CN103577893A - Energy-saving optimization method for new energy and thermal power bidirectionally supplying power for high energy carrying loads - Google Patents

Abstract

The invention discloses an energy-saving optimization method for new energy and thermal power bidirectionally supplying power for high energy carrying loads. The method comprises the steps of building a model to carry out ultra-short period power prediction on wind electric power data in a future preset time slot, adopting an existing load prediction mathematical model to carrying out ultra-short period power prediction on high energy carrying load data in the future preset time slot, judging whether wind electric power meets the demands of normal production operation of high energy carrying loads in the future preset time slot or not, adopting wind electricity to supply power for the high energy carrying loads directly if the wind electric power meets the demands of the normal production operation of the high energy carrying loads in the future preset time slot, and building an energy-saving optimization model of supplying power for the high energy carrying loads through the new energy and the thermal power bidirectionally if the wind electric power cannot meet the demands of the normal production operation of the high energy carrying loads in the future preset time slot. The energy-saving optimization method for the new energy and the thermal power bidirectionally supplying power for the high energy carrying loads has the advantages of being high in reliability and energy utilization rate, and good in energy-saving effect.

Description

The two-way energy conservation optimizing method for the power supply of high energy load of a kind of new forms of energy and thermoelectricity

Technical field

The present invention relates to new-energy grid-connected technical field, particularly, relate to the two-way energy conservation optimizing method for the power supply of high energy load of a kind of new forms of energy and thermoelectricity.

Background technology

21 century, along with the continuous rising of socioeconomic development and energy demand, the use dynamics to coal, oil, rock gas has been strengthened in countries in the world, because reserves are limited and exploitation increasingly sharpens, will cause the exhaustion of these resources.Meanwhile, combustion of fossil fuels can produce the lasting discharge of the air pollutants, particularly carbon dioxide such as sulphuric dioxide, particulate, and the greenhouse effect by the aggravation earth, cause air pollution, brings negative effect to our living environment.Global energy crisis and environmental destruction become the problem that concerns human survival and development, how to save to utilize the energy, improve its utilization ratio and become the focus that various countries pay close attention to.

Power industry is directly utilized industry as the main primary energy of national basis industry ，Shi China, the basic guarantee that efficiently utilizes the progress of ，Shi social economy and Society of the tremendous development of power industry and electric power.Electric power energy-saving first should be taked more strong sustainable development policy from national energy strategy aspect energy exploitation and application, and Devoting Major Efforts To Developing regenerative resource is adjusted and optimization energy industry structure realization saving under development; Secondly, improve energy conversion and utilization ratio, in fields such as production, transmission and consumption, by taking technology, law, economy and the comprehensive measure such as administrative, raising efficiency of energy utilization, obtains maximum economic and social benefit with minimum resource consumption.

Wind-power electricity generation, as a kind of important regenerative resource form, is one of the most ripe, on the largest scale generation mode that melts clockwork spring part and commercialized development prospect of technology in current regenerative resource.China's wind-powered electricity generation mainly adopts the extensive access way of concentrating, and due to the restriction that wind resource distributes, wind energy turbine set is built the end at electrical network mostly, and network structure is weaker, and wind-powered electricity generation ability to send outside is limited, needs emphasis to consider the on-site elimination of wind-powered electricity generation.Development power load, on-site elimination wind-powered electricity generation, can directly be converted into local economy advantage by local wind power resources advantage, for the sustainable development of Wind Power Generation Industry provides safeguard.And development medium-sized and small enterprises, power load is less, to dissolving a large amount of rich wind-powered electricity generation effects little, therefore, emphasis considers that the larger high energy industry of the development power load wind-powered electricity generation of dissolving will be more effective.But because wind energy has randomness and intermittent feature, making wind-powered electricity generation is that the power supply of high energy load has certain uncertainty, so, consider that the two-way energy saving optimizing scheme for the power supply of high energy load of a kind of new forms of energy and thermoelectricity is particularly important.

