at time t, P DG，i represents the predicted output value of wind farm and photovoltaic farm at node i at time t, P DG，f，i Represents the actual output value of the wind farm and photovoltaic farm at the i node; Step 2: Under the conditions of deep peak regulation and large-scale load changes of thermal power units, considering the differences in flexibility of different units, a comprehensive index evaluation model for the flexibility of multiple thermal power units is established; The comprehensive index evaluation model for the flexibility of multiple thermal power units in step 2 is: Comprehensive cost of a single thermal power unit: minC g (t)=a g，1 C g，1 (t)+a g，2 C g，2 (t)+a g，3 C g，3 (t) (2) In the formula, C g (t) is the comprehensive cost of unit g at time t, a g，1 , a g，2 , a g，3 is the weight coefficient; C g，1 (t) is the coal burning cost of unit g at time t, C g，2 (t) is the ramp cost of unit g at time t, C g，3 (t) is the pollutant emission penalty cost of unit g at time t; where the coal burning cost of unit g at time t is as shown in formula (3): In the formula, is the coal consumption coefficient of thermal power unit g; P g (t) represents the output power of thermal power unit g at time t; P g，max , P g，min Indicates the maximum and minimum output power of unit g, P g，b It is the dividing point between deep peak regulation and basic peak regulation of unit g; The ramp cost of unit g at time t is as follows: In the formula, σ g is the ramp cost factor of unit g; The pollutant emission penalty cost of unit g at time t is as follows: C g，3 (t)=Q g，SO2 +Q g，NOx +Q g，TSP (5) Q g，TSP =q3×M g ×μ×(1-η g，c ) (8) M g =u g (P g (t)) 2 +v g P g (t)+w g (9) In the formula, Q g，SO2 , Q g，NOx , Q g，TSP Respectively represent SO2 and NO x and dust emission costs; q1 represents the SO2 emission charge standard; Indicates the molecular weight ratio of SO2 and S; M g Indicates the coal consumption of unit g; S g，ar Indicates the sulfur content of the coal fired by unit g as received; K g，SO2 Indicates the conversion rate of SO2 during the combustion process of unit g; η g，SO2 is the desulfurization efficiency of unit g; q2 represents NO x Emissions charging standards; Indicates NO x The molecular weight ratio of N g，ar represents the nitrogen content of the coal as received; k represents the NO generated by nitrogen in the fuel x Accounts for all NO x The proportion of emissions; K g，NOx Indicates the NO in the combustion process of the unit g x The conversion rate of g，N is the denitration efficiency of the denitration device of unit g; q3 represents the dust emission charging standard; μ represents the dust emission coefficient; η g，c Indicates dust removal efficiency; u g 、v g 、w g Both represent the coal consumption coefficient of unit g; The flexibility comprehensive evaluation coefficient a of unit g in the objective function g as follows: S g =P g，max -P g，min (11) V g =min{R g，u ,R g，d } (12) Where b g，1 、b g，2 Adjustment capacity index for unit g and adjust speed indicator The weight coefficient, S g is the regulating capacity of the unit g, that is, the stable regulating range of the unit output power under normal operation of the unit; V g is the speed adjustment of unit g, i.e. the upward climbing speed of the unit R g，u and the downward climbing speed R g，d The minimum value of Step 3: Considering the constraints on the thermal power units, renewable energy and power grid, a source-grid-load dispatch model is established; Step 4: Use the particle swarm optimization algorithm to solve the source-grid-load scheduling model established in step 3 to obtain the optimal output of each unit.

2. The power system dispatching method considering the comprehensive evaluation of the flexibility of thermal power units according to claim 1 is characterized in that: The source-grid-load scheduling model in step 3 is the objective function of formula (1) and the following constraints: Output constraints of thermal power units: P g，min ≤P g (t)≤P g，max (13) Thermal power unit ramp rate constraints: -R g，d Δt≤P g (t)-P g (t-1)≤R g，u Δt (14) New energy output constraints: 0≤P DG，i (t)≤P DG，f，i (t) (15) System power balance constraints: Where P g (t) is the output of unit g during period t, P DG (t) is the actual output of new energy in period t, P load (t) represents the load value during period t; Grid voltage upper and lower limit constraints: In m，min ≤V m ≤V m，max (17) Where V m is the voltage amplitude of node m, V m，max , V m，min are the upper and lower limits of the voltage amplitude of node m respectively; Branch flow constraints: In the formula, G ii G is the self-conductance; ij is mutual conductance; B ij is the mutual susceptance; θ ij is the phase angle difference between node i and node j; P g,i is the output value of the thermal power unit g connected to the power grid at node i; P DG,i is the predicted value of the new energy output connected to node i; P load,i is the load at node i; Branch current upper limit constraint: In the formula, I ij,max is the maximum current value allowed to pass between node i and node j; E represents the power grid branch.

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