CN110930073B - Day-ahead scheduling method for wind-light-photo-thermal combined power generation system considering price type demand response - Google Patents
Day-ahead scheduling method for wind-light-photo-thermal combined power generation system considering price type demand response Download PDFInfo
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Abstract
The invention provides a day-ahead scheduling method of a wind-light-photo-thermal combined power generation system considering price type demand response, which is characterized in that wind power and photovoltaic are combined with TES of a CSP power station through an electricity-to-heat conversion link to construct a W-PV-CSP combined power generation system; secondly, a PDR model is introduced, a day-ahead optimization scheduling model of the W-PV-CSP combined power generation system considering the PDR is constructed, and finally, the wind power consumption of the system is promoted and the running cost of the system is reduced by coordinating and scheduling the output of each power station and the electricity purchasing quantity of an electric heating device. Has the advantages of scientific and reasonable structure, strong applicability, good effect and the like.
Description
Technical Field
The invention relates to a day-ahead scheduling method of a wind-light-photo-thermal combined power generation system considering price type demand response.
Background
In the prior art, various new energy sources are utilized to perform combined Power generation, including Wind Power (W), Photovoltaic (PV), photo-thermal (CSP), and the like. However, due to the restriction of natural attributes of wind and light, wind power and photovoltaic power generation have the characteristics of volatility and intermittence, and the safe operation of a power grid needs to be ensured by abandoning wind and light when necessary.
The CSP power station can store redundant electric quantity in a heat energy storage system (TES) in a form of heat energy, has certain energy time shifting characteristics, and can balance part of wind and light fluctuation power on site to realize energy complementation if the CSP power station is combined with wind power and photovoltaic power generation with high fluctuation. Therefore, the research on the wind-light-photo-thermal combined power generation system (hereinafter referred to as W-PV-CSP combined power generation system) and the day-ahead optimization scheduling method thereof have important theoretical and practical significance for improving the wind and light absorption capability of the power grid.
At present, optimization scheduling research on multiple new energy combined power generation has been advanced to a certain extent, mostly complementary characteristics between wind power generation and photovoltaic power generation are utilized, and system operation economy and wind-light absorption level are improved by coordinating and scheduling output between new energy power stations, but with the increase of types of new energy power stations, the traditional matching mode between the new energy power stations is single, and the operation characteristics of the new energy power stations cannot be fully utilized; meanwhile, the dispatching mode of the power grid does not fully utilize the resources on the demand side, and the research on the source load coordination dispatching method is not enough.
Disclosure of Invention
The invention aims to provide a day-ahead scheduling method of a wind-light-photo-thermal combined power generation system considering price type demand response, and aims to combine a wind-light power station and a photo-thermal power station heat storage system through an electricity-to-heat link, provide a wind-light-photo-thermal combined power generation system framework and principle, introduce the price type demand response, consider the uncertainty of the system under the premise of considering the optimal comprehensive cost, construct a day-ahead optimized scheduling model of the wind-light-photo-thermal combined power generation system considering the price type demand response, and finally reduce the operation cost of the system while promoting the wind power consumption of the system by coordinating and scheduling the output of each power station and the electricity purchasing quantity of an electric heating device.
