Coal-water-wind-solar wide-area power system optimal configuration method for improving flexibility

Abstract

The invention discloses a coal-water-wind-light wide-area power system optimal configuration method for improving flexibility, and belongs to the technical field of new energy power generation, and the method comprises the steps: building a coal-water-wind-light wide-area power system operation model; according to the coal-water-wind-light wide-area power system operation model, carrying out flexibility quantitative analysis on the coal-water-wind-light wide-area power system, and establishing a flexibility-considered wide-area power system operation model adopting a flexible supply and demand balance working mode; establishing an investment decision model by taking the total investment cost of the coal-water-wind-light wide-area power system as an optimization target; establishing a market clearing model according to constraint conditions of the investment decision model; and establishing an inner and outer double-layer planning-operation integrated model of which the outer layer is an investment decision model and the inner layer is a market clearing model, and obtaining a coal-water-wind-light wide-area power system planning scheme with improved flexibility through double-layer model optimization. According to the invention, the problem of insufficient flexibility in the current wide-area power system is solved.

Description

Technical Field

[0001] The present invention belongs to the technical field of renewable energy power generation, and in particular relates to a method for optimizing the configuration of a coal-water-wind-solar wide-area power system with improved flexibility. Background Art

[0002] In recent years, with the requirements of environmental obligations, power supply security, the evolution of new power generation technologies, the development of communication control technologies and new markets, the power system around the world is undergoing tremendous changes. At present, the form of energy utilization by human beings is still mainly based on traditional fossil energy, but fossil energy has the disadvantages of being non-renewable and causing serious environmental pollution, which prompts the pursuit of low-carbon development. In order to fully absorb renewable energy and improve the flexibility of traditional energy, it is necessary to study the optimization configuration technology of multiple types of energy.

[0003] At present, the research on flexibility planning of multi-type energy power systems has the following shortcomings: (1) A unified complementary coupling mathematical model including wind, light, water, fire and other energy resources has not been systematically established. At the same time, there is little research on the synergy and complementarity between multiple types of power sources. There is also a lack of flexibility evaluation indicators and synergy planning methods that can quantitatively evaluate multi-time and space scales and multi-energy power systems. (2) In terms of power source modeling and complementary characteristics of wide-area power systems, a single model of renewable energy systems has been established, but the compatibility between renewable energy models and traditional power models is not high, and the mechanism of using unit operation to improve renewable energy consumption is still unclear. (3) In the planning research of wide-area power systems containing multiple types of energy, resource coordination and capacity storage are often used to optimize system operation in order to reduce operating costs and increase wind and light consumption rates. There is little research on the synergy operation mechanism of multi-energy units from the perspective of flexibility, resulting in a large amount of available flexibility resources not being taken seriously, resulting in a serious lack of flexibility balance in the power system. Summary of the invention

[0004] In view of the above-mentioned deficiencies in the prior art, the present invention provides a method for optimizing the configuration of a coal-water-wind-solar wide-area power system with improved flexibility, which solves the problem of insufficient flexibility in the current wide-area power system.

[0005] In order to achieve the above-mentioned invention object, the technical solution adopted by the present invention is: a method for optimizing the configuration of a coal-water-wind-solar wide-area power system with improved flexibility, comprising:

[0006] Establish a coal-water-wind-solar wide-area power system operation model;

[0007] According to the coal-water-wind-solar wide-area power system operation model, conduct a quantitative analysis of the flexibility of the coal-water-wind-solar wide-area power system, and establish a wide-area power system operation model that takes flexibility into account and adopts a flexible supply and demand balance working mode;

[0008] Taking the total investment cost of coal-water-wind-solar wide-area power system as the optimization target, an investment decision model is established;

[0009] According to the constraints of the investment decision-making model, the market clearing model is established with the social welfare of the wide-area power system as the optimization goal;

[0010] An integrated planning and operation model with two layers is established, with the outer layer being the investment decision-making model and the inner layer being the market clearing model. Through the optimization of the two-layer model, a planning scheme for the coal-water-wind-solar wide-area power system with improved flexibility is obtained.

[0011] Furthermore, the coal-water-wind-light wide-area power system operation model includes a coal power output model, a hydropower output model, a wind power output model, a photovoltaic output model and a transmission line model:

[0012]

[0013] P hp,t =a hp ×q t 2 +b hp ×q t +c hp

[0014]

[0015]

[0016]

[0017] Among them, P t cp is the output power of the coal-fired power unit at time t; It is the minimum technical output level of coal-fired power units; P is the maximum technical output level of coal-fired power units; hp,t is the output power of the hydropower unit at time t; a hp 、b hp and c hp The water energy-electricity conversion coefficient of the hydropower unit; q t is the power generation flow of the hydropower station at time t; v t is the wind speed of the fan hub at time t; v wind,t is the wind speed at the wind measuring point at time t; h is the hub height; h w is the height of the wind measuring point; P t wp is the wind turbine output power at time t; V in is the cut-in wind speed; V out is the cut-out wind speed; P wnis the rated power of the wind turbine; V r is the rated wind speed; P t pv is the output power of the photovoltaic battery group at time t; L solar,t is the solar radiation intensity in the area where the photovoltaic cell is located at time t; m is the derating coefficient of the photovoltaic cell; P pvn is the nominal power of the photovoltaic cell under standard test conditions; α is the power temperature coefficient; T C,t is the actual working temperature of the photovoltaic battery group at time t; T stc is the standard operating temperature of the photovoltaic cell group; T temp,t is the ambient temperature of the photovoltaic cell at time t; N oct is the nominal temperature of the photovoltaic cell group; P t tr is the transmission power of the interconnection line at time t; is the maximum transmission power limit of the interconnection line; is the transmission power from area a to a′ at time t; is the transmission power from area a′ to a at time t.

