CN112491087B - Wind-solar-storage independent micro-grid economic optimization method based on demand side response - Google Patents
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Abstract
The invention discloses a wind-solar-storage independent micro-grid economic optimization method based on demand side response, which comprises the following steps of: establishing an output power decomposition formula of a solar panel, an output power decomposition formula of a wind turbine and a charge and discharge power expression formula of an energy storage system; obtaining a k-th equipment component total cost expression of the wind-solar-storage independent micro-grid by adopting demand side response planning; establishing a capital recovery coefficient expression; obtaining the annual initial cost of the kth equipment component, the annual reset cost of the kth equipment component and the residual value of the kth equipment component; obtaining the annual unit cost of equipment components in the wind-solar-storage independent micro-grid; obtaining the net current cost of the kth equipment component of the wind-solar-storage independent micro-grid; and analyzing the net current cost of the kth equipment assembly of the energy storage microgrid, and verifying the effectiveness of the energy storage optimization method adopting the demand side response planning. The invention applies DR planning to economic optimization of the wind-solar-storage micro-grid and solves the problem of energy generation in the independent micro-grid.
Description
Technical Field
The invention relates to a wind-solar-storage independent micro-grid economic optimization method based on demand side response. Cost reduction is realized by reducing or eliminating unbalance between a power generation side and a power consumption side, and the economy of the wind-solar energy storage independent micro-grid is improved.
Background
Wind and solar energy are considered important renewable resources. The energy produced by these resources varies over time and is generally not satisfactory for demand side use. This mismatch phenomenon increases the energy storage capacity of the off-grid system. In addition, if a Photovoltaic (PV) system or a Wind Turbine (WT) is used independently, the system scale and the investment cost will increase. The hybrid use of these energy sources can improve the reliability of the system and can reduce the investment cost and the capacity of the microgrid energy storage system.
In a wind-solar-storage independent microgrid grid-connected system, a demand side response (DR) is often required to reduce the operation cost. DR is a method of changing consumption patterns for changing electricity prices or changing consumption costs for reducing consumption.
Disclosure of Invention
The invention aims to provide a wind-solar-storage independent micro-grid economic optimization method based on demand side response, and particularly relates to a DR planning method applied to wind-solar-storage micro-grid economic optimization, which solves the problem of energy generation in an independent micro-grid by using DR. Cost reduction is realized by reducing or eliminating imbalance between a power generation side and a power consumption side, a load time domain is transferred or scheduling planning is carried out on the load, and the economy of the wind-solar-storage independent micro-grid is improved.
The invention is realized by adopting the following technical scheme:
a wind-solar-storage independent micro-grid economic optimization method based on demand side response comprises the following steps:
1) Establishing an output power decomposition formula of a solar panel, an output power decomposition formula of a wind turbine and a charge and discharge power expression formula of an energy storage system;
2) Obtaining a k-th equipment component total cost expression of the wind-solar storage independent micro-grid by adopting a demand side response planning according to the output power decomposition formula of the solar panel, the output power decomposition formula of the wind turbine and the charge-discharge power expression of the energy storage system in the step 1);
3) Converting the initial cost in the k-th equipment component total cost expression of the wind-solar-storage independent micro-grid in the step 2) into annual cost, and establishing a capital recovery coefficient expression;
4) Obtaining the annual initial cost of the kth equipment component, the annual reset cost of the kth equipment component and the residual value of the kth equipment component according to the capital recovery coefficient expression in the step 3);
5) Obtaining the annual unit cost of the equipment components in the wind-solar-storage independent micro-grid according to the annual initial cost of the kth equipment component, the annual reset cost of the kth equipment component and the residual value of the kth equipment component in the step 4);
6) Obtaining the net current cost of the kth equipment assembly of the wind-solar storage independent microgrid according to the annual unit cost of the equipment assemblies in the energy storage microgrid in the step 5);
7) And 6) analyzing the net current cost of the kth equipment assembly of the energy storage microgrid in the step 6), and verifying the effectiveness of the energy storage optimization method adopting the demand side response planning.
