CN104124681A - Calculation method for potential regulation capacity parameter of microgrid power supply - Google Patents

Abstract

The invention relates to a calculation method for the potential regulation capacity parameter of microgrid power supply. The calculation method comprises the following steps of: detecting the energy storage level of an energy storage system in a microgrid at the current time and the rated capacity of a random power supply; predicating the total power generation power of the random power supply of the microgrid in the next dispatching period and the total load ultra-short-term predicated value of the microgrid in the next dispatching period respectively; calculating the state variables of the microgrid at the current time and in the next dispatching period; determining the state sub-space where the microgrid is located; calculating the regulation capacity parameter of the consumption unbalance power randomness of the energy storage system of the microgrid; calculating the potential regulation capacity parameter of microgrid power supply according to the rated capacity, and the regulation capacity parameter of the consumption unbalance power randomness. The calculation method disclosed by the invention is simple to calculate and convenient for engineering realization, and lays a theoretical foundation for the energy dispatching of an external power grid for the microgrid.

Description

The computational methods of the potential regulating power parameter of a kind of micro-mains supply

Technical field

The present invention relates to intelligent grid field, particularly the computational methods of the potential regulating power parameter of a kind of micro-mains supply

Background technology

Increasingly mature and perfect along with renewable energy power generation technology, popularity rate and the utility ratio of renewable energy source current in power distribution network will improve constantly, a large amount of wind/light distributed power generations is usingd the form of micro-electrical network as two-way can an access from low-voltage network by scheduling unit, forms microgrid group or active power distribution network that a plurality of micro-electrical networks form.The randomness of the renewable energy power generation unit such as wind/light and source/year bidirectional characteristic intermittent, energy-storage system have proposed new problem to the Optimized Operation of traditional power distribution network.

More conventional method is the angle from power distribution network (or microgrid group) at present, and based on sending out, power consumption prediction is exerted oneself to all single distributed power sources in administrative area and energy-storage system is dispatched, and comprises the power supply of microgrid inside.

Mathematical Modeling, the dimension of this class methods control variables is very large on the one hand, forms source/year two-way control variables on the other hand make solution space more complicated by the inner energy-storage system of each microgrid.From engineering practice, following wind/the photoelectric source being connected of points of common connection (PCC point) of the micro-electrical network of low pressure and power distribution network and the scheduling and controlling of energy-storage system normally shield power distribution network or microgrid group, that is to say, the power that Utilities Electric Co. orders to micro-electrical network PCC carries out scheduling and controlling and is only feasible.。

Summary of the invention

Technical problem to be solved by this invention is to provide the calculation method of parameters of active power distribution network, microgrid group and microgrid energy scheduling.

For this purpose, the invention provides the computational methods of the potential regulating power parameter of a kind of micro-mains supply, said method comprising the steps of:

S1. detect energy-storage system in micro-electrical network in the energy storage level of current time with the rated capacity of electromechanical source;

S2. distinguish pre-micrometer electrical network with electromechanical source at total generated output ultra-short term predicted value of next dispatching cycle and micro-electrical network the total load ultra-short term predicted value in next dispatching cycle;

S3. according to described energy-storage system the energy storage level of current time, micro-electrical network the total load ultra-short term predicted value of next dispatching cycle and with electromechanical source the total generated output ultra-short term predicted value in next dispatching cycle, calculate micro-electrical network in current time and the state variable in next dispatching cycle;

S4. according to described micro-electrical network in current time and the state variable in next dispatching cycle, determine the subspace method at the current place of micro-electrical network;

S5. in described subspace method, calculate the regulating power parameter of the imbalance power randomness of dissolving of micro-electrical network energy-storage system;

S6. according to the regulating power parameter of the imbalance power randomness of dissolving of the described rated capacity with electromechanical source and micro-electrical network energy-storage system, calculate the potential regulating power parameter of micro-mains supply.

Further, described micro-electrical network comprises in the state variable of current time: micro-electrical network is at the reserve of electricity of current time and can deposit electric weight; The state variable of described micro-electrical network within next dispatching cycle comprises: risk standby electric weight and the risk short of electricity amount of micro-electrical network within next dispatching cycle.

Further, described step S3 specifically comprises the following steps:

According to described with electromechanical source at total generated output ultra-short term predicted value of next dispatching cycle and micro-electrical network the total load ultra-short term predicted value in next dispatching cycle, calculate the risk reserve capacity R of micro-electrical network _aR(β);

According to described risk reserve capacity, utilize formula and formula calculate respectively the risk standby electric weight E of micro-electrical network within next dispatching cycle _raRwith risk short of electricity amount E _laR;

Detect the rated capacity A of described micro-electrical network energy-storage system _r, reserve of electricity upper limit A _maxwith lower limit A _min;

According to the horizontal S of described energy storage _oC, described energy-storage system rated capacity A _r, described reserve of electricity upper limit A _maxwith lower limit A _min, utilize formula A _s,t=S _oCa _r-A _minwith formula A _e,t=A _max-S _oCa _r, calculate respectively micro-electrical network energy-storage system at the A of reserve of electricity of current time _s,twith can deposit electric weight A _e,t;

Wherein, t is current time, and T is dispatching cycle, and β is the confidence level that the actual reserve capacity of micro-electrical network is more than or equal to risk reserve capacity, and N is the sampling number of described dispatching cycle of T in the period, N ₀for risk reserve capacity R _aR(β)=0 sequence number, S _oCfor the energy storage level of described micro-electrical network energy-storage system at current time.

Further, the calculating of described risk reserve capacity specifically comprises the following steps:

According to described with electromechanical source at total generated output ultra-short term predicted value of next dispatching cycle and micro-electrical network in the total load ultra-short term predicted value of next dispatching cycle, utilize formula $\tilde{R}\left(t\right)=P_{\mathrm{\Σgt}}\left(t\right)-P_{\mathrm{\Σld}}\left(t\right),$ Calculate the reserve capacity of micro-electrical network

According to described reserve capacity, utilize formula $R_{\mathrm{aR}}\left(\mathrm{\β}\right)=\max \left\{\mathrm{\α}\right|\mathrm{Pr}\{\tilde{R}\left(t\right)\≤\mathrm{\α}\}\≤1-\mathrm{\β}\},$ Calculation risk reserve capacity R _aR(β);

Wherein, P _{Σ gt}(t) be described micro-electrical network with electromechanical source at next dispatching cycle of total generated output ultra-short term predicted value of t constantly, P _{Σ ld}(t) be described micro-electrical network in next dispatching cycle of the total load ultra-short term predicted value of t constantly, the reserve capacity comparison value that α is micro-electrical network, β is the confidence level that the actual reserve capacity of micro-electrical network is more than or equal to risk reserve capacity.