The purpose of the invention is realized by the following technical scheme: a day-ahead scheduling method of a wind-light-photo-thermal combined power generation system considering price type demand response is characterized by comprising the steps of combining wind power and photovoltaic with TESs of a CSP power station through an electric-to-heat conversion link to construct a W-PV-CSP combined power generation system; secondly, a price-based demand response (PDR) model is introduced to construct a W-PV-CSP combined power generation system day-ahead optimization scheduling model considering PDR, and the method specifically comprises the following steps:
1) construction of W-PV-CSP combined power generation system
The CSP power station comprises an optical field, a TES and a thermodynamic cycle subsystem (PC), wherein the optical field absorbs solar energy and uses the absorbed energy to heat a heat-transfer fluid (HTF); the HTF and the TES can perform bidirectional energy transfer, meanwhile, the heat energy of the HTF can be used for heating water vapor to push a turbine set in a PC link to generate electric energy, the TES of the CSP power station is an energy storage link, and the CSP power station is combined with a wind power and photovoltaic power generation system to construct a W-PV-CSP combined power generation system, so that the fluctuation of wind and light output can be stabilized by using the energy time shifting characteristic of the CSP power station, and the wind and light absorption capacity is improved;
the W-PV-CSP combined power generation system converts part of wind power and photovoltaic power generation into heat energy through an electricity-to-heat link, the heat energy is used for heating heat storage molten salt in the TES, and redundant wind power and photovoltaic are converted into heat energy to be stored in the TES of the CSP power station when the load is at a valley; in the peak load period, the scheduling flexibility is enhanced along with the increase of the heat storage capacity of the CSP power station, and more peak regulation pressure can be shared for the thermal power generating unit;
2) PDR-considered W-PV-CSP combined power generation system day-ahead scheduling model
Price type demand response modeling
The PDR changes the electricity utilization mode of a user by formulating reasonable day-ahead real-time electricity price according to the psychological desire of a consumer, and usually adopts a price type demand elastic matrix E to express the influence of the electricity price change rate on the load change rate;
in the formula, T is the total scheduling duration and takes the value of 24; lambda [ alpha ] △q,t Is the load change rate at time t; lambda [ alpha ] △p,t The rate of change of electricity price at the time t; e is a price type demand elastic matrix, the main diagonal line of the price type demand elastic matrix is a self-elastic coefficient, the auxiliary diagonal line of the price type demand elastic matrix is a mutual elastic coefficient, and values of the self-elastic coefficient and the mutual elastic coefficient are-0.2 and 0.03 respectively;
after PDR, the load changes from the original load, and the amount of change is called the load response, and is calculated from the load change rate of equation (1) as equation (2):
Δq t ＝λ Δq,t P l,t (2)
in the formula, Δ q t Is the load response at time t, P l,t The load prediction value at the original time t is obtained;
the sum of the load response quantity and the original load quantity is the load demand quantity after PDR, and the formula (3) is used for solving:
in the formula
The predicted value is the load predicted value at the time t after the PDR and is substituted into the optimization scheduling model in the day before for solving;
day-ahead optimization scheduling model
Wind power, photovoltaic and CSP power stations in the constructed day-ahead optimization scheduling model adopt the operation mode of a W-PV-CSP combined power generation system, and a thermal power generating unit is independently operated as a base load power supply;
the objective function of the day-ahead optimization scheduling model is equation (4),
F＝min(C 1 +C 2 +C 3 +C 4 ) (4)
wherein F is an objective function of the day-ahead scheduling model, C 1 For the operating costs of thermal power units, C 2 For the operation of wind power, photovoltaic and CSP power stationsLine maintenance cost, C 3 Penalty cost for abandoning wind and light 4 For the electric heating operation cost, the day-ahead scheduling model simultaneously optimizes the system operation cost and the wind abandoning and light abandoning amount by taking the lowest comprehensive cost as a target;
wherein the operation cost of the thermal power generating unit comprises the maintenance cost and the start-stop cost of the thermal power generating unit, and is represented by the formula (5),
in the formula of U i,t For the start-up and shut-down variables, U, of the ith thermal power generating unit i,t A value of 0 represents that the thermal power generating unit stops operating; a. b and c are coal consumption cost coefficients of the thermal power generating unit respectively; p Gi,t Outputting a force value for the ith thermal power generating unit at the moment t; s i The start-stop cost of the ith thermal power generating unit is calculated;