In realizing process of the present invention, inventor finds at least to exist in prior art the defect such as reliability is low, energy utilization rate is low and energy-saving effect is poor.

Summary of the invention

The object of the invention is to, for the problems referred to above, propose the two-way energy conservation optimizing method for the power supply of high energy load of a kind of new forms of energy and thermoelectricity, to realize the advantage that reliability is high, energy utilization rate is high and energy-saving effect is poor.

For achieving the above object, the technical solution used in the present invention is: the two-way energy conservation optimizing method for the power supply of high energy load of a kind of new forms of energy and thermoelectricity, comprising:

Step 1: with reference to randomness and the undulatory property of wind, according to historical wind power data, by curve and parameter estimation, set up arma modeling, wind power data in following Preset Time section are carried out to ultra-short term power prediction;

Step 2: the ruuning situation according to high energy load, adopts existing load prediction mathematical model to carry out ultra-short term to the high energy load data in following Preset Time section;

Step 3: according to the predicted data of the predicted data of wind power and high energy load, judge whether wind power in following Preset Time section meets the load needs of normal production run of high energy;

Step 4: if wind power can meet the load needs of normal production run of high energy in following Preset Time section, adopt wind-powered electricity generation directly for high energy load is powered;

Step 5: if wind power cannot meet the load needs of normal production run of high energy in following Preset Time section, take and adopt new forms of energy and the two-way fired power generating unit energy consumption of saving as high energy load power supply station of thermoelectricity to be target to the maximum, consider various constraint condition, set up the two-way energy saving optimizing model for the power supply of high energy load of new forms of energy and thermoelectricity.

Further, after described step 5, also comprise:

Step 6: adopt improvement particle cluster algorithm to solve the energy saving optimizing model in step 4, finally obtain the two-way energy saving optimizing scheme for the power supply of high energy load of new forms of energy and thermoelectricity;

In step 6, described improvement particle cluster algorithm, refers to and makes full use of the global search of particle cluster algorithm and the above-mentioned energy saving optimizing model of the local optimal searching capacity calculation of former-dual interior point.

Further, in step 6, described employing improves the operation that particle cluster algorithm solves the energy saving optimizing model in step 4, specifically comprises:

In the starting stage of optimizing, adopt particle cluster algorithm, the further local optimum of initial value using the particle group optimizing result that approaches global optimum of certain number of times as former-dual interior point, obtains more excellent solution.

Further, in step 6, the described further local optimum of initial value using the particle group optimizing result that approaches global optimum of certain number of times as former-dual interior point, obtains the operation of more excellent solution, specifically comprises:

With PSO Algorithm, contain equation and inequality constrain Large-scale Optimization Problems time, adopt feasibleization to adjust strategy, to not meeting the particle of equality constraint, adjust at every turn;

For multimodal optimization problem, for inertia particle, the continuous particle that approaches population optimal value for n time and substantially do not change, reinitializes to avoid precocious to its speed and occurs; N is natural number;

Using the solution that obtains after global search as initial value, for continuously differentiable Optimized model after smoothing, select convergence property stable and with the increase iterations of the scale of calculating change little non-linear former-dual interior point carries out local optimum, the higher-quality solution of the problem that is optimized.

Further, in step 1, described wind power data in following Preset Time section are carried out to ultra-short term power prediction, are specially:

Based on seasonal effect in time series ultra-short term wind energy Forecasting Methodology, the time series data obtaining according to systematic observation, sets up mathematical model by curve and parameter estimation, and then by this mathematical model, carrys out the data of predict future.