[0018] Furthermore, the results of the flexibility quantitative analysis of the coal-water-wind-solar wide-area power system are as follows:

[0019]

[0020]

[0021]

[0022]

[0023] F t N =F t l +F t wp +F t pv +ΔF t wp +ΔF t pv

[0024]

[0025]

[0026]

[0027] in, is the operational flexibility margin of the power system in region a in the upward direction at time t; is the operational flexibility margin of the power system in region a in the downward direction at time t; is the total amount of flexibility resources provided by region a in the upward direction at time t; is the total amount of flexibility resources provided by region a in the downward direction at time t; is the system flexibility requirement of area a at time t; is the total amount of flexibility resources provided by coal-fired power units in region a in the upward direction at time t; is the total amount of flexibility resources provided by the hydropower units in region a in the upward direction at time t; The total amount of flexibility resources provided in the upward direction for flexible line transmission in area a at time t; The total amount of flexibility resources provided for the flexibility ramping product in area a at time t; is the total amount of flexibility resources provided by coal-fired power units in region a in the downward direction at time t; is the total amount of flexibility resources provided by the hydropower units in region a in the downward direction at time t; The total amount of flexible resources provided in the downstream direction for flexible line transmission in area a at time t; N cp is the total number of coal-fired power units; n1 is the number of the coal-fired power unit; is the maximum technical output level of the n1th coal-fired power unit in region a; is the technical output level of the n1th coal-fired power unit in region a at time t; is the upward climbing capability of the n1th coal-fired power unit in region a; Δt is the scheduling interval time; is the minimum technical output level of the n1th coal-fired power unit in region a; is the climbing capacity of the n1th coal-fired power unit in area a in the downward direction; N hp is the total number of hydropower units; n2 is the hydropower unit number; is the maximum technical output level of the n2th hydropower unit in region a; is the technical output level of the n2th hydropower unit in region a at time t; is the climbing capacity of the n2th hydropower unit in area a in the upward direction; is the minimum technical output level of the n2th hydropower unit in region a; is the climbing ability of the n2th hydropower unit in area a in the downward direction; F t N is the system flexibility requirement at time t; F t 1 is the flexibility demand of system load at time t; F t wp is the flexibility demand of wind turbines in the system at time t; F t pvis the flexibility demand of the system PV unit at time t; ΔF t wp is the power fluctuation caused by the uncertain output of the wind turbine; ΔF t pv Power fluctuation caused by the uncertainty of the output of photovoltaic units; is the active power of the system load at time t+1; P t l is the active power of the system load at time t; is the active power of the system wind turbine at time t+1; P t wp is the active power of the system wind turbine at time t; is the active power of the system photovoltaic unit at time t+1; P t pv is the active power of the system photovoltaic unit at time t; P t wp,real is the actual output value of the system wind turbine at time t; P t wp,pre is the power forecast value of the system wind turbine at time t; is the power prediction error of the system wind turbine at time t; P t pv,real is the actual output value of the system photovoltaic unit at time t; P t pv,pre is the power prediction value of the system photovoltaic unit at time t; is the power prediction error of the system photovoltaic unit at time t.

[0028] Furthermore, the flexible supply and demand balancing working mode is specifically as follows:

[0029] When the total amount of flexibility resources is greater than or equal to the system flexibility demand, the electricity generated by wind turbines and photovoltaic units will be fully consumed first, and then hydropower units and coal-fired units will perform deep peak regulation, and finally flexible line transmission will be used to supplement it; when the total amount of flexibility resources is less than the system flexibility demand, hydropower units and coal-fired units will perform peak regulation first, and then wind turbines and photovoltaic units will supplement electricity, and finally flexible ramping products will be used to optimize operational flexibility; the flexibility resources include coal-fired units, hydropower units, flexible line transmission and flexible ramping products; the system flexibility demand includes wind turbines, photovoltaic units and power loads.

[0030] Furthermore, the objective function of the investment decision model is:

[0031]

[0032]

[0033] Among them, min is the minimum function; C all is the total investment cost; is the investment and construction cost of area a in planning year y; is the resource maintenance cost of region a in planning year y; is the operating cost of region a under scenario s in planning year y; i is the category number of power generation resources; d is a 0-1 variable used to determine whether it is necessary to repay the previous debt, 1 for yes and 0 for no; K1 is the capital repatriation coefficient; is the unit capacity construction cost of the i-th power generation resource; P i,y,a is the planned capacity of the i-th generation resource in region a in the planning year y; is the construction cost per unit capacity of the transmission line; is the planned capacity of the transmission line in region a in the planning year y; K2 is the maintenance cost per unit capacity; is the built capacity of the i-th generation resource in region a in planning year y; is the new planned capacity of the i-th generation resource in region a in planning year y; is the capacity of the i-th retired generating resource in region a in planning year y; is the built capacity of the transmission line in region a in planning year y; is the new planned capacity of the transmission lines in region a in planning year y.

[0034] Furthermore, the constraints of the investment decision model include: resource upper limit constraint, annual maximum load constraint, annual operating power constraint and market pricing constraint:

[0035]

[0036]

[0037]

[0038] Among them, P i,y,a is the planned capacity of the i-th generation resource in region a in the planning year y; is the maximum exploitable technical capacity of the i-th power generation resource in region a in planning year y; Plan the capacity of the transmission line in area a in the planning year y; P a lc,max is the planned capacity of the maximum transmission line in region a; i is the category number of the power generation resource; δ is the load growth rate; γ y,a is the system reserve capacity factor; is the maximum load power value in area a in planning year y; is the annual power generation of coal-fired power units in region a in the planning year y; is the annual power generation of hydropower units in region a in the planning year y; is the annual power generation of wind turbines in region a in the planning year y; is the annual power generation of the photovoltaic units in region a in the planning year y; is the annual operating power of the power load in area a in the planning year y; is the minimum clearing price; y,a,s,t is the clearing price of the flexible ramping product in area a at time t under scenario s in planning year y; is the maximum clearing price.

[0039] Furthermore, the objective function of the market clearing model is:

[0040]

[0041] Among them, max is the maximum value function; F is the social welfare value; is the power load and power resource clearing price of region a at time t under scenario s in planning year y; is the power value of the power load and power resources in area a at time t under scenario s in the planning year y; is the price of coal-fired power resources clearing in area a at time t under scenario s in planning year y; is the power value of coal-fired power generation unit power resources in area a at time t under scenario s in planning year y; is the clearing price of hydropower resources in region a at time t under scenario s in planning year y; is the power value of the hydropower unit power resources in area a at time t under scenario s in the planning year y; is the wind turbine power resource clearing price in area a at time t under scenario s in planning year y; is the power value of wind turbine power resources in area a at time t under scenario s in planning year y; is the price of clearing electricity resources of photovoltaic units in region a at time t under scenario s in planning year y; is the power value of the photovoltaic power resource in area a at time t under scenario s in the planning year y.