operating cost C of wind power, photovoltaic and CSP power station 2 Including the maintenance cost of each station and the start-up cost of the CSP station, is given by equation (6),
C 2 ＝kf*P w,t +kg*P v,t +ks*U t,e P th,t e +(U t,e (1-U t-1,e ))S e (6)
in the formula, kf, kg and ks are respectively the operating costs of the wind power station, the photovoltaic station and the CSP power station; p w,t 、P v,t Respectively scheduling output of wind power and photovoltaic at the time t; p e th,t For the CSP power station at the time of t, the output, U t,e Representing the on-off variable, U, of CSP power stations t,e 0 represents shutdown, S e The start-stop cost of the CSP power station;
the wind and light abandoning penalty cost is the formula (7),
in the formula, KF and KG are wind and light abandoning punishment cost coefficients;
the air volume is the air volume discarded at the time t,
the amount of light lost at time t,
for the predicted value of the wind power output at the moment t,
the predicted value of the photovoltaic output at the time t is obtained;
the electric heating operation cost is the formula (8),
in the formula (I), the compound is shown in the specification,
respectively providing electricity for the wind power and the photovoltaic to the electricity-to-heat link, K r Is the electricity to heat cost coefficient;
the constraint conditions of the day-ahead optimization scheduling model are as follows:
the system power balance constraint is equation (9),
in the formula (I), the compound is shown in the specification,
the power supply amount of wind power and photovoltaic power to a power grid is respectively;
the operation constraint of the thermal power generating unit is (10),
in the formula, P Gi,min 、P Gi,max The minimum and maximum output of the thermal power generating unit during operation,
the ramp rate of the ith thermal power generating unit is TS and TO are respectively minimum shutdown time and minimum startup time;
the W-PV-CSP combined power generation system operation constraint comprises an internal energy flow constraint of the combined power generation system, which is expressed by a formula (11),
in the formula (I), the compound is shown in the specification,
solar heat absorbed by the light field of the CSP power station,
The heat released from the TES to the HTF for the CSP power plant can be used for the CSP power plant to generate power,
The heat stored by HTF to TES in CSP power station can be partially stored in TES in CSP power station,
Heat for power generation in the HTF of CSP power stations;
meanwhile, the heat charging power of the TES in the W-PV-CSP combined power generation system is composed of the heat collection power of a CSP power station and the heat power provided by a wind-solar power station through an electric-to-heat conversion loop; the heat release power is only transmitted to the HTF, and the heat storage systems of the wind power station, the photovoltaic station and the photo-thermal power station are combined through the equations (12) and (13);
in the formula
Charging power, eta, for the heat-storage link in For the efficiency of heat charging, eta e In order to improve the efficiency of the electric-to-heat link,
the heat release power, eta, of the heat storage link out The heat release efficiency is obtained;
the dispatching output of wind power and photovoltaic power in the W-PV-CSP combined power generation system comprises the sum of the electric quantity provided for a power grid and the electric quantity provided for an electric heating system:
the invention provides a day-ahead scheduling method of a wind-light-photo-thermal combined power generation system considering price type demand response, which is characterized in that wind power and photovoltaic are combined with TES of a CSP power station through an electricity-to-heat conversion link to construct a W-PV-CSP combined power generation system; secondly, a PDR model is introduced, a day-ahead optimization scheduling model of the W-PV-CSP combined power generation system considering the PDR is constructed, and finally, the wind power consumption of the system is promoted and the running cost of the system is reduced by coordinating and scheduling the output of each power station and the electricity purchasing quantity of an electric heating device. Has the advantages of scientific and reasonable structure, strong applicability, good effect and the like.
Drawings
FIG. 1 is a diagram of the operation of a W-PV-CSP cogeneration system;
FIG. 2 is a diagram of an IEEE-30 node architecture;
FIG. 3 is a graph of typical daily load, wind power predicted value, solar radiation index;
FIG. 4 is a schematic diagram of a system dispatch plan when dispatch model 1 is used;
FIG. 5 is a schematic diagram of a system dispatch plan using dispatch model 2;
FIG. 6 is a schematic diagram of a system dispatch plan when dispatch model 3 is employed;
FIG. 7 is a schematic diagram of electricity prices at various times after model 3 PDR;
FIG. 8 is a graph showing a comparison of CSP plant contribution under model 2 versus model 3 scheduling models;
fig. 9 is a schematic diagram comparing the heat storage capacity of the CSP power station under the scheduling models of model 2 and model 3.
Detailed Description
The present invention relates to a wind-light-photo-thermal combined power generation system day-ahead scheduling method considering price type demand response, and is further described with reference to the accompanying drawings and examples.