Further, in described seasonal effect in time series ultra-short term wind energy Forecasting Methodology, adopt autoregression moving average arma modeling as seasonal effect in time series model, wind power is predicted;

The structure of described autoregression moving average arma modeling is as follows:

$X_t=\underset{j=1}{\overset{p}{\mathrm{\Σ}}}{a}_j{X}_{t-j}+\underset{k=0}{\overset{q}{\mathrm{\Σ}}}{b}_k{e}_{t-k};$

In formula, X _tfor the time series of wind power, it is a process of ARMA (p, q); a _jfor AR parameter; b _kfor MA parameter; e _t-kfor representing the time series of white-noise process; P and q are respectively AR exponent number and MA exponent number.

Further, in step 2, the existing load prediction mathematical model of described employing is carried out the operation of ultra-short term to the high energy load data in following Preset Time section, specifically comprises:

5min is to the ultra-short term of 60min, and its prediction principle is to utilize existing historical data, adopts suitable mathematical forecasting model to estimate the load value of prediction day; Described historical data comprises historical daily load data and weather data.

Further, in step 5, the two-way energy saving optimizing model for the power supply of high energy load of described new forms of energy and thermoelectricity, is specially:

Take and adopt new forms of energy and the two-way fired power generating unit energy consumption of saving as high energy load power supply station of thermoelectricity to be target to the maximum, consider the Optimized model of the multiple constraint conditions such as power constraint, fired power generating unit technology units limits.

Further, described take adopt that new forms of energy and thermoelectricity are two-way is target to the maximum for the load fired power generating unit energy consumption of power supply station's saving of high energy, consider the operation of the Optimized model of the multiple constraint conditions such as power constraint, fired power generating unit technology units limits, specifically comprise:

The objective function of considering to adopt new forms of energy and the two-way fired power generating unit energy consumption maximum for the saving of high energy load power supply station of thermoelectricity, its mathematical description is as follows:

max C _save；

In formula,

C _save=C ₁-C ₂

；

$C_1=\underset{t=1}{\overset{T}{\mathrm{\Σ}}}\underset{i=1}{\overset{G_1}{\mathrm{\Σ}}}{f}_i\left(p_{g,i}^t\right)=\underset{t=1}{\overset{T}{\mathrm{\Σ}}}\underset{i=1}{\overset{G}{\mathrm{\Σ}}}{a}_i{p}_{g,i}^t+b_i;$

$C_2=\underset{t=1}{\overset{T}{\mathrm{\Σ}}}\underset{j=1}{\overset{G_2}{\mathrm{\Σ}}}g(p_{g,j}^t-p_w^t)=\underset{t=1}{\overset{T}{\mathrm{\Σ}}}\underset{j=1}{\overset{G_2}{\mathrm{\Σ}}}{a}_j^{\′}(p_{g,j}^t-p_w^t)+b_j^{\′};$

According to the operation characteristic of fired power generating unit, fired power generating unit can be divided into base lotus unit and economic load dispatching unit;

When only adopting fired power generating unit to be the power supply of high energy load, because high energy workload demand is comparatively stable, load variations is little, and therefore can adopt the base lotus unit that coal consumption amount is low is the power supply of high energy load; When adopting that new forms of energy and fired power generating unit are two-way powers for high energy load, although new forms of energy do not consume primary energy, the wave characteristic of new forms of energy needs the low base lotus unit of economic load dispatching unit replacement coal consumption amount that coal consumption amount is higher to bear corresponding load;

C _savefor adopting the two-way fired power generating unit coal consumption amount for the saving of high energy load power supply station of new forms of energy and thermoelectricity; C ₁for adopting fired power generating unit, it is the coal consumption amount of high energy load power supply; C ₂for adopting the two-way coal consumption amount for the power supply of high energy load of new forms of energy and thermoelectricity; for the coal consumption amount function of base lotus unit, for the output power of base lotus unit i at period t, a _iand b _ifor the coal consumption amount characteristic coefficient of base lotus unit i, G ₁for base lotus unit number; for the coal consumption amount function of economic load dispatching unit, for the output power of economic load dispatching unit j at period t, a' _jand b' _jcoal consumption amount characteristic coefficient for economic load dispatching unit j; G ₂for economic load dispatching unit number; the wind power predicted value of dissolving for high energy load.