[0042] Furthermore, the constraints of the market clearing model include regional power balance constraints, unit operation constraints, network security constraints, flexible operation balance constraints and new energy output constraints:

[0043]

[0044] in, N is the power value of power load and power resources in area a at time t under scenario s in planning year y; cp is the total number of coal-fired power units; n1 is the number of the coal-fired power unit; is the power value of the n1th coal-fired power unit in area a at time t under scenario s in planning year y; N hp is the total number of hydropower units; n2 is the hydropower unit number; is the power value of the n2th hydropower unit in area a at time t under scenario s in planning year y; is the actual output value of wind turbine power resources in area a at time t under scenario s in planning year y; is the actual output value of the photovoltaic power resources in area a at time t under scenario s in the planning year y; is the power value of the flexible line transmission from area a′ to a at time t under scenario s in planning year y; is the minimum technical output level of the n1th coal-fired power unit; is the maximum technical output level of the n1th coal-fired power unit; Provide the power value of the flexible ramping product for the n1th coal-fired power unit in area a at time t under scenario s in planning year y; is the power value of the n1th coal-fired power unit in area a at time t-1 under scenario s in planning year y; is the upward climbing capability of the n1th coal-fired power unit; Δt is the scheduling interval time; is the climbing capacity of the n1th coal-fired power unit in the downward direction; is the minimum technical output level of the n2th hydropower unit; is the maximum technical output level of the n2th hydropower unit; is the power value of the n2th hydropower unit in area a at time t-1 under scenario s in planning year y; is the climbing ability of the n2th hydropower unit in the upward direction; is the climbing ability of the n2th hydropower unit in the downward direction; is the maximum transmission power limit of the interconnection line from area a′ to a; is the power value of the flexible line transmission from area a to a′ at time t under scenario s in planning year y; The total amount of flexibility resources provided in the upward direction for area a at time t under scenario s in planning year y; To plan the flexibility demand of system load in area a at time t under scenario s in year y; To plan the flexibility requirements of system wind turbines in area a at time t under scenario s in year y; is the flexibility demand of the system PV units in area a at time t under scenario s in planning year y; Pr{} is the probability of the event occurring; To plan the power fluctuation of wind turbines in area a at time t under scenario s in year y due to the uncertainty of output; To plan the power fluctuation of photovoltaic units due to the uncertainty of output in area a at time t under scenario s in year y; t is the total prediction error at time t; α1 and α2 are the probabilities of the event being true; is the wind turbine output prediction error at time t; is the output prediction error of the photovoltaic unit at time t; is the wind turbine output prediction error distribution coefficient at time t; is the distribution coefficient of the photovoltaic unit output prediction error at time t; N() is the normal distribution function; is the resource credible capacity factor of the wind turbine; is the resource credible capacity factor of the PV unit; It is the maximum technical output level of the wind turbine; It is the maximum technical output level of the photovoltaic unit.

[0045] Furthermore, the two-layer model is optimized to obtain a coal-water-wind-light wide-area power system planning scheme with improved flexibility, specifically: a Lagrangian function is established for the inner market clearing model, an MPEC model is established by obtaining KKT conditions and complementary relaxation constraints, and the two-layer model is converted into a single-layer model through MPEC model processing for optimization and solution, thereby obtaining a coal-water-wind-light wide-area power system planning scheme with improved flexibility.

[0046] The beneficial effects of the present invention are as follows: the coal-water-wind-light wide-area power system of the present invention includes four energy forms: coal-fired power, hydropower, wind power, and photovoltaic power, and fully considers the output and peak-shaving characteristics of wind, solar, and water resources and the flexible adjustment capabilities of coal-fired power units and power transmission. By constructing an internal and external double-layer optimization configuration model, the planning of the coal-water-wind-light wide-area power system is optimized, thereby improving the flexibility of the system. In terms of economy, the present invention quantitatively analyzes the planning capacity and operating costs of various units from the perspective of flexibility, so that the system can achieve high-flexibility planning while ensuring economy, and takes the investment and construction costs of generator sets, the operating costs of coal-fired power units, the planning costs of transmission lines, and the abandonment costs of renewable energy into the scope of economic considerations. The flexibility optimization configuration method of the coal-water-wind-light wide-area power system from the perspective of different time scales enables the coal-water-wind-light wide-area power system to achieve the best planning of flexibility and economy. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 The figure is a flow chart of the method of the present invention.

[0048] Figure 2A schematic diagram of the relationship between flexibility resources and flexibility demands of the power system of the present invention.

[0049] Figure 3 It is a schematic diagram of the internal and external double-layer optimization configuration model of the coal-water-wind-light wide-area power system of the present invention.

[0050] Figure 4 This is a diagram of the unit output results of the present invention. DETAILED DESCRIPTION

[0051] The specific implementation modes of the present invention are described below so that those skilled in the art can understand the present invention. However, it should be clear that the present invention is not limited to the scope of the specific implementation modes. For those of ordinary skill in the art, as long as various changes are within the spirit and scope of the present invention as defined and determined by the attached claims, these changes are obvious, and all inventions and creations utilizing the concept of the present invention are protected.

[0052] like Figure 1 As shown, in one embodiment of the present invention, a method for optimizing the configuration of a coal-water-wind-solar wide-area power system with improved flexibility includes:

[0053] Establish a coal-water-wind-solar wide-area power system operation model;

[0054] According to the coal-water-wind-solar wide-area power system operation model, conduct a quantitative analysis of the flexibility of the coal-water-wind-solar wide-area power system, and establish a wide-area power system operation model that takes flexibility into account and adopts a flexible supply and demand balance working mode;

[0055] Taking the total investment cost of coal-water-wind-solar wide-area power system as the optimization target, an investment decision model is established;

[0056] According to the constraints of the investment decision-making model, the market clearing model is established with the social welfare of the wide-area power system as the optimization goal;

[0057] An integrated planning and operation model with two layers is established, with the outer layer being the investment decision-making model and the inner layer being the market clearing model. Through the optimization of the two-layer model, a planning scheme for the coal-water-wind-solar wide-area power system with improved flexibility is obtained.