The further improvement of the invention is that the specific implementation method of the step 1) is as follows: establish solar cell panel output power decomposition formula, solar cell panel PPV's output direct current power depends on solar radiation intensity, absorption capacity, panel area and battery temperature, and solar cell panel output power decomposition formula is:
wherein: g t (t)(W/m 2 ) Is the incident power of the radiation, P, perpendicular to the array surface pv-rated Is the rated power, eta, of the panel under standard test STC conditions pv Is the power reduction coefficient, T, of the solar cell panel C,STC Is the temperature of the battery at STC, beta T Is the photovoltaic temperature coefficient, T C Is the battery temperature at run time, expressed as:
wherein: NOCT is the normal operating battery temperature, T amb Is the ambient temperature; the output power of a wind turbine is a function of the wind speed at the hub height of the fan, and is decomposed into:
wherein: v (m/s), v r 、v cut-in And v and cut-out respectively, the height of the wind turbine hub, the rated rotating speed, the cut-in speed and the cut-off rotating speed, P r Representing the output power at the rated rotating speed; the charge and discharge power expression of the energy storage system is as follows: p is B (t)＝P WT (t)+P PV (t)-P L (t)/η inv (ii) a Wherein: p L Is the total electrical load at time t, η inv Is the inverter efficiency, if P B =0 then the battery pack is neither charged nor discharged; if P is B And > 0, the battery pack is charged due to the excess power generated by the microgrid.
The further improvement of the invention is that the specific implementation method of the step 2) is as follows: according to the step 1), obtaining a k-th equipment component total cost expression of the wind-solar storage independent micro-grid by adopting demand side response planning according to the solar panel output power decomposition type, the wind turbine output power decomposition type and the energy storage system charge-discharge power expression: TUC k ＝IC k +Rep k +M k -RV k (ii) a Wherein: IC (integrated circuit) k Initial costs for procurement, installation and debugging; rep (Rep) k Cost for reset; m k For operating maintenance costs, RV k Is the remaining value.
The further improvement of the invention is that the specific implementation method of the step 3) comprises the following steps: converting the initial cost in the k-th equipment component total cost expression of the wind-light storage independent micro-grid in the step 2) into the yearCost, establishing a capital recovery coefficient expression:
wherein: i is interest rate, n is system life cycle, n is k Is the life cycle of the kth energy storage device.
A further improvement of the invention is that step 4) is embodied in such a way that the annual initial cost of the kth equipment component is obtained from the expression for the capital recovery factor of step 3): AIC k ＝IC k X CRF (i, n), annual reset cost of kth equipment component:
and the remaining value of the kth equipment component:
the further improvement of the invention is that the concrete implementation method of the step 5) is as follows: obtaining the annual unit cost of the equipment components in the wind-solar-storage independent micro-grid according to the initial annual cost of the kth equipment component, the annual reset cost of the kth equipment component and the residual value of the kth equipment component in the step 4): ATUC k ＝AIC k +APep k +M k -ARV k 。
The further improvement of the invention is that the specific implementation method of the step 6) is as follows: obtaining the net cost of the kth equipment component of the wind-solar energy storage independent microgrid according to the annual unit cost of the equipment components in the energy storage microgrid in the step 5): NPCU k ＝ATUC k /CRF(i,n)。
The further improvement of the invention is that the specific implementation method of the step 7) is as follows: and 6) analyzing the net current cost of the kth equipment assembly of the energy storage microgrid in the step 6), and verifying the effectiveness of the energy storage optimization method adopting the demand side response planning.
Compared with the prior art, the invention has at least the following beneficial technical effects:
1. the invention provides a wind-solar-storage independent micro-grid economic optimization method based on demand side response, DR planning is applied to wind-solar-storage micro-grid economic optimization, and the problem of energy generation in an independent micro-grid is solved.