Further, in described step S4, by following logical formula, determined the subspace method at the current place of micro-electrical network:

If meet logic judgment formula: (E _raR-E _laR)>=0 ∩ A _e,t>=E _raR∩ A _s,t>=E _laR, the current place of micro-electrical network the first subspace method;

If meet logic judgment formula: (E _raR-E _laR)>=0 ∩ A _e,t>=E _raR∩ A _s,t< E _laR, the current place of micro-electrical network the second subspace method;

If meet logic judgment formula: (E _raR-E _laR)>=0 ∩ E _raR> A _e,t>=E ∩ A _s,t>=E _laR, third state subspace, the current place of micro-electrical network;

If meet logic judgment formula: (E _raR-E _laR)>=0 ∩ E _raR> A _e,t>=E ∩ A _s,t< E _laR, the current place of micro-electrical network the 4th subspace method;

If meet logic judgment formula: (E _raR-E _laR)>=0 ∩ A _e,t< E ∩ A _s,t>=E _laR, the current place of micro-electrical network the 5th subspace method;

If meet logic judgment formula: (E _raR-E _laR)>=0 ∩ A _e,t< E ∩ A _s,t< E _laR, the current place of micro-electrical network the 6th subspace method;

If meet logic judgment formula: (E _raR-E _laR) < 0 ∩ A _s,t>=E _laR∩ A _e,t>=E _raR, the current place of micro-electrical network the 7th subspace method;

If meet logic judgment formula: (E _raR-E _laR) < 0 ∩ A _s,t>=E _laR∩ A _e,t< E _raR, the current place of micro-electrical network the 8th subspace method;

If meet logic judgment formula: (E _raR-E _laR) < 0 ∩ E _laR> A _s,t>=| E| ∩ A _e,t>=E _raR, the current place of micro-electrical network the 9th subspace method;

If meet logic judgment formula: (E _raR-E _laR) < 0 ∩ E _laR> A _s,t>=| E| ∩ A _e,t< E _raR, the current place of micro-electrical network the tenth subspace method;

If meet logic judgment formula: (E _raR-E _laR) < 0 ∩ A _s,t< | E ∩ A _e,t>=E _raR, the current place of micro-electrical network the 11 subspace method;

If meet logic judgment formula: (E _raR-E _laR) < 0 ∩ A _s,t< | E| ∩ A _e,t< E _raR, the tenth two-state subspace, the current place of micro-electrical network;

Wherein, E _raRfor risk standby electric weight, the E of described micro-electrical network within next dispatching cycle _laRfor the risk short of electricity amount of described micro-electrical network within next dispatching cycle, A _s,tfor the reserve of electricity of described micro-electrical network at current time, A _e,tfor the deposited electric weight of described micro-electrical network at current time.

Further, described step S5 specifically comprises:

In definite subspace, the regulating power parameter of calculating the imbalance power randomness of dissolving of described micro-electrical network energy-storage system according to following subspace computing formula, the regulating power parameter of the imbalance power randomness of dissolving of described micro-electrical network energy-storage system comprises: described micro-electrical network energy-storage system abandoning within next dispatching cycle can electric weight with off-load electric weight described micro-electrical network energy-storage system is at the A of reserve of electricity of next dispatching cycle end _{s, t+T}with can deposit electric weight A _{e, t+T};

The first subspace method computing formula: a _{s, t+T}=A _s,t+ Δ E, A _{e, t+T}=A _e,t-Δ E;

The second subspace method computing formula: $E_g^0=0,E_L^0\&Element;[0,E_{\mathrm{LaR}}-A_{s,t}],$ A _s,t+T∈[A _s,t+ΔE,E _RaR]、A _e,t+T∈[A－E _RaR,A _e,t－ΔE]；

Third state subspace computing formula: a _{s, t+T}∈ [A-E _laR, A _s,t+ Δ E], A _{e, t+T}∈ [A _e,t-Δ E, E _raR];

The 4th subspace method computing formula: $E_g^0\&Element;[0,E_{\mathrm{RaR}}-A_{e,t}],E_L^0\&Element;[0,E_{\mathrm{LaR}}-A_{s,t}],$ A _s,t+T∈[A－E _LaR,E _RaR]、A _e,t+T∈[A－E _RaR,E _LaR]；

The 5th subspace method computing formula: $E_g^0\&Element;[\mathrm{\&Delta;E}-A_{e,t},E_{\mathrm{RaR}}-A_{e,t}],E_L^0=0,$ A _s,t+T∈[A－E _LaR,A]、A _e,t+T∈[0,E _LaR]；

The 6th subspace method computing formula: $E_g^0\&Element;[\mathrm{\&Delta;E}-A_{e,t},E_{\mathrm{RaR}}-A_{e,t}],E_L^0\&Element;[0,E_{\mathrm{LaR}}$ $-A_{s,t}],$ A _s,t+T∈[A－E _LaR,A]、A _e,t+T∈[0,E _LaR]；

The 7th subspace method computing formula: a _{s, t+T}=A _s,t-| Δ E|, A _{e, t+T}=A _e,t+ | Δ E|;

The 8th subspace method computing formula: a _{s, t+T}∈ [A-E _laR, A _s,t-| Δ E|], A _{e, t+T}∈ [A _e,t+ | Δ E|, E _laR];

The 9th subspace method computing formula: $E_g^0=0,E_L^0\&Element;[0,E_{\mathrm{LaR}}-A_{s,t}],$ A _s,t+T∈[A _s,t-|ΔE|,E _RaR]、A _e,t+T∈[A-E _RaR,A _e,t+|ΔE|]；

The tenth subspace method computing formula: $E_g^0\&Element;[0,E_{\mathrm{RaR}}-A_{e,t}],E_L^0\&Element;[0,E_{\mathrm{LaR}}-A_{s,t}],$ A _s,t+T∈[A－E _LaR,E _RaR]、A _e,t+T∈[A-E _RaR,E _LaR]；