[0058] The coal-water-wind-light wide-area power system operation model includes a coal power output model, a hydropower output model, a wind power output model, a photovoltaic output model and a transmission line model:

[0059]

[0060] P hp,t =a hp ×q t 2 +bhp ×q t +c hp

[0061]

[0062]

[0063] Among them, P t cp is the output power of the coal-fired power unit at time t; It is the minimum technical output level of coal-fired power units; P is the maximum technical output level of coal-fired power units; hp,t is the output power of the hydropower unit at time t; a hp , b hp and c hp The water energy-electricity conversion coefficient of the hydropower unit; q t is the power generation flow of the hydropower station at time t; v t is the wind speed of the fan hub at time t; v wind,t is the wind speed at the wind measuring point at time t; h is the hub height; h w is the height of the wind measuring point; P t wp is the output power of the wind turbine at time t; V in is the cut-in wind speed; V out is the cut-out wind speed; P wn is the rated power of the wind turbine; V r is the rated wind speed; P t pv is the output power of the photovoltaic battery group at time t; L solar,t is the solar radiation intensity in the area where the photovoltaic cell is located at time t; m is the derating coefficient of the photovoltaic cell; P pvn is the nominal power of the photovoltaic cell under standard test conditions; α is the power temperature coefficient; T C,t is the actual working temperature of the photovoltaic battery group at time t; T stc is the standard operating temperature of the photovoltaic cell group; T temp,t is the ambient temperature of the photovoltaic cell at time t; N oct is the nominal temperature of the photovoltaic cell group; P t tr is the transmission power of the interconnection line at time t; is the maximum transmission power limit of the interconnection line; is the transmission power from area a to a′ at time t; is the transmission power from area a′ to a at time t.

[0064] The results of the flexibility quantitative analysis of the coal-water-wind-solar wide-area power system are as follows:

[0065]

[0066]

[0067]

[0068]

[0069] in, is the operational flexibility margin of the power system in region a in the upward direction at time t; is the operational flexibility margin of the power system in region a in the downward direction at time t; is the total amount of flexibility resources provided by region a in the upward direction at time t; is the total amount of flexibility resources provided by region a in the downward direction at time t; is the system flexibility requirement of area a at time t; is the total amount of flexibility resources provided by coal-fired power units in region a in the upward direction at time t; is the total amount of flexibility resources provided by the hydropower units in region a in the upward direction at time t; The total amount of flexibility resources provided in the upward direction for flexible line transmission in area a at time t; The total amount of flexibility resources provided for the flexibility ramping product in area a at time t; is the total amount of flexibility resources provided by coal-fired power units in region a in the downward direction at time t; is the total amount of flexibility resources provided by the hydropower units in region a in the downward direction at time t; The total amount of flexible resources provided in the downward direction for flexible line transmission in area a at time t; N cp is the total number of coal-fired power units; n1 is the number of the coal-fired power unit; is the maximum technical output level of the n1th coal-fired power unit in region a; is the technical output level of the n1th coal-fired power unit in region a at time t; is the upward climbing capability of the n1th coal-fired power unit in region a; Δt is the scheduling interval time; is the minimum technical output level of the n1th coal-fired power unit in region a; is the climbing capacity of the n1th coal-fired power unit in area a in the downward direction; N hp is the total number of hydropower units; n2 is the hydropower unit number; is the maximum technical output level of the n2th hydropower unit in region a; is the technical output level of the n2th hydropower unit in region a at time t; is the climbing capacity of the n2th hydropower unit in area a in the upward direction; is the minimum technical output level of the n2th hydropower unit in region a; is the climbing ability of the n2th hydropower unit in area a in the downward direction; F t N is the system flexibility requirement at time t; F t 1 is the flexibility demand of system load at time t; F t wp is the flexibility demand of wind turbines in the system at time t; F t pv is the flexibility demand of the system PV unit at time t; ΔF t wp is the power fluctuation caused by the uncertain output of the wind turbine; ΔF t pv Power fluctuation caused by the uncertainty of the output of photovoltaic units; is the active power of the system load at time t+1; P t l is the active power of the system load at time t; is the active power of the system wind turbine at time t+1; P t wp is the active power of the system wind turbine at time t; is the active power of the system photovoltaic unit at time t+1; P t pv is the active power of the system photovoltaic unit at time t; P t wp,real is the actual output value of the system wind turbine at time t; P t wp,pre is the power forecast value of the system wind turbine at time t; is the power prediction error of the system wind turbine at time t; P t pv,real is the actual output value of the system photovoltaic unit at time t; P t pv,pre is the power prediction value of the system photovoltaic unit at time t; is the power prediction error of the system photovoltaic unit at time t.

[0070] The flexible supply and demand balancing working mode is specifically as follows:

[0071] When the total amount of flexibility resources is greater than or equal to the system flexibility demand, the electricity generated by wind turbines and photovoltaic units will be fully consumed first, and then hydropower units and coal-fired units will perform deep peak regulation, and finally flexible line transmission will be used to supplement it; when the total amount of flexibility resources is less than the system flexibility demand, hydropower units and coal-fired units will perform peak regulation first, and then wind turbines and photovoltaic units will supplement electricity, and finally flexible ramping products will be used to optimize operational flexibility; the flexibility resources include coal-fired units, hydropower units, flexible line transmission and flexible ramping products; the system flexibility demand includes wind turbines, photovoltaic units and power loads.