2. According to the wind-solar-storage independent micro-grid, the cost reduction of the wind-solar-storage independent micro-grid is realized by reducing or eliminating the unbalance between the power generation side and the power consumption side, the load time domain is transferred or the load is scheduled and planned, and the economy of the wind-solar-storage independent micro-grid is improved.
Drawings
FIG. 1 is a schematic diagram of a photovoltaic/wind energy/battery hybrid microgrid system;
FIG. 2 is a schematic diagram of a microgrid economic optimization process;
FIG. 3 is a graph of generating side power and consuming side power without DR;
fig. 4 is a graph showing power generation side power and power consumption side power in the presence of DR.
Detailed Description
The technical scheme of the invention is further described in detail through the attached drawings.
As shown in fig. 1, in the wind-photovoltaic-storage independent microgrid, PV and WT are used as voltage sources, and the energy storage system (battery) is used as an electric energy storage device. And the wind-solar-storage independent micro-grid carries out load scheduling through intelligent system management. The intelligent system utilizes DR to reduce or eliminate imbalance between the generation side and the consumption side, with the backup load being used to consume excess load of the light-storage independent microgrid.
The DR planning configuration of the wind-solar-storage independent micro-grid needs to stipulate the operation times of schedulable loads in a specified time period, and the number of unallocated and insufficient energy sources. Constraints include operational and physical limitations of the components, energy balance, capacity limitations, equipment capabilities, and battery constraints.
The invention provides a new DR mode, and the phenomenon of mismatching between the power generation side and the power consumption side is reduced or eliminated by planning the schedulable load through the DR mode.
The solar cell panel directly converts sunlight into electric energy. The output dc power of a solar cell panel (PPV) depends on the solar radiation intensity, absorption capacity, panel area and cell temperature, as shown in equation (1).
In formula (1): g t (t)(W/m 2 ) Is the incident power of the radiation, P, perpendicular to the array surface pv-rated Is the rated power, eta, of the panel under Standard Test (STC) conditions pv Is the power reduction coefficient (%) of the solar cell panel, T C,STC Is the temperature of the battery at STC, beta T Is the photovoltaic temperature coefficient, T C Is the battery temperature during operation, and specifically solves the following formula (2):
in the formula (2): NOCT is the normal operating battery temperature, T amb Is the ambient temperature.
The output power of a wind turbine is a function of the wind speed at the hub height of the wind turbine, and is expressed as:
in formula (3): v (m/s), v r 、v cut-in And v and cut-out the wind turbine hub height, the rated rotating speed, the cut-in speed and the cut-off rotating speed are respectively. P is r Representing the output power at nominal speed.
The energy storage system is used for balancing supply and demand, and the batteries can be used as the energy storage system in the micro-grid. The charging or discharging of the battery can be determined according to the power generation and power consumption, and the input power of the battery can be positive or negative, which depends on the charging and discharging state of the battery pack, as shown in formula (4).
P B (t)＝P WT (t)+P PV (t)-P L (t)/η inv (4)
In formula (4): p is L Is the total electrical load at time t, η inv Is the inverter efficiency. If P is B =0 then the battery pack is neither charged nor discharged; if P is B If > 0, then the battery pack is charged.
As shown in fig. 2, the total cost expression of the kth device component of the wind-solar-storage independent microgrid adopting the demand-side response planning is as follows:
TUC k ＝IC k +Rep k +M k -RV k (5)
in formula (5): IC (integrated circuit) k Initial costs for procurement, installation and debugging; rep (Rep) k Cost for reset; m is a group of k For operating maintenance costs, RV k Is the remaining value.
Each device component cost time is configured as: initial cost (at the beginning of the project), reset cost (from the end of the life of each component to the end of the system lifecycle), operation and maintenance cost (within the system lifecycle of each year), remaining value (at the end of the system lifecycle).