The 11 subspace method computing formula: $E_g^0=0,E_L^0\&Element;\left[\right|\mathrm{\&Delta;E}|-A_{s,t},E_{\mathrm{LaR}}-A_{s,t}],$ A _s,t+T∈[0，E _RaR]、A _e,t+T∈[A-E _RaR,A]；

The tenth two-state subspace computing formula: a _{s, t+T}∈ [0, E _raR], A _{e, t+T}∈ [A-E _raR, A];

Wherein, Δ E=E _raR-E _laR, Δ E is that micro-electrical network is by the electric energy gross spread of random Power supply, E _raRfor the risk standby electric weight of micro-electrical network within next dispatching cycle, E _laRfor the risk short of electricity amount of micro-electrical network within next dispatching cycle, A _{s, t+T}for the reserve of electricity of micro-electrical network energy-storage system in next dispatching cycle end, A _{e, t+T}for the deposited electric weight of micro-electrical network energy-storage system in next dispatching cycle end, for micro-electrical network energy-storage system abandoning within next dispatching cycle can electric weight, for the off-load electric weight of micro-electrical network energy-storage system within next dispatching cycle, A _s,tfor the reserve of electricity of micro-electrical network energy-storage system at current time, A _e,tfor the deposited electric weight of micro-electrical network energy-storage system at current time, A is that micro-electrical network energy-storage system is at the A of reserve of electricity of current time _s,twith can deposit electric weight A _e,tsum.

Further, described step S6 specifically comprises the following steps:

According to the described rated capacity with electromechanical source, by formula calculating is with electromechanical source exportable maximum total amount within next dispatching cycle;

According to described maximum total amount G, by formula calculate the exportable electric weight E of micro-electrical network within next dispatching cycle _out;

By formula calculate the inputted electric weight E of micro-electrical network within next dispatching cycle _in;

By formula calculating micro-electrical network abandoning within next dispatching cycle can electric weight E _g;

According to described maximum total amount G, by formula $E_L=\left\{\begin{array}{cc}{E}_{L,\max }^0-G& E_{L,\max }^0>G\\ 0& E_{L,\max }^0\&le;G\end{array}\right.$ Calculate the off-load electric weight E of micro-electrical network within next dispatching cycle _l:

Wherein, for described micro-electrical network energy-storage system abandoning within next dispatching cycle can electric weight maximum, for described micro-electrical network energy-storage system abandoning within next dispatching cycle can electric weight minimum value, for the off-load electric weight of described micro-electrical network energy-storage system within next dispatching cycle minimum value, for the off-load electric weight of described micro-electrical network energy-storage system within next dispatching cycle maximum, A _{s, t+T, min}for the reserve of electricity A of described micro-electrical network energy-storage system in next dispatching cycle end _{s, t+T}minimum value, A _{e, t+T, min}for the minimum value of described micro-electrical network energy-storage system at the electric weight deposited of next dispatching cycle end, P _{gn, j}be j platform with the rated capacity of electromechanical source, T is next dispatching cycle.

Further, described exportable electric weight, can be to the electric weight of external power grid output for to meet under the prerequisite of self-demand at micro-electrical network; The described electric weight of inputting is that micro-electrical network can absorb the outside electric weight injecting; Described abandon can electric weight the load that is micro-electrical network and the energy storage maximum residual energy output that can not receive; Described off-load electric weight is the maximum off-load electric weight that micro-electrical network causes due to generation deficiency.

By adopting the computational methods of the potential regulating power parameter of a kind of micro-mains supply disclosed in this invention, provide a kind of calculate simple, be convenient to Project Realization, the power supply regulating power that micro-electrical network has within dispatching cycle can correctly be described.

Accompanying drawing explanation

By reference to accompanying drawing, can more clearly understand the features and advantages of the present invention, accompanying drawing is schematically to should not be construed as the present invention is carried out to any restriction, in the accompanying drawings:

Fig. 1 shows the computational methods flow chart of the potential regulating power parameter of a kind of micro-mains supply that the embodiment of the present invention provides;

Fig. 2 shows the risk reserve capacity curve that the embodiment of the present invention provides.

Embodiment

Below in conjunction with accompanying drawing, embodiments of the present invention is described in detail.

The embodiment of the present invention has proposed the computational methods of the potential regulating power parameter of a kind of micro-mains supply, and as shown in Figure 1, the method comprises the following steps:

S1. detect the energy storage level at current time of energy-storage system in micro-electrical network and with the rated capacity of electromechanical source.

S2. distinguish pre-micrometer electrical network with electromechanical source at total generated output ultra-short term predicted value of next dispatching cycle and micro-electrical network the total load ultra-short term predicted value in next dispatching cycle.

S3. according to described energy-storage system the energy storage level of current time, micro-electrical network the total load ultra-short term predicted value of next dispatching cycle and with electromechanical source the total generated output ultra-short term predicted value in next dispatching cycle, calculate micro-electrical network in current time and the state variable in next dispatching cycle.

Particularly, described micro-electrical network comprises in the state variable of current time: micro-electrical network is at the reserve of electricity of current time and can deposit electric weight; The state variable of described micro-electrical network within next dispatching cycle comprises: risk standby electric weight and the risk short of electricity amount of micro-electrical network within next dispatching cycle.

Particularly, described step S3 specifically comprises the following steps:

According to described with electromechanical source at total generated output ultra-short term predicted value of next dispatching cycle and micro-electrical network the total load ultra-short term predicted value in next dispatching cycle, calculate the risk reserve capacity R of micro-electrical network _aR(β);

According to described risk reserve capacity, utilize formula and formula calculate respectively the risk standby electric weight E of micro-electrical network within next dispatching cycle _raRwith risk short of electricity amount E _laR;

Detect the rated capacity A of described micro-electrical network energy-storage system _r, reserve of electricity upper limit A _maxwith lower limit A _min;

According to the horizontal S of described energy storage _oC, described energy-storage system rated capacity A _r, described reserve of electricity upper limit A _maxwith lower limit A _min, utilize formula A _s,t=S _oCa _r-A _minwith formula A _e,t=A _max-S _oCa _r, calculate respectively micro-electrical network energy-storage system at the A of reserve of electricity of current time _s,twith can deposit electric weight A _e,t;

Wherein, t is current time, and T is dispatching cycle, and β is the confidence level that the actual reserve capacity of micro-electrical network is more than or equal to risk reserve capacity, and N is the sampling number of described dispatching cycle of T in the period, obtains the N that sampling number sorted after sampling number ₀for risk reserve capacity R _aR(β)=0 sequence number (after obtaining sampling number, sampling number being sorted), S _oCfor the energy storage level of described micro-electrical network energy-storage system at current time.