[0072] In this embodiment, the relationship between the power system flexibility resources and flexibility demand is as follows: Figure 2 As shown, on the basis of satisfying the balance of electricity and power, if the flexibility resource content is equal to the flexibility demand, the multi-energy wide-area power system will operate in a stable state and have the ability to respond promptly to the fluctuations of variables in the system; if the amount of flexibility resources is too much, the supply and demand balance will be in an oversaturated state, resulting in a waste of flexibility resources; if the amount of flexibility resources is insufficient, the system will be forced to perform operations such as load shedding, wind abandonment, and solar abandonment, resulting in resource waste and economic losses.

[0073] The flexibility supply and demand balancing working mode is: coal-fired power, hydropower units, flexible transmission lines and flexible climbing products with stable output conditions and peak-shaving capabilities in the coal-water-wind-light wide-area power system are defined as flexibility resources, and wind power, photovoltaic units and grid loads with uncertainty and volatility are defined as flexibility demand. On the basis of ensuring power balance, flexibility resources meet the needs of climbing, output uncertainty, peak-shaving, etc. When flexibility resources are abundant, the electricity generated by wind and light resources is fully absorbed first, and then hydropower and coal-fired power are deeply peak-shaving, and finally supplemented by flexible line transmission; when flexibility resources are less than demand, hydropower and coal-fired power are peak-shaving first, and then wind and light units supplement electricity, and finally the operation flexibility is optimized through flexible climbing products.

[0074] The objective function of the investment decision model is:

[0075]

[0076] Among them, min is the minimum function; C all is the total investment cost; is the investment and construction cost of area a in planning year y; is the resource maintenance cost of region a in planning year y; is the operating cost of region a under scenario s in planning year y; i is the category number of power generation resources; d is a 0-1 variable used to determine whether it is necessary to repay the previous debt, 1 for yes and 0 for no; K1 is the capital repatriation coefficient; is the unit capacity construction cost of the i-th power generation resource; P i,y,a is the planned capacity of the i-th generation resource in region a in the planning year y; is the construction cost per unit capacity of the transmission line; is the planned capacity of the transmission line in region a in the planning year y; K2 is the maintenance cost per unit capacity; is the built capacity of the i-th generation resource in region a in planning year y; is the new planned capacity of the i-th generation resource in region a in planning year y; is the capacity of the i-th retired power generation resource in region a in planning year y; P a old,lc is the built capacity of the transmission line in region a in planning year y; is the new planned capacity of the transmission lines in region a in planning year y.

[0077] The constraints of the investment decision model include: resource upper limit constraint, annual maximum load constraint, annual operating power constraint and market pricing constraint:

[0078]

[0079]

[0080]

[0081] Among them, P i,y,a is the planned capacity of the i-th generation resource in region a in the planning year y; is the maximum exploitable technical capacity of the i-th power generation resource in region a in planning year y; Plan the capacity for the transmission lines in region a in planning year y; is the planned capacity of the maximum transmission line in region a; i is the category number of the power generation resource; δ is the load growth rate; γ y,a is the system reserve capacity factor; is the maximum load power value in area a in planning year y; is the annual power generation of coal-fired power units in region a in the planning year y; is the annual power generation of hydropower units in region a in the planning year y; is the annual power generation of wind turbines in region a in the planning year y; is the annual power generation of the photovoltaic units in region a in the planning year y; is the annual operating power of the power load in area a in the planning year y; is the minimum clearing price; y,a,s,tis the clearing price of the flexible ramping product in area a at time t under scenario s in planning year y; is the maximum clearing price.

[0082] The objective function of the market clearing model is:

[0083]

[0084] Among them, max is the maximum value function; F is the social welfare value; is the power load and power resource clearing price of region a at time t under scenario s in planning year y; is the power value of the power load and power resources in area a at time t under scenario s in the planning year y; is the price of coal-fired power resources clearing in area a at time t under scenario s in planning year y; is the power value of coal-fired power generation unit power resources in area a at time t under scenario s in planning year y; is the clearing price of hydropower resources in region a at time t under scenario s in planning year y; is the power value of the hydropower unit power resources in area a at time t under scenario s in the planning year y; is the wind turbine power resource clearing price in area a at time t under scenario s in planning year y; is the power value of wind turbine power resources in area a at time t under scenario s in planning year y; is the price of clearing electricity resources of photovoltaic units in region a at time t under scenario s in planning year y; is the power value of the photovoltaic power resource in area a at time t under scenario s in the planning year y.

[0085] The constraints of the market clearing model include regional power balance constraints, unit operation constraints, network security constraints, flexible operation balance constraints and new energy output constraints:

[0086]

[0087]

[0088]

[0089] in, N is the power value of power load and power resources in area a at time t under scenario s in planning year y; cp is the total number of coal-fired power units; n1 is the number of the coal-fired power unit; is the power value of the n1th coal-fired power unit in area a at time t under scenario s in planning year y; N hpis the total number of hydropower units; n2 is the hydropower unit number; is the power value of the n2th hydropower unit in area a at time t under scenario s in planning year y; is the actual output value of wind turbine power resources in area a at time t under scenario s in planning year y; is the actual output value of the photovoltaic power resources in area a at time t under scenario s in the planning year y; is the power value of the flexible line transmission from area a′ to a at time t under scenario s in planning year y; is the minimum technical output level of the n1th coal-fired power unit; is the maximum technical output level of the n1th coal-fired power unit; Provide the power value of the flexible ramping product for the n1th coal-fired power unit in area a at time t under scenario s in planning year y; is the power value of the n1th coal-fired power unit in area a at time t-1 under scenario s in planning year y; is the upward climbing capability of the n1th coal-fired power unit; Δt is the scheduling interval time; is the climbing capacity of the n1th coal-fired power unit in the downward direction; is the minimum technical output level of the n2th hydropower unit; is the maximum technical output level of the n2th hydropower unit; is the power value of the n2th hydropower unit in area a at time t-1 under scenario s in planning year y; is the climbing ability of the n2th hydropower unit in the upward direction; is the climbing ability of the n2th hydropower unit in the downward direction; is the maximum transmission power limit of the interconnection line from area a′ to a; is the power value of the flexible line transmission from area a to a′ at time t under scenario s in planning year y; The total amount of flexibility resources provided in the upward direction for area a at time t under scenario s in planning year y; To plan the flexibility demand of system load in area a at time t under scenario s in year y; To plan the flexibility requirements of system wind turbines in area a at time t under scenario s in year y; is the flexibility demand of the system PV units in area a at time t under scenario s in planning year y; Pr{} is the probability of the event occurring; To plan the power fluctuation of wind turbines in area a at time t under scenario s in year y due to the uncertainty of output; To plan the power fluctuation of photovoltaic units due to the uncertainty of output in area a at time t under scenario s in year y; tis the total prediction error at time t; α1 and α2 are the probabilities of the event being true; is the wind turbine output prediction error at time t; is the output prediction error of the photovoltaic unit at time t; is the wind turbine output prediction error distribution coefficient at time t; is the distribution coefficient of the photovoltaic unit output prediction error at time t; N() is the normal distribution function; is the resource credible capacity factor of the wind turbine; is the resource credible capacity factor of the PV unit; It is the maximum technical output level of the wind turbine; It is the maximum technical output level of the photovoltaic unit.