To convert the initial cost into an annual cost, a capital recovery factor (CRF (i, n)) is used, the capital recovery factor being:
in formula (6): i is interest rate, n is system life cycle, n k Is the life cycle of the kth device component. The annual initial cost of the kth equipment component is:
AIC k ＝IC k ×CRF(i,n) (7)
the annual reset cost for the kth equipment component is:
the remaining value (residual value) of the kth equipment component is:
the annual unit cost of the wind-solar energy storage independent micro-grid equipment assembly is as follows:
ATUC k ＝AIC k +APep k +M k -ARV k (10)
according to the formula (10): the net current cost of the kth equipment component of the wind-solar-storage independent micro-grid is as follows:
NPCU k ＝ATUC k /CRF(i,n) (11)
the scale optimization of the wind-solar-storage independent micro-grid can be divided into: there are cases of DR and no DR. Table 1 gives the results of the scale optimization in these two cases:
TABLE 1 microgrid component size optimization results
The power consumed in the two cases is equal, and partial energy waste can be generated in the charging and discharging processes. The reason for this slight difference in photovoltaic cell power is this waste. However, as shown in the table, the application of DR results in a significant reduction in battery capacity and inverter power. The reason is that: first, due to the proximity of the power consumption side and the power generation side; secondly due to the reduction of load peaks.
In addition, the net present cost of each component and the total net present cost of the microgrid are also obtained, as shown in table 2. Implementation of DR results in a significant reduction in the number of component capacities and energy supply costs. DR also reduced the power of the energy storage system, inverter power, photovoltaic cell capacity, and overall cost by 35%, 35.6%, 1.8%, and 17.2%, respectively.
TABLE 2 comparison of Net Ready cost of Components for two cases (with or without DR)
As shown in fig. 3, the degree of proximity between the power generation side and the power consumption side is determined by a relative difference coefficient:
the DR-free DF index is 0.551, and the correlation factor between the power generation side and the power consumption side is-0.07813 in the case of DR.
As shown in fig. 4, the DF index with DR is 0.406, and the DF index can be reduced by DR to make the power on the power generation side closer to the power on the power consumption side. The DF index is reduced by 26.3% by using DR, so that the power generation side and the power utilization side are closer. In addition, the correlation factor between the power generation side and the power consumption side is +0.2093 in the case of DR. The use of DR increased this factor by 368%.
The above description is only a preferred embodiment of the present invention, and is not intended to limit the present invention, and any simple modifications, changes and equivalent structural changes made to the above embodiment according to the technical essence of the present invention still fall within the protection scope of the technical solution of the present invention.
Claims (8)
1. A wind-solar-storage independent micro-grid economic optimization method based on demand side response is characterized by comprising the following steps:
1) Establishing an output power decomposition formula of a solar panel, an output power decomposition formula of a wind turbine and a charge and discharge power expression formula of an energy storage system;
2) Obtaining a kth equipment component total cost expression of the wind-solar storage independent micro-grid by adopting demand side response planning according to the step 1) of the decomposed output power of the solar panel, the decomposed output power of the wind turbine and the charge-discharge power expression of the energy storage system;
3) Converting initial cost in the kth equipment component total cost expression of the wind-solar-storage independent micro-grid in the step 2) into annual cost, and establishing a capital recovery coefficient expression;
4) Obtaining the initial annual cost of the kth equipment component, the reset annual cost of the kth equipment component and the residual value of the kth equipment component according to the capital recovery coefficient expression in the step 3);
5) Obtaining the annual unit cost of the equipment components in the wind-solar-storage independent micro-grid according to the initial annual cost of the kth equipment component, the annual reset cost of the kth equipment component and the residual value of the kth equipment component in the step 4);
6) Obtaining the net current cost of the kth equipment component of the wind-solar-storage independent micro-grid according to the annual unit cost of the equipment components in the energy-storage micro-grid in the step 5);
7) And 6) analyzing the net current cost of the kth equipment assembly of the energy storage microgrid in the step 6), and verifying the effectiveness of the energy storage optimization method adopting the demand side response planning.