Particularly, the calculating of described risk reserve capacity specifically comprises the following steps:

According to described with electromechanical source at total generated output ultra-short term predicted value of next dispatching cycle and micro-electrical network in the total load ultra-short term predicted value of next dispatching cycle, utilize formula $\tilde{R}\left(t\right)=P_{\mathrm{\&Sigma;gt}}\left(t\right)-P_{\mathrm{\&Sigma;ld}}\left(t\right),$ Calculate the reserve capacity of micro-electrical network

According to described reserve capacity, utilize formula $R_{\mathrm{aR}}\left(\mathrm{\&beta;}\right)=\max \left\{\mathrm{\&alpha;}\right|\mathrm{Pr}\{\tilde{R}\left(t\right)\&le;\mathrm{\&alpha;}\}\&le;1-\mathrm{\&beta;}\},$ Calculation risk reserve capacity R _aR(β);

Wherein, P _{Σ gt}(t) be described micro-electrical network with electromechanical source at next dispatching cycle of total generated output ultra-short term predicted value of t constantly, P _{Σ ld}(t) be described micro-electrical network in next dispatching cycle of the total load ultra-short term predicted value of t constantly, the reserve capacity comparison value that α is micro-electrical network, β is the confidence level that the actual reserve capacity of micro-electrical network is more than or equal to risk reserve capacity.

Wherein, the standby computing formula of risk computing formula with risk short of electricity amount according to following content, release: as shown in Figure 2, according to described reserve capacity, utilize formula $R_{\mathrm{aR}}\left(\mathrm{\&beta;}\right)=\max \left\{\mathrm{\&alpha;}\right|\mathrm{Pr}\{\tilde{R}\left(t\right)\&le;\mathrm{\&alpha;}\}\&le;1-\mathrm{\&beta;}\},$ Calculation risk reserve capacity R _aR(β), risk reserve capacity R _aR(β) with level of confidence, change, the larger level of confidence of risk reserve capacity is lower, more excessive risk reserve capacity is less for confidence level, i.e. R _aR(β) with level of confidence is dull, decline, R within a dispatching cycle _aR(β) change curve; Curve R _aR(β) upper risk reserve capacity equals the β of 0 correspondence ₀, represented that system can meet the probability of workload demand with electromechanical source.Curve is greater than the area S that 0 part and transverse axis surround ₁in period T, the surplus electric weight of micro-electrical network, being defined as confidence level is β ₀under the standby electric weight of risk, curve R _aR(β) be less than the area S that 0 part and transverse axis surround ₂for in period T, only by the short of electricity amount of micro-electrical network in random Power supply situation, being defined as confidence level is β ₀under risk short of electricity amount.

S4. according to described micro-electrical network in current time and the state variable in next dispatching cycle, determine the subspace method at the current place of micro-electrical network.

Particularly, in described step S4, by following logical formula, determined the subspace method at the current place of micro-electrical network:

If meet logic judgment formula: (E _raR-E _laR)>=0 ∩ A _e,t>=E _raR∩ A _s,t>=E _laR, the current place of micro-electrical network the first subspace method;

If meet logic judgment formula: (E _raR-E _laR)>=0 ∩ A _e,t>=E _raR∩ A _s,t< E _laR, the current place of micro-electrical network the second subspace method;

If meet logic judgment formula: (E _raR-E _laR)>=0 ∩ E _raR> A _e,t>=E ∩ A _s,t>=E _laR, third state subspace, the current place of micro-electrical network;

If meet logic judgment formula: (E _raR-E _laR)>=0 ∩ E _raR> A _e,t>=E ∩ A _s,t< E _laR, the current place of micro-electrical network the 4th subspace method;

If meet logic judgment formula: (E _raR-E _laR)>=0 ∩ A _e,t< E ∩ A _s,t>=E _laR, the current place of micro-electrical network the 5th subspace method;

If meet logic judgment formula: (E _raR-E _laR)>=0 ∩ A _e,t< E ∩ A _s,t< E _laR, the current place of micro-electrical network the 6th subspace method;

If meet logic judgment formula: (E _raR-E _laR) < 0 ∩ A _s,t>=E _laR∩ A _e,t>=E _raR, the current place of micro-electrical network the 7th subspace method;

If meet logic judgment formula: (E _raR-E _laR) < 0 ∩ A _s,t>=E _laR∩ A _e,t< E _raR, the current place of micro-electrical network the 8th subspace method;

If meet logic judgment formula: (E _raR-E _laR) < 0 ∩ E _laR> A _s,t>=| E| ∩ A _e,t>=E _raR, the current place of micro-electrical network the 9th subspace method;

If meet logic judgment formula: (E _raR-E _laR) < 0 ∩ E _laR> A _s,t>=| E| ∩ A _e,t< E _raR, the current place of micro-electrical network the tenth subspace method;

If meet logic judgment formula: (E _raR-E _laR) < 0 ∩ A _s,t< | E ∩ A _e,t>=E _raR, the current place of micro-electrical network the 11 subspace method;

If meet logic judgment formula: (E _raR-E _laR) < 0 ∩ A _s,t< | E| ∩ A _e,t< E _raR, the tenth two-state subspace, the current place of micro-electrical network;

Wherein, E _raRfor risk standby electric weight, the E of described micro-electrical network within next dispatching cycle _laRfor the risk short of electricity amount of described micro-electrical network within next dispatching cycle, A _s,tfor the reserve of electricity of described micro-electrical network at current time, A _e,tfor the deposited electric weight of described micro-electrical network at current time.

In the present embodiment, utilize table 1 inquiry micro-electrical network place subspace method.According to described micro-electrical network in current time and the state variable in next dispatching cycle: micro-electrical network is in the standby electric weight of risk and the risk short of electricity amount of next dispatching cycle, micro-electrical network is at the reserve of electricity of current time and can deposit electric weight, judge the scope of subspace, thereby definite micro-electrical network place

Subspace method.Build table 1 specific as follows.