The invention relates to a day-ahead scheduling method of a wind-light-photo-thermal combined power generation system considering price type demand response, which comprises the steps of combining wind power and photovoltaic with TES of a CSP power station through an electric-to-heat conversion link to construct a W-PV-CSP combined power generation system; secondly, a price-based demand response (PDR) model is introduced to construct a W-PV-CSP combined power generation system day-ahead optimization scheduling model considering PDR, and the method specifically comprises the following steps:
1) construction of W-PV-CSP combined power generation system
The CSP power station comprises an optical field, a TES and a thermodynamic cycle subsystem (PC), wherein the optical field absorbs solar energy and uses the absorbed energy to heat a heat-transfer fluid (HTF); the HTF and the TES can perform bidirectional energy transfer, meanwhile, the heat energy of the HTF can be used for heating water vapor to push a turbine set in a PC link to generate electric energy, the TES of the CSP power station is an energy storage link, and the CSP power station is combined with a wind power and photovoltaic power generation system to construct a W-PV-CSP combined power generation system, so that the fluctuation of wind and light output can be stabilized by using the energy time shifting characteristic of the CSP power station, and the wind and light absorption capacity is improved;
the W-PV-CSP combined power generation system converts part of wind power and photovoltaic power generation into heat energy through an electricity-to-heat link, the heat energy is used for heating heat storage molten salt in the TES, and redundant wind power and photovoltaic are converted into heat energy and stored in the TES of the CSP power station when the load is at the valley; in the peak load period, the scheduling flexibility is enhanced along with the increase of the heat storage capacity of the CSP power station, and more peak regulation pressure can be shared for the thermal power generating unit;
2) PDR-considered W-PV-CSP combined power generation system day-ahead scheduling model
Price type demand response modeling
The PDR changes the electricity utilization mode of a user by formulating reasonable day-ahead real-time electricity price according to the psychological desire of a consumer, and usually adopts a price type demand elastic matrix E to express the influence of the electricity price change rate on the load change rate;
in the formula, T is the total scheduling duration, and the value is 24; lambda [ alpha ] △q,t Is the load change rate at time t; lambda [ alpha ] △p,t The rate of change of electricity price at the time t; e is a price type demand elastic matrix, the main diagonal line of the price type demand elastic matrix is a self-elastic coefficient, the auxiliary diagonal line of the price type demand elastic matrix is a mutual elastic coefficient, and values of the self-elastic coefficient and the mutual elastic coefficient are-0.2 and 0.03 respectively;
after PDR, the load changes from the original load, and the amount of change is called the load response, and is calculated from the load change rate of equation (1) as equation (2):
Δq t ＝λ Δq,t P l,t (2)
in the formula, Δ q t Is the load response at time t, P l,t The load predicted value at the original time t is obtained;
the sum of the load response and the original load is the load demand after passing through the PDR, and the formula (3) is used for solving:
in the formula
The load prediction value at the time t after the PDR is substituted into a day-ahead optimization scheduling model for solving;
day-ahead optimization scheduling model
The wind power, photovoltaic and CSP power stations in the constructed day-ahead optimization scheduling model adopt the operation mode of a W-PV-CSP combined power generation system, and the thermal power generating unit is independently operated as a base load power supply;
the objective function of the day-ahead optimization scheduling model is equation (4),
F＝min(C 1 +C 2 +C 3 +C 4 ) (4)
wherein F is an objective function of the day-ahead scheduling model, C 1 For the operating costs of thermal power units, C 2 For the operating maintenance costs of wind power, photovoltaic, CSP power stations, C 3 Punishment cost C for wind abandonment and light abandonment 4 For the electric heating operation cost, the day-ahead scheduling model simultaneously optimizes the system operation cost and the wind and light abandoning amount by taking the lowest comprehensive cost as a target;
wherein the operation cost of the thermal power generating unit comprises the maintenance cost and the start-stop cost of the thermal power generating unit, and is represented by the formula (5),
in the formula of U i,t For the start-up and shut-down variables, U, of the ith thermal power generating unit i,t A value of 0 represents that the thermal power generating unit stops operating; a. b and c are coal consumption cost coefficients of the thermal power generating unit respectively; p Gi,t Outputting a force value for the ith thermal power generating unit at the moment t; s i The start-stop cost of the ith thermal power generating unit is calculated;
operating cost C of wind power, photovoltaic and CSP power station 2 Including the maintenance cost of each station and the start-up cost of the CSP station, is given by equation (6),
C 2 ＝kf*P w,t +kg*P v,t +ks*U t,e P th,t e +(U t,e (1-U t-1,e ))S e (6)
in the formula, kf, kg and ks are respectively the operating costs of wind power, photovoltaic and CSP power stations; p w,t 、P v,t Respectively scheduling output of wind power and photovoltaic at the time t; p is e th,t For the CSP power station at the time of t, the output, U t,e Representing the on-off variable, U, of CSP power stations t,e 0 represents shutdown, S e The start-stop cost of the CSP power station;
the wind and light abandoning penalty cost is the formula (7),