Further, described bound for objective function, comprising:

(1) system power Constraints of Equilibrium:

$\underset{i=1}{\overset{G_1}{\mathrm{\Σ}}}{p}_{g,i}^t+\underset{j=1}{\overset{G_2}{\mathrm{\Σ}}}{p}_{g,j}^t-p_w^t=p_l^t;$

In formula, for load prediction value;

(2) conventional Unit commitment

Genset units limits:

$p_{\min ,i}\≤p_{g,i}^t\≤p_{\max ,i};p_{\min ,j}\≤p_{g,j}^t\≤p_{\max ,j};$

In formula, p _{min, i}, p _{max, i}be respectively minimum load and the maximum output of base lotus unit i; p _{min, j}, p _{max, j}be respectively minimum load and the maximum output of economic load dispatching unit j;

(3) genset climbing rate constraint:

$\left\{\begin{array}{c}{p}_{g,i}^{t-1}-p_{g,i}^t\≤r_{d,i}\\ p_{g,i}^t-p_{g,i}^{t-1}\≤r_{u,i}\end{array}\right.;\left\{\begin{array}{c}{p}_{g,j}^{t-1}-p_{g,j}^t\≤r_{d,j}\\ p_{g,j}^t-p_{g,j}^{t-1}\≤r_{u,j}\end{array}\right.;$

In formula, r _d,i, r _u,ibe respectively descending Ramp Rate and the up Ramp Rate of base lotus unit i; r _d,j, r _u,jbe respectively descending Ramp Rate and the up Ramp Rate of economic load dispatching unit j.

The two-way energy conservation optimizing method for the power supply of high energy load of the new forms of energy of various embodiments of the present invention and thermoelectricity, owing to comprising: set up arma modeling, wind power data in following Preset Time section are carried out to ultra-short term power prediction; Adopt existing load prediction mathematical model to carry out ultra-short term to the high energy load data in following Preset Time section; Judge whether wind power in following Preset Time section meets the load needs of normal production run of high energy; If wind power can meet the load needs of normal production run of high energy in following Preset Time section, adopt wind-powered electricity generation directly for high energy load is powered; If wind power cannot meet the load needs of normal production run of high energy in following Preset Time section, set up the two-way energy saving optimizing model of loading and powering for high energy of new forms of energy and thermoelectricity; Can solve existing high energy supplying charge method and be difficult to improve the problem that new forms of energy are dissolved ability and can not effectively be saved primary energy, improve the level of dissolving of new forms of energy, effectively save primary energy; Thereby can overcome the defect that in prior art, reliability is low, energy utilization rate is low and energy-saving effect is poor, to realize the advantage that reliability is high, energy utilization rate is high and energy-saving effect is poor.

Other features and advantages of the present invention will be set forth in the following description, and, partly from instructions, become apparent, or understand by implementing the present invention.

Below by drawings and Examples, technical scheme of the present invention is described in further detail.

Accompanying drawing explanation

Accompanying drawing is used to provide a further understanding of the present invention, and forms a part for instructions, for explaining the present invention, is not construed as limiting the invention together with embodiments of the present invention.In the accompanying drawings:

Fig. 1 is the schematic flow sheet of the two-way energy conservation optimizing method for the power supply of high energy load of new forms of energy of the present invention and thermoelectricity;

Fig. 2 is wind power prognostic chart in the two-way energy conservation optimizing method that is the power supply of high energy load of new forms of energy of the present invention and thermoelectricity;

Fig. 3 is the two-way power network wiring schematic diagram for IEEE39 node system in the energy conservation optimizing method of high energy load power supply of new forms of energy of the present invention and thermoelectricity.

Embodiment

Below in conjunction with accompanying drawing, the preferred embodiments of the present invention are described, should be appreciated that preferred embodiment described herein, only for description and interpretation the present invention, is not intended to limit the present invention.