Table 1: the logical expression of energy-storage system regulating power subspace method

No	Subspace scope	No	Subspace scope
				1	ΔE≥0∩A e,t≥E RaR∩A s,t≥E LaR	7	ΔE＜0∩A s,t≥E LaR∩A e,t≥E RaR
2	ΔE≥0∩A e,t≥E RaR∩A s,t＜E LaR	8	ΔE＜0∩A s,t≥E LaR∩A e,t＜E RaR
				3	ΔE≥0∩E RaR＞A e,t≥ΔE∩A s,t≥E LaR	9	ΔE＜0∩E LaR＞A s,t≥|ΔE|∩A e,t≥E RaR
4	ΔE≥0∩E RaR＞A e,t≥ΔE∩A s,t＜E LaR	10	ΔE＜0∩E LaR＞A s,t≥|ΔE|∩A e,t＜E RaR
				5	ΔE≥0∩A e,t＜ΔE∩A s,t≥E LaR	11	ΔE＜0∩A s,t＜|ΔE∩A e,t≥E RaR
6	ΔE≥0∩A e,t＜ΔE∩A s,t＜E LaR	12	ΔE＜0∩A s,t＜|ΔE|∩A e,t＜E RaR

S5. in described subspace method, calculate the regulating power parameter of the imbalance power randomness of dissolving of micro-electrical network energy-storage system.

Particularly, described step S5 specifically comprises:

In definite subspace, the regulating power parameter of calculating the imbalance power randomness of dissolving of described micro-electrical network energy-storage system according to following subspace computing formula, the regulating power parameter of the imbalance power randomness of dissolving of described micro-electrical network energy-storage system comprises: described micro-electrical network energy-storage system abandoning within next dispatching cycle can electric weight with off-load electric weight described micro-electrical network energy-storage system is at the A of reserve of electricity of next dispatching cycle end _{s, t+T}with can deposit electric weight A _{e, t+T};

The first subspace method computing formula: a _{s, t+T}=A _s,t+ Δ E, A _{e, t+T}=A _e,t-Δ E;

The second subspace method computing formula: $E_g^0=0,E_L^0\&Element;[0,E_{\mathrm{LaR}}-A_{s,t}],$ A _s,t+T∈[A _s,t+ΔE,E _RaR]、A _e,t+T∈[A－E _RaR,A _e,t－ΔE]；

Third state subspace computing formula: a _{s, t+T}∈ [A-E _laR, A _s,t+ Δ E], A _{e, t+T}∈ [A _e,t-Δ E, E _raR];

The 4th subspace method computing formula: $E_g^0\&Element;[0,E_{\mathrm{RaR}}-A_{e,t}],E_L^0\&Element;[0,E_{\mathrm{LaR}}-A_{s,t}],$ A _s,t+T∈[A－E _LaR,E _RaR]、A _e,t+T∈[A－E _RaR,E _LaR]；

The 5th subspace method computing formula: $E_g^0\&Element;[\mathrm{\&Delta;E}-A_{e,t}{,E}_{\mathrm{RaR}}-A_{e,t}],E_L^0=0,$ A _s,t+T∈[A－E _LaR,A]、A _e,t+T∈[0,E _LaR]；

The 6th subspace method computing formula: $E_g^0\&Element;[\mathrm{\&Delta;E}-A_{e,t},E_{\mathrm{RaR}}-A_{e,t}],E_L^0\&Element;[0,E_{\mathrm{LaR}}$ $-A_{s,t}],$ A _s,t+T∈[A－E _LaR,A]、A _e,t+T∈[0,E _LaR]；

The 7th subspace method computing formula: a _{s, t+T}=A _s,t-| Δ E|, A _{e, t+T}=A _e,t+ | Δ E|;

The 8th subspace method computing formula: a _{s, t+T}∈ [A-E _laR, A _s,t-| Δ E|], A _{e, t+T}∈ [A _e,t+ | Δ E|, E _laR];

The 9th subspace method computing formula: $E_g^0=0,E_L^0\&Element;[0,E_{\mathrm{LaR}}-A_{s,t}],$ A _s,t+T∈[A _s,t-|ΔE|,E _RaR]、A _e,t+T∈[A-E _RaR,A _e,t+|ΔE|]；

The tenth subspace method computing formula: $E_g^0\&Element;[0,E_{\mathrm{RaR}}-A_{e,t}],E_L^0\&Element;[0,E_{\mathrm{LaR}}-A_{s,t}],$ A _s,t+T∈[A－E _LaR,E _RaR]、A _e,t+T∈[A-E _RaR,E _LaR]；

The 11 subspace method computing formula: $E_g^0=0,E_L^0\&Element;\left[\right|\mathrm{\&Delta;E}|-A_{s,t},E_{\mathrm{LaR}}-A_{s,t}],$ A _s,t+T∈[0，E _RaR]、A _e,t+T∈[A-E _RaR,A]；

The tenth two-state subspace computing formula: a _{s, t+T}∈ [0, E _raR], A _{e, t+T}∈ [A-E _raR, A];

Wherein, Δ E=E _raR-E _laR, Δ E is that micro-electrical network is by the electric energy gross spread of random Power supply, E _raRfor the risk standby electric weight of micro-electrical network within next dispatching cycle, E _laRfor the risk short of electricity amount of micro-electrical network within next dispatching cycle, A _{s, t+T}for the reserve of electricity of micro-electrical network energy-storage system in next dispatching cycle end, A _{e, t+T}for the deposited electric weight of micro-electrical network energy-storage system in next dispatching cycle end, for micro-electrical network energy-storage system abandoning within next dispatching cycle can electric weight, for the off-load electric weight of micro-electrical network energy-storage system within next dispatching cycle, A _s,tfor the reserve of electricity of micro-electrical network energy-storage system at current time, A _e,tfor the deposited electric weight of micro-electrical network energy-storage system at current time, A is that micro-electrical network energy-storage system is at the A of reserve of electricity of current time _s,twith can deposit electric weight A _e,tsum.

When this micro-electrical network is when with electromechanical source supply of electrical energy, the gross spread of electric energy supply and demand is:

ΔE＝E _RaR-E _LaR

Δ E>0 represents the dump energy that system is supplied with in T period regenerative resource; Δ E<0 represents the vacancy electric weight that system is supplied with in T period regenerative resource; Δ E=0 represents that system just in time meets the equilibrium of supply and demand at T period renewable energy power generation.