in the formula, KF and KG are wind and light abandoning punishment cost coefficients;
the air volume is the air volume discarded at the time t,
the amount of light rejected at time t,
for the predicted value of the wind power output at the moment t,
the predicted value of the photovoltaic output at the time t is obtained;
the electric heating operation cost is the formula (8),
in the formula (I), the compound is shown in the specification,
respectively providing electricity for the electricity-to-heat link for wind power and photovoltaic power, K r Is the electricity to heat cost coefficient;
the constraint conditions of the day-ahead optimization scheduling model are as follows:
the system power balance constraint is equation (9),
in the formula (I), the compound is shown in the specification,
the power supply amount of wind power and photovoltaic power to a power grid is respectively;
the operation constraint of the thermal power generating unit is (10),
in the formula, P Gi,min 、P Gi,max The minimum and maximum output of the thermal power generating unit during operation,
the ramp rate of the ith thermal power generating unit is TS and TO are respectively minimum shutdown time and minimum startup time;
the W-PV-CSP combined power generation system operation constraint comprises an internal energy flow constraint of the combined power generation system, which is expressed by a formula (11),
in the formula (I), the compound is shown in the specification,
solar heat absorbed by the light field of the CSP power station,
The heat released from the TES to the HTF for the CSP power plant can be used for the CSP power plant to generate power,
The heat stored by HTF to TES in CSP power station can be partially stored in TES in CSP power station,
Heat for power generation in the HTF of the CSP plant;
meanwhile, the heat charging power of the TES in the W-PV-CSP combined power generation system is composed of the heat collection power of a CSP power station and the heat power provided by a wind-solar power station through an electric-to-heat loop; the heat release power is only transmitted to the HTF, and the heat storage systems of the wind power station, the photovoltaic station and the photo-thermal power station are combined through the equations (12) and (13);
in the formula
Charging power, eta, for the heat-storage link in For the efficiency of heat charging, eta e In order to improve the efficiency of the electric-to-heat link,
the heat release power, eta, of the heat storage link out The heat release efficiency is obtained;
the dispatching output of wind power and photovoltaic power in the W-PV-CSP combined power generation system comprises the sum of the electric quantity provided for a power grid and the electric quantity provided for an electric heating system:
referring to fig. 1-2, in the embodiment, a certain grid actual load, wind power output, photovoltaic output and solar radiation index are used as a basis, example simulation is performed in an IEEE-30 node system, and three different scheduling models are set for comparison, so that the validity of the model constructed by the method is verified.
Example the calculation conditions are illustrated below:
1) the IEEE-30 node system comprises 3 thermal power generating units, wherein the capacities of the thermal power generating units are respectively 200MW, 35MW and 30MW, a 200MW wind power plant, a 100MW photovoltaic power station and a 100MW CSP power station.
2) The three set comparison models are respectively as follows:
model 1: the traditional day-ahead economic dispatching model does not consider PDR nor adopt a W-PV-CSP combined power generation system;
model 2: considering PDR but not adopting a day-ahead optimization scheduling model of the W-PV-CSP combined power generation system;
model 3: by adopting the method, the PDR and W-PV-CSP combined power generation system is considered to optimize the scheduling model day ahead.
Under the above calculation conditions, the optimal scheduling result of the combined power generation system by applying the method of the present invention is as follows:
1. and the effectiveness of a W-PV-CSP combined power generation system day-ahead scheduling model of the PDR on reducing wind curtailment and light curtailment of the system is considered.
Fig. 3 is a typical daily load, a wind power predicted value and a solar radiation index curve, fig. 4, fig. 5 and fig. 6 are respectively system scheduling planned values of model 1, model 2 and model 3, fig. 7 is a day-ahead real-time electricity price after passing through the PDR, the electricity price before the PDR is a fixed 400 yuan/MW, as can be seen by the analysis combining fig. 3 and fig. 4: when the demand response is not considered, the wind power output is in a period of high wind power output when the time is 0-8, and the load demand is low at the moment, the wind power has the characteristic of reverse peak regulation, so that the wind abandon is serious in the period; meanwhile, the solar radiation index is higher at 12-14, the photovoltaic output is increased, but the light abandon is generated due to insufficient load demand at the moment.
It can be seen from the electricity price formulation of fig. 7 that after the PDR is taken into account, the electricity price after 15 hours is increased, while the electricity price is relatively lower at 0-8 hours when the wind power output is higher and at 12-14 hours when the photovoltaic output is higher. Meanwhile, as can be seen from the comparison between fig. 5 and fig. 6: the load demand amounts of the model 2 and the model 3 are increased as compared with the model 1 at 0 to 8 and 12 to 14, so that the amount of wind curtailment and light curtailment generated by the limitation of the load demand amount in the model 1 is reduced; after 15 hours, the load demand of the model 1 is reduced compared with that of the model 3 in the model 2, and the output of the thermal power generating unit is reduced accordingly.