[0090] The double-layer model optimization obtains a coal-water-wind-light wide-area power system planning scheme with improved flexibility, specifically: a Lagrangian function is established for the inner market clearing model, an MPEC model is established by obtaining KKT conditions and complementary relaxation constraints, and the double-layer model is converted into a single-layer model through MPEC model processing for optimization and solution, thereby obtaining a coal-water-wind-light wide-area power system planning scheme with improved flexibility.

[0091] In this embodiment, see Figure 3 As shown in the figure, an integrated internal and external double-layer optimization configuration model for the planning and operation of the coal-water-wind-light wide-area power system is established. The upper layer is the outer investment decision model of the coal-water-wind-light wide-area power system, which takes the minimum total system investment cost as the planning goal, performs single-objective optimization, and the optimization variables are coal-fired power construction capacity, hydropower construction capacity, wind power construction capacity, photovoltaic construction capacity, and transmission line construction capacity; the lower layer is the inner market clearing model of the coal-water-wind-light wide-area power system, which takes the maximum system social welfare as the optimization goal, and the optimization variables are coal-fired power output, hydropower output, wind power output, photovoltaic output, load winning quantity, power transmission, and flexible ramp product capacity. The outer investment decision model determines the investment and construction capacity of multiple types of power sources and the planned capacity of regional transmission lines. The optimized capacity results of various types of units are used as the boundary conditions of the inner power market clearing model, and the inner optimization is based on the results of the outer model for intraday optimization, optimizing the operation of the wide-area power system in a finer time scale. The capacity configuration plan of the coal-water-wind-light wide-area power system of the outer optimization model will directly affect the optimal target value of the inner model, and the system operating cost after the inner optimization is fed back to the outer layer to assist the outer optimization, thereby realizing the information transmission between the inner and outer layers to rationally plan the coal-water-wind-light wide-area power system.

[0092] Based on the above-mentioned method for optimizing the configuration of the coal-water-wind-light wide-area power system with improved flexibility, the natural condition data of a typical scenario in the southwest region is taken as an example, and simulation is performed based on the actual data of the southwest power grid for detailed description. The following examples are only used to more clearly illustrate the technical solution of the present invention, but not to limit the scope of the present invention.

[0093] The boundary conditions of the simulation model are: Electricity demand growth: The annual growth rate of electricity in the region is 5.4%. The installed capacity, maximum technical exploitable capacity, power generation system and other operating parameters of the southwest region are shown in the following table.

[0094] Table 1 Power installed capacity in each region in 2020

[0095]

[0096]

[0097] Table 2 Maximum technically exploitable resources

[0098]

[0099] Table 3 Unit capacity construction cost of units to be built

[0100]

[0101] Table 4 Operating parameters of each power supply

[0102]

[0103] This patent sets up four operating scenarios to verify the adaptability of the proposed optimized operating model. For the selection of typical days, firstly, the NASA meteorological data inversion analysis database is used to obtain natural data such as wind speed and solar radiation intensity in the region. After further processing, the distribution of wind and light resources in the southwest region is obtained. Secondly, the K-means clustering method is used to cluster the seasonal wind and light natural resources to obtain four typical day operating scenarios in spring, summer, autumn and winter.

[0104] According to the planning-operation integrated internal and external double-layer optimization model introduced above, the coal-water-wind-light wide-area power system is optimized, and the optimal planning and operation indicators are shown in Tables 6 and 7.

[0105] Table 6 Planning results

[0106]

[0107]

[0108] Table 7 Operation results

[0109]

[0110] Based on this planning scheme, the output of various resources in the coal-water-wind-light wide-area power system under typical scenarios is obtained as follows: Figure 4 As shown, it can be seen that the method proposed in this patent takes flexibility into consideration on the basis of multi-region interaction and adds flexible resource selection.

[0111] pass Figure 4 The output of the units shows that the output of coal-fired power is relatively stable, which is conducive to ensuring the stable operation of the units and extending the service life of the units. Combined with the data on abandoned power and load shedding of wind and solar resources, it is found that regional interaction can reasonably transfer excess power generation resources through power transmission, achieving the effect of flexible interaction among multiple regions.

Claims

1. A method for optimizing the configuration of a coal-water-wind-solar wide-area power system with improved flexibility, characterized in that: include: Establish a coal-water-wind-solar wide-area power system operation model; According to the coal-water-wind-solar wide-area power system operation model, conduct a quantitative analysis of the flexibility of the coal-water-wind-solar wide-area power system, and establish a wide-area power system operation model that takes flexibility into account and adopts a flexible supply and demand balance working mode; Taking the total investment cost of coal-water-wind-solar wide-area power system as the optimization target, an investment decision model is established; According to the constraints of the investment decision-making model, the market clearing model is established with the social welfare of the wide-area power system as the optimization goal; An integrated planning and operation model with two layers is established, with the outer layer being the investment decision-making model and the inner layer being the market clearing model. Through the optimization of the two-layer model, a planning scheme for the coal-water-wind-solar wide-area power system with improved flexibility is obtained.