For existing high energy supplying charge method, be difficult to improve the problem that new forms of energy are dissolved ability and can not effectively be saved primary energy, according to the embodiment of the present invention, as shown in Figure 1-Figure 3, provide a kind of new forms of energy and thermoelectricity the two-way energy conservation optimizing method for the power supply of high energy load, improve the level of dissolving of new forms of energy, effectively saved primary energy.

The two-way energy conservation optimizing method for the power supply of high energy load of the new forms of energy of the present embodiment and thermoelectricity, comprising:

Step 1: with reference to randomness and the undulatory property of wind, according to historical wind power data, by curve and parameter estimation, set up arma modeling, wind power data in following Preset Time section are carried out to ultra-short term power prediction;

In step 1, wind power prediction refers to: based on seasonal effect in time series ultra-short term wind energy Forecasting Methodology, the time series data that should obtain according to systematic observation based on seasonal effect in time series ultra-short term wind energy Forecasting Methodology, by curve and parameter estimation, set up mathematical model, and then by this mathematical model, carry out the data of predict future.Seasonal effect in time series types of models is a lot, adopts autoregression moving average (ARMA) model to predict wind power here.ARMA (p, q) model structure is as follows:

$X_t=\underset{j=1}{\overset{p}{\mathrm{\Σ}}}{a}_j{X}_{t-j}+\underset{k=0}{\overset{q}{\mathrm{\Σ}}}{b}_k{e}_{t-k};$

In formula, X _tfor the time series of wind power, it is a process of ARMA (p, q); a _jfor AR parameter; b _kfor MA parameter; e _t-kfor representing the time series of white-noise process; P and q are respectively AR exponent number and MA exponent number;

Step 2: the ruuning situation according to high energy load, adopts existing load prediction mathematical model to carry out ultra-short term to the high energy load data in following Preset Time section;

In step 2, load prediction refers to: 5min is to the ultra-short term of 60min, its prediction principle is to utilize existing historical data (historical daily load data and weather data etc.), adopts suitable mathematical forecasting model to estimate the load value of prediction day;

In step 2, load prediction mathematical model is techniques well known, and current existing Short-term Load Forecasting Model mainly contains time series predicting model, Regression Model, Artificial Neural Network Prediction Model, wavelet analysis forecast model etc.List of references: the research > > [master thesis] of the power-system short-term load forecasting method of < < based on load decomposition, Wang Chenggang, Hebei: North China Electric Power University, 2006;

Step 3: according to the predicted data of the predicted data of wind power and high energy load, judge whether wind power in following Preset Time section meets the load needs of normal production run of high energy;

Step 4: if wind power can meet the load needs of normal production run of high energy in following Preset Time section, adopt wind-powered electricity generation directly for high energy load is powered;

Step 5: if wind power cannot meet the load needs of normal production run of high energy in following Preset Time section, take and adopt new forms of energy and the two-way fired power generating unit energy consumption of saving as high energy load power supply station of thermoelectricity to be target to the maximum, consider various constraint condition, set up the two-way energy saving optimizing model for the power supply of high energy load of new forms of energy and thermoelectricity;

In step 5, the two-way energy saving optimizing model for the power supply of high energy load of new forms of energy and thermoelectricity refers to adopt new forms of energy and the two-way fired power generating unit energy consumption of saving for high energy load power supply station of thermoelectricity to be target to the maximum, considers the Optimized model of the multiple constraint conditions such as power constraint, fired power generating unit technology units limits.Specifically comprise:

The objective function of considering to adopt new forms of energy and the two-way fired power generating unit energy consumption maximum for the saving of high energy load power supply station of thermoelectricity, its mathematical description is as follows:

max C _save；

In formula,

C _save=C ₁-C ₂

；

$C_1=\underset{t=1}{\overset{T}{\mathrm{\&Sigma;}}}\underset{i=1}{\overset{G_1}{\mathrm{\&Sigma;}}}{f}_i\left(p_{g,i}^t\right)=\underset{t=1}{\overset{T}{\mathrm{\&Sigma;}}}\underset{i=1}{\overset{G}{\mathrm{\&Sigma;}}}{a}_i{p}_{g,i}^t+b_i;$