The price type demand response can be effectively combined with the source load two sides for scheduling, and the wind and light absorption capacity is improved. However, as can be seen from comparison between fig. 6 and fig. 7, in the northwest area, under the higher wind curtailment and light curtailment levels, the load amount can only be adjusted in a small range by using the day-ahead optimal scheduling of the price type demand response, and the basic trend of the load cannot be changed, so that the wind curtailment and light curtailment phenomena are still relatively serious.
In order to further solve the problems of wind abandoning and light abandoning in northwest regions, the model 3 adopted by the method adopts a W-PV-CSP combined power generation system operation mode for the wind power, photovoltaic and CSP power station on the basis of the model 2, and the wind abandoning and the light abandoning in the model 2 can be converted into heat to be stored in a TES system of the CSP power station through an electricity-to-heat link, so that more heat sources are provided for the CSP power station. The amount of wind curtailment of model 3 is further reduced compared to model 2.
In order to verify that the model provided by the method can fully utilize the heat storage system of the CSP power station, the scheduling flexibility of the CSP power station is improved, and the output of the model 2 and the model 3CSP power station and the internal heat storage capacity are compared and analyzed. Fig. 8 is a comparison of model 2 and model 3CSP power station outputs, and fig. 9 is a comparison of model 2 and model 3CSP power station heat storage capacities. When analyzing with reference to fig. 8 and 9, it can be seen that: because an electricity-to-heat conversion link is added, the W-PV-CSP combined power generation system of the model 3 converts the abandoned wind and abandoned light into heat and stores the heat in the TES of the CSP power station, so that the CSP power station heat storage capacity of the model 3 is more than that of the model 2 at most moments in a day, the output power which can be provided by the CSP power station of the model 3 in a load peak period is higher than that of the model 2, and the peak regulation pressure of a thermal power unit is reduced.
2. Verifying effectiveness of the day-ahead scheduling model constructed by the method on reducing system cost
Table 1 shows specific values of thermal power unit cost, wind abandon and light abandon punishment cost, wind power and photovoltaic operation cost, CSP power station operation cost, electricity-to-heat loop operation cost, total cost, and total wind abandon and light abandon rate, which are obtained by the three models.
TABLE 1
The data in the table show that the model 3 has the lowest penalty cost of wind abandonment and light abandonment due to the addition of an electric-to-heat conversion link, and the total wind abandonment and light abandonment rate is reduced by 7.39 percent and 5.36 percent compared with the model 1 and the model 2.
Meanwhile, as the W-PV-CSP combined power generation system is adopted in the model 3, the heat sources of the CSP power station are increased and the schedulability is improved while wind and light abandonment is absorbed, so that the cost of the thermal power unit participating in peak regulation in the system is reduced. In combination, compared with the model 1 and the model 2, the comprehensive cost of the model 3 is reduced by 15.4% and 7.6% respectively.
Through the analysis of the above examples, the effectiveness of the day-ahead scheduling strategy provided by the invention on improving the wind and light absorption capability and reducing the comprehensive cost of the system in a typical day is verified.
3. The effectiveness of the day-ahead scheduling model constructed by the method is verified under different levels of wind curtailment and light curtailment.
In order to analyze the effect of the model provided by the text under different abandoned wind and abandoned light levels, the abandoned wind and abandoned light levels of the system when the traditional day-ahead economic dispatching model is adopted are divided into the following three scenes by taking the average abandoned wind and abandoned light rate in the whole country as the reference:
1) low wind and light abandon level: the total wind and light rejection rate is between 0 and 5 percent;
2) medium wind abandoning and light abandoning levels: the total light rejection and the total wind rejection are between 5 and 10 percent;
3) high wind and light abandoning level: the total light rejection and the total wind rejection are between 10 and 15 percent.
Table 2 shows the total cost and wind-solar energy absorption of three models at three wind and light rejection levels.
TABLE 2
As can be seen from Table 2, the optimization effect of the model 3 becomes more and more obvious as the total wind curtailment and the light curtailment rate are improved.
In the aspect of comprehensive cost, under the condition of 0-5% of total wind curtailment rate, the model 3 is respectively reduced by 8.1% and 0.13% compared with the model 1 and the model 2; under the total wind curtailment rate of 5-10%, the model 3 is respectively reduced by 15.4% and 7.6% compared with the model 1 and the model 2; and when the total wind curtailment rate reaches 10% -15%, the comprehensive cost of the model 3 is reduced by 21.4% and 17.7% compared with that of the model 1 and the model 2.