In the present embodiment, utilize the formula of table 2 corresponding row.In the subspace method at micro-electrical network place of determining in step S4, reserve of electricity and the data that can deposit the scarce standby electric weight of electric weight and the risk of next dispatching cycle end, risk short of electricity amount according to micro-electrical network energy-storage system at current time.By the formula in table 2, calculate micro-electrical network energy-storage system in next dispatching cycle Mo, the reserve of electricity of energy-storage system, can deposit electric weight, abandoning can electric weight, the upper and lower bound of off-load electric weight, thereby determine the regulating power parameter of the imbalance power randomness of dissolving of micro-electrical network energy-storage system.Wherein, micro-electrical network energy-storage system in the data of next dispatching cycle end, is got two ends data (current time and next end moment dispatching cycle) constantly at current time, calculates the regulating power parameter of the imbalance power randomness of dissolving.The A of reserve of electricity by current time _s,t, can deposit electric weight A _e,t, and the standby electric weight E of risk of next dispatching cycle _raRwith risk short of electricity amount E _laRfor state variable.By the span of state variable, state space can be divided into 12 intervals.Current micro-electrical network is when 12 different intervals, and micro-electrical network energy-storage system is at the minimum value A of the reserve of electricity of next dispatching cycle Mo (t+T constantly) _{s, t+T, min}, can deposit the minimum value A of electric weight _{e, t+T, min}, abandon can electric weight maximum and minimum value and the maximum of off-load electric weight and minimum value computing formula list in table 2.

Table 2:12 sub spaces energy-storage system regulating power index computational chart

Wherein, the minimum value A of reserve of electricity as shown in table 2 _{s, t+T, min}, can deposit the minimum value A of electric weight _{e, t+T, min}, abandon can electric weight maximum and minimum value and the maximum of off-load electric weight and minimum value computing formula be in the computing formula of subspace interval two ends.

S6. according to the regulating power parameter of the imbalance power randomness of dissolving of the described rated capacity with electromechanical source and micro-electrical network energy-storage system, calculate the potential regulating power parameter of micro-mains supply.

Particularly, described step S6 specifically comprises the following steps:

According to the described rated capacity with electromechanical source, by formula calculating is with electromechanical source exportable maximum total amount within next dispatching cycle;

According to described maximum total amount G, by formula calculate the exportable electric weight E of micro-electrical network within next dispatching cycle _out;

By formula calculate the inputted electric weight E of micro-electrical network within next dispatching cycle _in;

By formula calculating micro-electrical network abandoning within next dispatching cycle can electric weight E _g;

According to described maximum total amount G, by formula $E_L=\left\{\begin{array}{cc}{E}_{L,\max }^0-G& E_{L,\max }^0>G\\ 0& E_{L,\max }^0\&le;G\end{array}\right.$ Calculate the off-load electric weight E of micro-electrical network within next dispatching cycle _l:

Wherein, for described micro-electrical network energy-storage system abandoning within next dispatching cycle can electric weight maximum, for described micro-electrical network energy-storage system abandoning within next dispatching cycle can electric weight minimum value, for the off-load electric weight of described micro-electrical network energy-storage system within next dispatching cycle minimum value, for the off-load electric weight of described micro-electrical network energy-storage system within next dispatching cycle maximum, A _{s, t+T, min}for the reserve of electricity A of described micro-electrical network energy-storage system in next dispatching cycle end _{s, t+T}minimum value, A _{e, t+T, min}for the minimum value of described micro-electrical network energy-storage system at the electric weight deposited of next dispatching cycle end, P _{gn, j}be j platform with the rated capacity of electromechanical source, T is next dispatching cycle.

Particularly, described exportable electric weight, can be to the electric weight of external power grid output for to meet under the prerequisite of self-demand at micro-electrical network; The described electric weight of inputting is that micro-electrical network can absorb the outside electric weight injecting; Described abandon can electric weight the load that is micro-electrical network and the energy storage maximum residual energy output that can not receive; Described off-load electric weight is the maximum off-load electric weight that micro-electrical network causes due to generation deficiency.

Visible by foregoing description, the embodiment of the present invention has following beneficial effect:

The computational methods of the potential regulating power parameter of a kind of micro-mains supply that the embodiment of the present invention provides, by calculating micro-electrical network in current time and the state variable of next dispatching cycle end, determine state space described in micro-electrical network, and in state space, calculate after the regulating power parameter of the imbalance power randomness of dissolving of energy-storage system, calculate the potential regulating power parameter of micro-mains supply, provide a kind of calculating simple, be convenient to Project Realization, the power supply regulating power that micro-electrical network has within dispatching cycle can correctly be described, for external power grid (comprising initiatively power distribution network and microgrid group) has been established theoretical foundation to the energy scheduling of micro-electrical network.

Although described by reference to the accompanying drawings embodiments of the present invention, but those skilled in the art can make various modifications and variations without departing from the spirit and scope of the present invention, such modification and modification all fall into by within claims limited range.

Claims (8)

1. computational methods for the potential regulating power parameter of micro-mains supply, is characterized in that, said method comprising the steps of:

S1. detect energy-storage system in micro-electrical network in the energy storage level of current time with the rated capacity of electromechanical source;

S2. distinguish pre-micrometer electrical network with electromechanical source at total generated output ultra-short term predicted value of next dispatching cycle and micro-electrical network the total load ultra-short term predicted value in next dispatching cycle;

S3. according to described energy-storage system the energy storage level of current time, micro-electrical network the total load ultra-short term predicted value of next dispatching cycle and with electromechanical source the total generated output ultra-short term predicted value in next dispatching cycle, calculate micro-electrical network in current time and the state variable in next dispatching cycle;

S4. according to described micro-electrical network in current time and the state variable in next dispatching cycle, determine the subspace method at the current place of micro-electrical network;

S5. in described subspace method, calculate the regulating power parameter of the imbalance power randomness of dissolving of micro-electrical network energy-storage system;

S6. according to the regulating power parameter of the imbalance power randomness of dissolving of the described rated capacity with electromechanical source and micro-electrical network energy-storage system, calculate the potential regulating power parameter of micro-mains supply.