$C_2=\underset{t=1}{\overset{T}{\mathrm{\&Sigma;}}}\underset{j=1}{\overset{G_2}{\mathrm{\&Sigma;}}}g(p_{g,j}^t-p_w^t)=\underset{t=1}{\overset{T}{\mathrm{\&Sigma;}}}\underset{j=1}{\overset{G_2}{\mathrm{\&Sigma;}}}{a}_j^{\&prime;}(p_{g,j}^t-p_w^t)+b_j^{\&prime;};$

According to the operation characteristic of fired power generating unit, fired power generating unit can be divided into base lotus unit and economic load dispatching unit.The coal consumption amount of base lotus unit is low, and dynamic response capability is poor, is applicable to on-load and changes less base lotus; The dynamic response capability of economic load dispatching unit is strong, and coal consumption amount is higher, is applicable to doing spinning reserve, participatory economy scheduling or frequency modulation etc.When only adopting fired power generating unit to be the power supply of high energy load, because high energy workload demand is comparatively stable, load variations is little, and therefore can adopt the base lotus unit that coal consumption amount is low is the power supply of high energy load; When adopting that new forms of energy and fired power generating unit are two-way powers for high energy load, although new forms of energy do not consume primary energy, the wave characteristic of new forms of energy needs the low base lotus unit of economic load dispatching unit replacement coal consumption amount that coal consumption amount is higher to bear corresponding load.C _savefor adopting the two-way fired power generating unit coal consumption amount for the saving of high energy load power supply station of new forms of energy and thermoelectricity; C ₁for adopting fired power generating unit, it is the coal consumption amount of high energy load power supply; C ₂for adopting the two-way coal consumption amount for the power supply of high energy load of new forms of energy and thermoelectricity; for the coal consumption amount function of base lotus unit, for the output power of base lotus unit i at period t, a _iand b _ifor the coal consumption amount characteristic coefficient of base lotus unit i, G ₁for base lotus unit number; for the coal consumption amount function of economic load dispatching unit, for the output power of economic load dispatching unit j at period t, a' _jand b' _jcoal consumption amount characteristic coefficient for economic load dispatching unit j; G ₂for economic load dispatching unit number; the wind power predicted value of dissolving for high energy load.

Above-mentioned bound for objective function is:

(1) system power Constraints of Equilibrium:

$\underset{i=1}{\overset{G_1}{\mathrm{\&Sigma;}}}{p}_{g,i}^t+\underset{j=1}{\overset{G_2}{\mathrm{\&Sigma;}}}{p}_{g,j}^t-p_w^t=p_l^t;$

In formula, for load prediction value.

(2) conventional Unit commitment

Genset units limits:

$p_{\min ,i}\&le;p_{g,i}^t\&le;p_{\max ,i};p_{\min ,j}\&le;p_{g,j}^t\&le;p_{\max ,j};$

In formula, p _{min, i}, p _{max, i}be respectively minimum load and the maximum output of base lotus unit i; p _{min, j}, p _{max, j}be respectively minimum load and the maximum output of economic load dispatching unit j.

(3) genset climbing rate constraint:

$\left\{\begin{array}{c}{p}_{g,i}^{t-1}-p_{g,i}^t\&le;r_{d,i}\\ p_{g,i}^t-p_{g,i}^{t-1}\&le;r_{u,i}\end{array}\right.;\left\{\begin{array}{c}{p}_{g,j}^{t-1}-p_{g,j}^t\&le;r_{d,j}\\ p_{g,j}^t-p_{g,j}^{t-1}\&le;r_{u,j}\end{array}\right.;$