The above results are mainly that when the wind abandoning and light abandoning levels are low, the punishment cost of wind abandoning and light abandoning of the model 1 and the model 2 is low, and the wind abandoning and light abandoning quantity which can be utilized by the W-PV-CSP combined power generation system is also relatively low, so that the optimization effect of the model 3 is not obvious; along with the improvement of the levels of abandoned wind and abandoned light, the quantity of abandoned wind and abandoned light available in the W-PV-CSP combined power generation system is increased, the number of heat sources of CSP power stations is increased, the scheduling flexibility is improved, and the effects of reducing the punishment cost of abandoned wind and abandoned light of the system and the peak regulation cost of a thermal power generating unit are more obvious.
Meanwhile, in the wind and light absorption rate, the total wind abandoning rate and the light abandoning rate of the model 3 are respectively improved by 2.15%, 7.42% and 8.47% compared with the model 1 from low to high; the improvement is 1.38%, 5.36% and 7.87% respectively compared with the model 2.
The computing conditions, diagrams and the like in the embodiments of the present invention are used for further description, are not exhaustive, and do not limit the scope of the claims, and those skilled in the art can conceive other substantially equivalent alternatives without inventive step in light of the teachings of the embodiments of the present invention, which are within the scope of the present invention.
Claims (1)
1. A day-ahead scheduling method of a wind-light-photo-thermal combined power generation system considering price type demand response is characterized by comprising the steps of combining wind power and photovoltaic with TESs of a CSP power station through an electric conversion heating link to construct a W-PV-CSP combined power generation system; secondly, a PDR-considered W-PV-CSP combined power generation system day-ahead optimization scheduling model is constructed by introducing a price type demand response PDR model, and the method specifically comprises the following steps:
1) constructing a W-PV-CSP combined power generation system
The CSP power station comprises an optical field, a TES and a thermodynamic cycle subsystem PC, wherein the optical field absorbs solar energy and uses the absorbed energy to heat a heat-conducting working medium HTF; the HTF and the TES can perform bidirectional energy transfer, meanwhile, the heat energy of the HTF can be used for heating water vapor to push a turbine set in a PC link to generate electric energy, the TES of the CSP power station is an energy storage link, and the CSP power station is combined with a wind power and photovoltaic power generation system to construct a W-PV-CSP combined power generation system, so that the fluctuation of wind and light output can be stabilized by using the energy time shifting characteristic of the CSP power station, and the wind and light absorption capacity is improved;
the W-PV-CSP combined power generation system converts part of wind power and photovoltaic power generation into heat energy through an electricity-to-heat link, the heat energy is used for heating heat storage molten salt in the TES, and redundant wind power and photovoltaic are converted into heat energy and stored in the TES of the CSP power station when the load is at the valley; in the peak load period, the scheduling flexibility is enhanced along with the increase of the heat storage capacity of the CSP power station, and more peak regulation pressure can be shared for the thermal power generating unit;
2) PDR-considered W-PV-CSP combined power generation system day-ahead scheduling model
Price type demand response modeling
The PDR changes the electricity utilization mode of a user by formulating reasonable day-ahead real-time electricity price according to the psychological willingness of a consumer, and a price type demand elastic matrix E is adopted to express the influence of the electricity price change rate on the load change rate;
in the formula, T is the total scheduling duration and takes the value of 24; lambda [ alpha ] △q,t Is the load change rate at time t; lambda △p,t The rate of change of electricity price at the time t; e is a price type demand elastic matrix, the main diagonal line of the price type demand elastic matrix is a self-elastic coefficient, the auxiliary diagonal line of the price type demand elastic matrix is a mutual elastic coefficient, and values of the self-elastic coefficient and the mutual elastic coefficient are-0.2 and 0.03 respectively;
after PDR, the load changes from the original load, and the amount of change is referred to as the load response, and is calculated from the load change rate of equation (1) as equation (2):
Δq t ＝λ Δq,t P l,t (2)
in the formula, Δ q t Is the load response at time t, P l,t The load prediction value at the original time t is obtained;
the sum of the load response quantity and the original load quantity is the load demand quantity after PDR, and the formula (3) is used for solving:
in the formula
The predicted value is the load predicted value at the time t after the PDR and is substituted into the optimization scheduling model in the day before for solving;