2. The economic optimization method of the wind-solar-storage independent micro-grid based on demand-side response according to claim 1, characterized in that the specific implementation method of the step 1) is as follows: establish solar cell panel output power decomposition formula, solar cell panel PPV's output direct current power depends on solar radiation intensity, absorption capacity, panel area and battery temperature, and solar cell panel output power decomposition formula is:
wherein: g t (t)(W/m 2 ) Is the incident power of the radiation, P, perpendicular to the array surface pv-rated Is the rated power, eta, of the panel under standard test STC conditions pv Is the power reduction coefficient, T, of the solar cell panel C,STC Is the temperature of the battery at STC, beta T Is the photovoltaic temperature coefficient, T C Is the battery temperature at run time, expressed as:
wherein: NOCT is the normal operating battery temperature, T amb Is the ambient temperature; the output power of a wind turbine is a function of the wind speed at the hub height of the wind turbine, and the output power of the wind turbine is decomposed into:
wherein: v (m/s), v r 、v cut-in And v and cut-out respectively, the height of the wind turbine hub, the rated rotating speed, the cut-in speed and the cut-off rotating speed, P r Representing the output power at rated speed; the charge and discharge power expression of the energy storage system is as follows: p is B (t)＝P WT (t)+P PV (t)-P L (t)/η inv (ii) a Wherein: p L Is the total electrical load at time t, eta inv Is the inverter efficiency, if P B =0 then the battery pack is neither charged nor discharged; if P is B And > 0, the battery pack is charged due to the excess power generated by the microgrid.
3. The economic optimization method of the wind-solar-storage independent micro-grid based on demand-side response according to claim 2, wherein the specific implementation method of the step 2) is as follows: according to the step 1), obtaining a k-th equipment component total cost expression of the wind-solar storage independent micro-grid by adopting demand side response planning according to the solar panel output power decomposition type, the wind turbine output power decomposition type and the energy storage system charge-discharge power expression: TUC k ＝IC k +Rep k +M k -RV k (ii) a Wherein: IC (integrated circuit) k Initial costs for procurement, installation and debugging; rep (Rep) k Cost for reset; m is a group of k For operating maintenance costs, RV k Is the remaining value.
4. The economic optimization method of the wind-solar-storage independent micro-grid based on demand-side response according to claim 3, characterized in that the specific implementation method of the step 3) is as follows: converting the initial cost in the k-th equipment component total cost expression of the wind-light storage independent micro-grid in the step 2) into annual cost, and establishing a capital recovery coefficient expression:
wherein: i is interest rate, n is system life cycle, n k Is the generation of the kth energy storage deviceAnd (4) the service life.
5. The economic optimization method of the wind-solar-storage independent micro-grid based on demand-side response is characterized in that the concrete implementation method of the step 4) is to obtain the annual initial cost of the kth equipment component according to the expression of the capital recovery coefficient of the step 3): AIC k ＝IC k X CRF (i, n), annual reset cost of kth equipment component:
and the remaining value of the kth equipment component:
6. the economic optimization method of the wind-solar-storage independent micro-grid based on demand-side response according to claim 5, characterized in that the specific implementation method of the step 5) is as follows: obtaining the annual unit cost of the equipment components in the wind-solar-storage independent micro-grid according to the annual initial cost of the kth equipment component, the annual reset cost of the kth equipment component and the residual value of the kth equipment component in the step 4): ATUC k ＝AIC k +APep k +M k -ARV k 。
7. The economic optimization method of the wind-solar-storage independent micro-grid based on demand-side response according to claim 6, wherein the specific implementation method of the step 6) is as follows: obtaining the net cost of the kth equipment component of the wind-solar energy storage independent microgrid according to the annual unit cost of the equipment components in the energy storage microgrid in the step 5): NPCU k ＝ATUC k /CRF(i,n)。
8. The economic optimization method of the wind-solar-storage independent micro-grid based on demand-side response is characterized in that the specific implementation method of the step 7) is as follows: and 6) analyzing the net current cost of the kth equipment assembly of the energy storage microgrid in the step 6), and verifying the effectiveness of the energy storage optimization method adopting the demand side response planning.
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