In formula, r _d,i, r _u,ibe respectively descending Ramp Rate and the up Ramp Rate of base lotus unit i; r _d,j, r _u,jbe respectively descending Ramp Rate and the up Ramp Rate of economic load dispatching unit j;

Step 6: adopt improvement particle cluster algorithm to solve the energy saving optimizing model in step 4, finally obtain the two-way energy saving optimizing scheme for the power supply of high energy load of new forms of energy and thermoelectricity;

In step 6, improve particle cluster algorithm and refer to: make full use of the global search of particle cluster algorithm and the above-mentioned energy saving optimizing model of the local optimal searching capacity calculation of former-dual interior point.In the starting stage of optimizing, adopt particle cluster algorithm, the further local optimum of initial value using the particle group optimizing result that approaches global optimum of certain number of times as former-dual interior point, thus obtain more excellent solution.

In step 6, while adopting the Large-scale Optimization Problems that PSO Algorithm contains equation and inequality constrain, feasible zone is conventionally narrower and small, in optimizing process, be difficult to meet fast the especially requirement of equality constraint of institute's Constrained, therefore, adopt feasibleization to adjust strategy, to not meeting the particle of equality constraint, adjust at every turn.

In step 6, for multimodal optimization problem, may there is precocious phenomenon in particle cluster algorithm, make optimization be absorbed in local optimum, therefore, for inertia particle, be the continuous particle that approaches population optimal value for n time and substantially do not change, its speed reinitialized to avoid precocious and occur.

In step 6, using the solution that obtains after global search as initial value, for continuously differentiable Optimized model after smoothing, select convergence property stable and with the increase iterations of the scale of calculating change little non-linear former-dual interior point carries out local optimum, thereby the higher-quality solution of the problem that is optimized.

According to the new forms of energy of above-described embodiment and the two-way energy conservation optimizing method for the power supply of high energy load of thermoelectricity, using IEEE39 node system as Knowledge Verification Model, be analyzed as follows:

By contrast, only adopting fired power generating unit is that high energy supplying charge formula is high energy supplying charge formula with adopting new forms of energy and thermoelectricity two-way, can find out, when only adopting fired power generating unit to be the power supply of high energy load, the coal consumption amount of fired power generating unit is 520.178t, and adopt, new forms of energy and thermoelectricity are two-way loads while powering for high energy, the coal consumption amount of fired power generating unit is 495.154t, has saved the coal consumption amount of 25.024t, thereby can effectively reduce the primary energy consumption amount of system.

Above-mentioned instance analysis shows: the two-way energy conservation optimizing method for the power supply of high energy load of the new forms of energy of the various embodiments described above of the present invention and thermoelectricity, solve existing high energy supplying charge method and be difficult to improve the problem that new forms of energy are dissolved ability and can not effectively be saved primary energy, on the basis of load prediction and wind power prediction, set up the energy saving optimizing model of new forms of energy and thermoelectricity bidirectional power supply, and provided corresponding energy saving optimizing scheme, thereby improved the level of dissolving of new forms of energy, effectively saved primary energy.

In sum, the two-way energy conservation optimizing method for the power supply of high energy load of the new forms of energy of the various embodiments described above of the present invention and thermoelectricity, comprise: according to historical wind power data, by arma modeling, wind power data in following Preset Time section are carried out to ultra-short term power prediction; Ruuning situation according to high energy load, adopts existing load prediction mathematical model to carry out ultra-short term to the high energy load data in following Preset Time section; In following Preset Time section, wind power cannot meet the load needs of normal production run of high energy, take and adopt new forms of energy and the two-way fired power generating unit energy consumption of saving as high energy load power supply station of thermoelectricity to be target to the maximum, consider various constraint condition, set up the two-way energy saving optimizing model for the power supply of high energy load of new forms of energy and thermoelectricity, and adopt improvement particle cluster algorithm to solve this model, finally obtain the two-way energy saving optimizing scheme for the power supply of high energy load of new forms of energy and thermoelectricity.