day-ahead optimization scheduling model
Wind power, photovoltaic and CSP power stations in the constructed day-ahead optimization scheduling model adopt the operation mode of a W-PV-CSP combined power generation system, and a thermal power generating unit is independently operated as a base load power supply;
the objective function of the day-ahead optimization scheduling model is equation (4),
F＝min(C 1 +C 2 +C 3 +C 4 ) (4)
wherein F is an objective function of a day-ahead scheduling model, C 1 For the operating costs of thermal power units, C 2 For the operating maintenance costs of wind power, photovoltaic, CSP power stations, C 3 Penalty cost for abandoning wind and light, C 4 For the electric heating operation cost, the day-ahead scheduling model simultaneously optimizes the system operation cost and the wind and light abandoning amount by taking the lowest comprehensive cost as a target;
wherein the operation cost of the thermal power generating unit comprises the maintenance cost and the start-stop cost of the thermal power generating unit, and is represented by the formula (5),
in the formula of U i,t For the start-up and shut-down variables, U, of the ith thermal power generating unit i,t A value of 0 represents that the thermal power generating unit stops operating; a. b and c are coal consumption cost coefficients of the thermal power generating unit respectively; p Gi,t Outputting a force value for the ith thermal power generating unit at the moment t; s. the i The start-stop cost of the ith thermal power generating unit is calculated;
operating cost C of wind power, photovoltaic and CSP power station 2 Including the maintenance cost of each station and the start-up cost of the CSP station, is given by equation (6),
C 2 ＝kf*P w,t +kg*P v,t +ks*U t,e P th,t e +(U t,e (1-U t-1,e ))S e (6)
in the formula, kf, kg and ks are respectively the operating costs of wind power, photovoltaic and CSP power stations; p w,t 、P v,t Respectively scheduling output of wind power and photovoltaic at the time t; p e th,t Output, U, for the scheduling of the CSP power station at time t t,e Representing the on-off variable, U, of CSP power stations t,e 0 represents shutdown, S e The start-stop cost of the CSP power station;
the wind and light abandoning penalty cost is the formula (7),
in the formula, KF and KG are wind and light abandoning punishment cost coefficients;
the air volume is the air volume discarded at the time t,
the amount of light lost at time t,
for the predicted value of the wind power output at the moment t,
the predicted value of the photovoltaic output at the time t is obtained;
the electric heating operation cost is expressed by the formula (8),
C 4 ＝(P t th,W-H +P t th,V-H )*Kr (8)
in the formula, P t th,W-H 、P t th,V-H Respectively providing electricity for the electricity-to-heat link for wind power and photovoltaic power, K r Is the electricity to heat cost coefficient;
the constraint conditions of the day-ahead optimization scheduling model are as follows:
the system power balance constraint is equation (9),
in the formula (I), the compound is shown in the specification,
the power supply amount of wind power and photovoltaic power to a power grid is respectively;
the operation constraint of the thermal power generating unit is (10),
in the formula, P Gi,min 、P Gi,max The minimum and maximum output of the thermal power generating unit during operation,
the ramp rate of the ith thermal power generating unit is TS and TO are respectively minimum shutdown time and minimum startup time;
the W-PV-CSP combined power generation system operation constraint comprises the combined power generation system internal energy flow constraint, which is expressed by a formula (11),
P t th,S-H +P t th,T-H ＝P t th,H-T +u t C P SU th +P t th,H-P (11)
in the formula, P t th,S-H Solar heat P absorbed by CSP power station light field t th,T-H The heat released by the TES to the HTF for the CSP plant, part of which is used for CSP plant power generation, P t th,H-T Heat stored to the TES by the HTF in the CSP power station, this part of the heat being stored in the TES of the CSP power station, P t th,H-P Heat for power generation in the HTF of CSP power stations;
meanwhile, the heat charging power of the TES in the W-PV-CSP combined power generation system is composed of the heat collection power of a CSP power station and the heat power provided by a wind-solar power station through an electric-to-heat conversion loop; the heat release power is only transmitted to the HTF, and the heat storage systems of the wind power station, the photovoltaic station and the photo-thermal power station are combined through the equations (12) and (13);
P t in ＝(P t th,H-T +(P t th,W-H +P t th,V-H )η e )η in (12)
P t out ＝P t th,T-H /η out (13)
in the formula P t in Charging power, eta, for the heat-storage link in For the efficiency of heat charging, eta e For the efficiency of the electrothermal link, P t out The heat release power, eta, of the heat storage link out The heat release efficiency is obtained;
the dispatching output of wind power and photovoltaic power in the W-PV-CSP combined power generation system comprises the sum of the electric quantity provided for a power grid and the electric quantity provided for an electric heating system:
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