2. The method for optimizing the configuration of a coal-water-wind-solar wide-area power system with improved flexibility according to claim 1, characterized in that: The coal-water-wind-light wide-area power system operation model includes a coal power output model, a hydropower output model, a wind power output model, a photovoltaic output model and a transmission line model: P hp,t =a hp ×q t 2 +b hp ×q t +c hp Among them, P t cp is the output power of the coal-fired power unit at time t; It is the minimum technical output level of coal-fired power units; P is the maximum technical output level of coal-fired power units; hp,t is the output power of the hydropower unit at time t; a hp , b hp and c hp The water energy-electricity conversion coefficient of the hydropower unit; q t is the power generation flow of the hydropower station at time t; v t is the wind speed of the fan hub at time t; v wind,t is the wind speed at the wind measuring point at time t; h is the hub height; h w is the height of the wind measuring point; P t wp is the output power of the wind turbine at time t; V in is the cut-in wind speed; V out is the cut-out wind speed; P wn is the rated power of the wind turbine; V r is the rated wind speed; P t pv is the output power of the photovoltaic battery group at time t; L solar,t is the solar radiation intensity in the area where the photovoltaic cell is located at time t; m is the derating coefficient of the photovoltaic cell; P pvn is the nominal power of the photovoltaic cell under standard test conditions; α is the power temperature coefficient; T C,t is the actual working temperature of the photovoltaic battery group at time t; T stc is the standard operating temperature of the photovoltaic cell group; T temp,t is the ambient temperature of the photovoltaic cell at time t; N oct is the nominal temperature of the photovoltaic cell group; P t tr is the transmission power of the interconnection line at time t; is the maximum transmission power limit of the interconnection line; is the transmission power from area a to a′ at time t; is the transmission power from area a′ to a at time t.

3. The method for optimizing the configuration of a coal-water-wind-solar wide-area power system with improved flexibility according to claim 1, characterized in that: The results of the flexibility quantitative analysis of the coal-water-wind-solar wide-area power system are as follows: F t N =F t l +F t wp +F t pv +ΔF t wp +ΔF t pv in, is the operational flexibility margin of the power system in region a in the upward direction at time t; is the operational flexibility margin of the power system in region a in the downward direction at time t; is the total amount of flexibility resources provided by region a in the upward direction at time t; is the total amount of flexibility resources provided by region a in the downward direction at time t; is the system flexibility requirement of area a at time t; is the total amount of flexibility resources provided by coal-fired power units in region a in the upward direction at time t; is the total amount of flexibility resources provided by the hydropower units in region a in the upward direction at time t; The total amount of flexibility resources provided in the upward direction for flexible line transmission in area a at time t; The total amount of flexibility resources provided for the flexibility ramping product in area a at time t; is the total amount of flexibility resources provided by coal-fired power units in region a in the downward direction at time t; is the total amount of flexibility resources provided by the hydropower units in region a in the downward direction at time t; The total amount of flexible resources provided in the downward direction for flexible line transmission in area a at time t; N cp is the total number of coal-fired power units; n1 is the number of the coal-fired power unit; is the maximum technical output level of the n1th coal-fired power unit in region a; is the technical output level of the n1th coal-fired power unit in region a at time t; is the upward climbing capability of the n1th coal-fired power unit in region a; Δt is the scheduling interval time; is the minimum technical output level of the n1th coal-fired power unit in region a; is the climbing capacity of the n1th coal-fired power unit in area a in the downward direction; N hp is the total number of hydropower units; n2 is the hydropower unit number; is the maximum technical output level of the n2th hydropower unit in region a; is the technical output level of the n2th hydropower unit in region a at time t; is the climbing capacity of the n2th hydropower unit in area a in the upward direction; is the minimum technical output level of the n2th hydropower unit in region a; is the climbing ability of the n2th hydropower unit in area a in the downward direction; F t N is the system flexibility requirement at time t; F t 1 is the flexibility demand of system load at time t; F t wp is the flexibility demand of wind turbines in the system at time t; F t pv is the flexibility demand of the system PV unit at time t; ΔF t wp is the power fluctuation caused by the uncertain output of the wind turbine; ΔF t pv Power fluctuation caused by the uncertainty of the output of photovoltaic units; is the active power of the system load at time t+1; P t l is the active power of the system load at time t; is the active power of the system wind turbine at time t+1; P t wp is the active power of the system wind turbine at time t; is the active power of the system photovoltaic unit at time t+1; P t pv is the active power of the system photovoltaic unit at time t; P t wp,real is the actual output value of the system wind turbine at time t; P t wp,pre is the power forecast value of the system wind turbine at time t; is the power prediction error of the system wind turbine at time t; P t pv,real is the actual output value of the system photovoltaic unit at time t; P t pv,pre is the power prediction value of the system photovoltaic unit at time t; is the power prediction error of the system photovoltaic unit at time t.

4. The method for optimizing the configuration of a coal-water-wind-solar wide-area power system with improved flexibility according to claim 1, characterized in that: The flexible supply and demand balancing working mode is specifically as follows: When the total amount of flexibility resources is greater than or equal to the system flexibility demand, the electricity generated by wind turbines and photovoltaic units will be fully consumed first, and then hydropower units and coal-fired units will perform deep peak regulation, and finally flexible line transmission will be used to supplement it; when the total amount of flexibility resources is less than the system flexibility demand, hydropower units and coal-fired units will perform peak regulation first, and then wind turbines and photovoltaic units will supplement electricity, and finally flexible ramping products will be used to optimize operational flexibility; the flexibility resources include coal-fired units, hydropower units, flexible line transmission and flexible ramping products; the system flexibility demand includes wind turbines, photovoltaic units and power loads.

5. The method for optimizing the configuration of a coal-water-wind-solar wide-area power system with improved flexibility according to claim 1, characterized in that: The objective function of the investment decision model is: Among them, min is the minimum function; C all is the total investment cost; is the investment and construction cost of area a in planning year y; is the resource maintenance cost of region a in planning year y; is the operating cost of region a under scenario s in planning year y; i is the category number of power generation resources; d is a 0-1 variable used to determine whether it is necessary to repay the previous debt, 1 for yes and 0 for no; K1 is the capital repatriation coefficient; is the unit capacity construction cost of the i-th power generation resource; P i,y,a is the planned capacity of the i-th generation resource in region a in the planning year y; is the construction cost per unit capacity of the transmission line; is the planned capacity of the transmission line in region a in the planning year y; K2 is the maintenance cost per unit capacity; is the built capacity of the i-th generation resource in region a in planning year y; is the new planned capacity of the i-th generation resource in region a in planning year y; is the capacity of the i-th retired generating resource in region a in planning year y; is the built capacity of the transmission line in region a in planning year y; is the new planned capacity of the transmission lines in region a in planning year y.