2. computational methods according to claim 1, is characterized in that, described micro-electrical network comprises in the state variable of current time: micro-electrical network is at the reserve of electricity of current time and can deposit electric weight; The state variable of described micro-electrical network within next dispatching cycle comprises: risk standby electric weight and the risk short of electricity amount of micro-electrical network within next dispatching cycle.

3. computational methods according to claim 1, is characterized in that, described step S3 specifically comprises the following steps:

According to described with electromechanical source at total generated output ultra-short term predicted value of next dispatching cycle and micro-electrical network the total load ultra-short term predicted value in next dispatching cycle, calculate the risk reserve capacity R of micro-electrical network _aR(β);

According to described risk reserve capacity, utilize formula and formula calculate respectively the risk standby electric weight E of micro-electrical network within next dispatching cycle _raRwith risk short of electricity amount E _laR;

Detect the rated capacity A of described micro-electrical network energy-storage system _r, reserve of electricity upper limit A _maxwith lower limit A _min;

According to the horizontal S of described energy storage _oC, described energy-storage system rated capacity A _r, described reserve of electricity upper limit A _maxwith lower limit A _min, utilize formula A _s,t=S _oCa _r-A _minwith formula A _e,t=A _max-S _oCa _r, calculate respectively micro-electrical network energy-storage system at the A of reserve of electricity of current time _s,twith can deposit electric weight A _e,t;

Wherein, t is current time, and T is dispatching cycle, and β is the confidence level that the actual reserve capacity of micro-electrical network is more than or equal to risk reserve capacity, and N is the sampling number of described dispatching cycle of T in the period, N ₀for risk reserve capacity R _aR(β)=0 sequence number, S _oCfor the energy storage level of described micro-electrical network energy-storage system at current time.

4. computational methods according to claim 3, is characterized in that, the calculating of described risk reserve capacity specifically comprises the following steps:

According to described with electromechanical source at total generated output ultra-short term predicted value of next dispatching cycle and micro-electrical network in the total load ultra-short term predicted value of next dispatching cycle, utilize formula $\tilde{R}\left(t\right)=P_{\mathrm{\&Sigma;gt}}\left(t\right)-P_{\mathrm{\&Sigma;ld}}\left(t\right),$ Calculate the reserve capacity of micro-electrical network

According to described reserve capacity, utilize formula $R_{\mathrm{aR}}\left(\mathrm{\&beta;}\right)=\max \left\{\mathrm{\&alpha;}\right|\mathrm{Pr}\{\tilde{R}\left(t\right)\&le;\mathrm{\&alpha;}\}\&le;1-\mathrm{\&beta;}\},$ Calculation risk reserve capacity R _aR(β);

Wherein, P _{∑ gt}(t) be described micro-electrical network with electromechanical source at next dispatching cycle of total generated output ultra-short term predicted value of t constantly, P _{Σ ld}(t) be described micro-electrical network in next dispatching cycle of the total load ultra-short term predicted value of t constantly, the reserve capacity comparison value that α is micro-electrical network, β is the confidence level that the actual reserve capacity of micro-electrical network is more than or equal to risk reserve capacity.

5. computational methods according to claim 4, is characterized in that, in described step S4, are determined the subspace method at the current place of micro-electrical network by following logical formula:

If meet logic judgment formula: (E _raR-E _laR)>=0 ∩ A _e,t>=E _raR∩ A _s,t>=E _laR, the current place of micro-electrical network the first subspace method;

If meet logic judgment formula: (E _raR-E _laR)>=0 ∩ A _e,t>=E _raR∩ A _s,t< E _laR, the current place of micro-electrical network the second subspace method;

If meet logic judgment formula: (E _raR-E _laR)>=0 ∩ E _raR> A _e,t>=E ∩ A _s,t>=E _laR, third state subspace, the current place of micro-electrical network;

If meet logic judgment formula: (E _raR-E _laR)>=0 ∩ E _raR> A _e,t>=E ∩ A _s,t< E _laR, the current place of micro-electrical network the 4th subspace method;

If meet logic judgment formula: (E _raR-E _laR)>=0 ∩ A _e,t< E ∩ A _s,t>=E _laR, the current place of micro-electrical network the 5th subspace method;

If meet logic judgment formula: (E _raR-E _laR)>=0 ∩ A _e,t< E ∩ A _s,t< E _laR, the current place of micro-electrical network the 6th subspace method;

If meet logic judgment formula: (E _raR-E _laR) < 0 ∩ A _s,t>=E _laR∩ A _e,t>=E _raR, the current place of micro-electrical network the 7th subspace method;

If meet logic judgment formula: (E _raR-E _laR) < 0 ∩ A _s,t>=E _laR∩ A _e,t< E _raR, the current place of micro-electrical network the 8th subspace method;

If meet logic judgment formula: (E _raR-E _laR) < 0 ∩ E _laR> A _s,t>=| E| ∩ A _e,t>=E _raR, the current place of micro-electrical network the 9th subspace method;

If meet logic judgment formula: (E _raR-E _laR) < 0 ∩ E _laR> A _s,t>=| E| ∩ A _e,t< E _raR, the current place of micro-electrical network the tenth subspace method;

If meet logic judgment formula: (E _raR-E _laR) < 0 ∩ A _s,t< | E ∩ A _e,t>=E _raR, the current place of micro-electrical network the 11 subspace method;

If meet logic judgment formula: (E _raR-E _laR) < 0 ∩ A _s,t< | E| ∩ A _e,t< E _raR, the tenth two-state subspace, the current place of micro-electrical network;

Wherein, E _raRfor risk standby electric weight, the E of described micro-electrical network within next dispatching cycle _laRfor the risk short of electricity amount of described micro-electrical network within next dispatching cycle, A _s,tfor the reserve of electricity of described micro-electrical network at current time, A _e,tfor the deposited electric weight of described micro-electrical network at current time.