6. The method for optimizing the configuration of a coal-water-wind-solar wide-area power system with improved flexibility according to claim 1, characterized in that: The constraints of the investment decision model include: resource upper limit constraint, annual maximum load constraint, annual operating power constraint and market pricing constraint: Among them, P i,y,a is the planned capacity of the i-th generation resource in region a in the planning year y; is the maximum exploitable technical capacity of the i-th power generation resource in region a in planning year y; Plan the capacity for the transmission lines in region a in planning year y; is the planned capacity of the maximum transmission line in region a; i is the category number of the power generation resource; δ is the load growth rate; γ y,a is the system reserve capacity factor; is the maximum load power value in area a in planning year y; is the annual power generation of coal-fired power units in region a in the planning year y; is the annual power generation of hydropower units in region a in the planning year y; is the annual power generation of wind turbines in region a in the planning year y; is the annual power generation of the photovoltaic units in region a in the planning year y; is the annual operating power of the power load in area a in the planning year y; is the minimum clearing price; y,a,s,t is the clearing price of the flexible ramping product in area a at time t under scenario s in planning year y; is the maximum clearing price.

7. The method for optimizing the configuration of a coal-water-wind-solar wide-area power system with improved flexibility according to claim 1, characterized in that: The objective function of the market clearing model is: Among them, max is the maximum value function; F is the social welfare value; is the power load and power resource clearing price of region a at time t under scenario s in planning year y; is the power value of the power load and power resources in area a at time t under scenario s in the planning year y; is the price of coal-fired power resources clearing in area a at time t under scenario s in planning year y; is the power value of coal-fired power generation unit power resources in area a at time t under scenario s in planning year y; is the clearing price of hydropower resources in region a at time t under scenario s in planning year y; is the power value of the hydropower unit power resources in area a at time t under scenario s in the planning year y; is the wind turbine power resource clearing price in area a at time t under scenario s in planning year y; is the power value of wind turbine power resources in area a at time t under scenario s in planning year y; is the price of clearing electricity resources of photovoltaic units in region a at time t under scenario s in planning year y; is the power value of the photovoltaic power resource in area a at time t under scenario s in the planning year y.

8. The method for optimizing the configuration of a coal-water-wind-solar wide-area power system with improved flexibility according to claim 1, characterized in that: The constraints of the market clearing model include regional power balance constraints, unit operation constraints, network security constraints, flexible operation balance constraints and new energy output constraints: in, N is the power value of power load and power resources in area a at time t under scenario s in planning year y; cp is the total number of coal-fired power units; n1 is the number of the coal-fired power unit; is the power value of the n1th coal-fired power unit in area a at time t under scenario s in planning year y; N hp is the total number of hydropower units; n2 is the hydropower unit number; is the power value of the n2th hydropower unit in area a at time t under scenario s in planning year y; is the actual output value of wind turbine power resources in area a at time t under scenario s in planning year y; is the actual output value of the photovoltaic power resources in area a at time t under scenario s in the planning year y; is the power value of the flexible line transmission from area a′ to a at time t under scenario s in planning year y; is the minimum technical output level of the n1th coal-fired power unit; is the maximum technical output level of the n1th coal-fired power unit; Provide the power value of the flexible ramping product for the n1th coal-fired power unit in area a at time t under scenario s in planning year y; is the power value of the n1th coal-fired power unit in area a at time t-1 under scenario s in planning year y; is the upward climbing capability of the n1th coal-fired power unit; Δt is the scheduling interval time; is the climbing capacity of the n1th coal-fired power unit in the downward direction; is the minimum technical output level of the n2th hydropower unit; is the maximum technical output level of the n2th hydropower unit; is the power value of the n2th hydropower unit in area a at time t-1 under scenario s in planning year y; is the climbing ability of the n2th hydropower unit in the upward direction; is the climbing ability of the n2th hydropower unit in the downward direction; is the maximum transmission power limit of the interconnection line from area a′ to a; is the power value of the flexible line transmission from area a to a′ at time t under scenario s in planning year y; The total amount of flexibility resources provided in the upward direction for area a at time t under scenario s in planning year y; To plan the flexibility demand of system load in area a at time t under scenario s in year y; To plan the flexibility requirements of system wind turbines in area a at time t under scenario s in year y; is the flexibility demand of the system PV units in area a at time t under scenario s in planning year y; Pr{} is the probability of the event occurring; To plan the power fluctuation of wind turbines in area a at time t under scenario s in year y due to the uncertainty of output; To plan the power fluctuation of photovoltaic units due to the uncertainty of output in area a at time t under scenario s in year y; t is the total prediction error at time t; α1 and α2 are the probabilities of the event being true; is the wind turbine output prediction error at time t; is the output prediction error of the photovoltaic unit at time t; is the wind turbine output prediction error distribution coefficient at time t; is the distribution coefficient of the photovoltaic unit output prediction error at time t; N() is the normal distribution function; is the resource credible capacity factor of the wind turbine; is the resource credible capacity factor of the PV unit; It is the maximum technical output level of the wind turbine; It is the maximum technical output level of the photovoltaic unit.

9. The method for optimizing the configuration of a coal-water-wind-solar wide-area power system with improved flexibility according to claim 1, characterized in that: The double-layer model optimization obtains a coal-water-wind-light wide-area power system planning scheme with improved flexibility, specifically: a Lagrangian function is established for the inner market clearing model, an MPEC model is established by obtaining KKT conditions and complementary relaxation constraints, and the double-layer model is converted into a single-layer model through MPEC model processing for optimization and solution, thereby obtaining a coal-water-wind-light wide-area power system planning scheme with improved flexibility.

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