6. computational methods according to claim 5, is characterized in that, described step S5 specifically comprises:

In definite subspace, the regulating power parameter of calculating the imbalance power randomness of dissolving of described micro-electrical network energy-storage system according to following subspace computing formula, the regulating power parameter of the imbalance power randomness of dissolving of described micro-electrical network energy-storage system comprises: described micro-electrical network energy-storage system abandoning within next dispatching cycle can electric weight with off-load electric weight described micro-electrical network energy-storage system is at the A of reserve of electricity of next dispatching cycle end _{s, t+T}with can deposit electric weight A _{e, t+T};

The first subspace method computing formula: a _{s, t+T}=A _s,t+ Δ E, A _{e, t+T}=A _e,t-Δ E;

The second subspace method computing formula: $E_g^0=0,E_L^0\&Element;[0,E_{\mathrm{LaR}}-A_{s,t}],$ A _s,t+T∈[A _s,t+ΔE,E _RaR]、A _e,t+T∈[A－E _RaR,A _e,t－ΔE]；

Third state subspace computing formula: a _{s, t+T}∈ [A-E _laR, A _s,t+ Δ E], A _{e, t+T}∈ [A _e,t-Δ E, E _raR];

The 4th subspace method computing formula: $E_g^0\&Element;[0,E_{\mathrm{RaR}}-A_{e,t}],E_L^0\&Element;[0,E_{\mathrm{LaR}}-A_{s,t}],$ A _s,t+T∈[A－E _LaR,E _RaR]、A _e,t+T∈[A－E _RaR,E _LaR]；

The 5th subspace method computing formula: $E_g^0\&Element;[\mathrm{\&Delta;E}-A_{e,t},E_{\mathrm{RaR}}-A_{e,t}],E_L^0=0,$ A _s,t+T∈[A－E _LaR,A]、A _e,t+T∈[0,E _LaR]；

The 6th subspace method computing formula: $E_g^0\&Element;[\mathrm{\&Delta;E}-A_{e,t},E_{\mathrm{RaR}}-A_{e,t}],E_L^0\&Element;[0,E_{\mathrm{LaR}}$ $-A_{s,t}],$ A _s,t+T∈[A－E _LaR,A]、A _e,t+T∈[0,E _LaR]；

The 7th subspace method computing formula: a _{s, t+T}=A _s,t-| Δ E|, A _{e, t+T}=A _e,t+ | Δ E|;

The 8th subspace method computing formula: a _{s, t+T}∈ [A-E _laR, A _s,t-| Δ E|], A _{e, t+T}∈ [A _e,t+ | Δ E|, E _laR];

The 9th subspace method computing formula: $E_g^0=0,E_L^0\&Element;[0,E_{\mathrm{LaR}}-A_{s,t}],$ A _s,t+T∈[A _s,t-|ΔE|,E _RaR]、A _e,t+T∈[A-E _RaR,A _e,t+|ΔE|]；

The tenth subspace method computing formula: $E_g^0\&Element;[0,E_{\mathrm{RaR}}-A_{e,t}],E_L^0\&Element;[0,E_{\mathrm{LaR}}-A_{s,t}],$ A _s,t+T∈[A－E _LaR,E _RaR]、A _e,t+T∈[A-E _RaR,E _LaR]；

The 11 subspace method computing formula: $E_g^0=0,E_L^0\&Element;\left[\right|\mathrm{\&Delta;E}|-A_{s,t},E_{\mathrm{LaR}}-A_{s,t}],$ A _s,t+T∈[0，E _RaR]、A _e,t+T∈[A-E _RaR,A]；

The tenth two-state subspace computing formula: a _{s, t+T}∈ [0, E _raR], A _{e, t+T}∈ [A-E _raR, A];

Wherein, Δ E=E _raR-E _laR, Δ E is that micro-electrical network is by the electric energy gross spread of random Power supply, E _raRfor the risk standby electric weight of micro-electrical network within next dispatching cycle, E _laRfor the risk short of electricity amount of micro-electrical network within next dispatching cycle, A _{s, t+T}for the reserve of electricity of micro-electrical network energy-storage system in next dispatching cycle end, A _{e, t+T}for the deposited electric weight of micro-electrical network energy-storage system in next dispatching cycle end, for micro-electrical network energy-storage system abandoning within next dispatching cycle can electric weight, for the off-load electric weight of micro-electrical network energy-storage system within next dispatching cycle, A _s,tfor the reserve of electricity of micro-electrical network energy-storage system at current time, A _e,tfor the deposited electric weight of micro-electrical network energy-storage system at current time, A is that micro-electrical network energy-storage system is at the A of reserve of electricity of current time _s,twith can deposit electric weight A _e,tsum.

7. computational methods according to claim 6, is characterized in that, described step S6 specifically comprises the following steps:

According to the described rated capacity with electromechanical source, by formula calculating is with electromechanical source exportable maximum total amount within next dispatching cycle;

According to described maximum total amount G, by formula calculate the exportable electric weight E of micro-electrical network within next dispatching cycle _out;

By formula calculate the inputted electric weight E of micro-electrical network within next dispatching cycle _in;

By formula calculating micro-electrical network abandoning within next dispatching cycle can electric weight E _g;

According to described maximum total amount G, by formula $E_L=\left\{\begin{array}{cc}{E}_{L,\max }^0-G& E_{L,\max }^0>G\\ 0& E_{L,\max }^0\&le;G\end{array}\right.$ Calculate the off-load electric weight E of micro-electrical network within next dispatching cycle _l:

Wherein, for described micro-electrical network energy-storage system abandoning within next dispatching cycle can electric weight maximum, for described micro-electrical network energy-storage system abandoning within next dispatching cycle can electric weight minimum value, for the off-load electric weight of described micro-electrical network energy-storage system within next dispatching cycle minimum value, for the off-load electric weight of described micro-electrical network energy-storage system within next dispatching cycle maximum, A _{s, t+T, min}for the reserve of electricity A of described micro-electrical network energy-storage system in next dispatching cycle end _{s, t+T}minimum value, A _{e, t+T, min}for the minimum value of described micro-electrical network energy-storage system at the electric weight deposited of next dispatching cycle end, P _{gn, j}be j platform with the rated capacity of electromechanical source, T is next dispatching cycle.

8. computational methods according to claim 7, is characterized in that, described exportable electric weight, can be to the electric weight of external power grid output for to meet under the prerequisite of self-demand at micro-electrical network; The described electric weight of inputting is that micro-electrical network can absorb the outside electric weight injecting; Described abandon can electric weight the load that is micro-electrical network and the energy storage maximum residual energy output that can not receive; Described off-load electric weight is the maximum off-load electric weight that micro-electrical network causes due to generation deficiency.