Finally it should be noted that: the foregoing is only the preferred embodiments of the present invention, be not limited to the present invention, although the present invention is had been described in detail with reference to previous embodiment, for a person skilled in the art, its technical scheme that still can record aforementioned each embodiment is modified, or part technical characterictic is wherein equal to replacement.Within the spirit and principles in the present invention all, any modification of doing, be equal to replacement, improvement etc., within all should being included in protection scope of the present invention.

Claims (10)

1. the two-way energy conservation optimizing method for the power supply of high energy load of new forms of energy and thermoelectricity, is characterized in that, comprising:

Step 1: with reference to randomness and the undulatory property of wind, according to historical wind power data, by curve and parameter estimation, set up arma modeling, wind power data in following Preset Time section are carried out to ultra-short term power prediction;

Step 2: the ruuning situation according to high energy load, adopts existing load prediction mathematical model to carry out ultra-short term to the high energy load data in following Preset Time section;

Step 3: according to the predicted data of the predicted data of wind power and high energy load, judge whether wind power in following Preset Time section meets the load needs of normal production run of high energy;

Step 4: if wind power can meet the load needs of normal production run of high energy in following Preset Time section, adopt wind-powered electricity generation directly for high energy load is powered;

Step 5: if wind power cannot meet the load needs of normal production run of high energy in following Preset Time section, take and adopt new forms of energy and the two-way fired power generating unit energy consumption of saving as high energy load power supply station of thermoelectricity to be target to the maximum, consider various constraint condition, set up the two-way energy saving optimizing model for the power supply of high energy load of new forms of energy and thermoelectricity.

2. the two-way energy conservation optimizing method for the power supply of high energy load of new forms of energy according to claim 1 and thermoelectricity, is characterized in that, after described step 5, also comprises:

Step 6: adopt improvement particle cluster algorithm to solve the energy saving optimizing model in step 4, finally obtain the two-way energy saving optimizing scheme for the power supply of high energy load of new forms of energy and thermoelectricity;

In step 6, described improvement particle cluster algorithm, refers to and makes full use of the global search of particle cluster algorithm and the above-mentioned energy saving optimizing model of the local optimal searching capacity calculation of former-dual interior point.

3. the two-way energy conservation optimizing method for the power supply of high energy load of new forms of energy according to claim 2 and thermoelectricity, is characterized in that, in step 6, described employing improves the operation that particle cluster algorithm solves the energy saving optimizing model in step 4, specifically comprises:

In the starting stage of optimizing, adopt particle cluster algorithm, the further local optimum of initial value using the particle group optimizing result that approaches global optimum of certain number of times as former-dual interior point, obtains more excellent solution.

4. the two-way energy conservation optimizing method for high energy load power supply of new forms of energy according to claim 3 and thermoelectricity, it is characterized in that, in step 6, the described further local optimum of initial value using the particle group optimizing result that approaches global optimum of certain number of times as former-dual interior point, obtain the operation of more excellent solution, specifically comprise:

With PSO Algorithm, contain equation and inequality constrain Large-scale Optimization Problems time, adopt feasibleization to adjust strategy, to not meeting the particle of equality constraint, adjust at every turn;

For multimodal optimization problem, for inertia particle, the continuous particle that approaches population optimal value for n time and substantially do not change, reinitializes to avoid precocious to its speed and occurs; N is natural number;

Using the solution that obtains after global search as initial value, for continuously differentiable Optimized model after smoothing, select convergence property stable and with the increase iterations of the scale of calculating change little non-linear former-dual interior point carries out local optimum, the higher-quality solution of the problem that is optimized.

5. according to the new forms of energy described in any one in claim 1-4 and the two-way energy conservation optimizing method for the power supply of high energy load of thermoelectricity, it is characterized in that, in step 1, described wind power data in following Preset Time section are carried out to ultra-short term power prediction, be specially:

Based on seasonal effect in time series ultra-short term wind energy Forecasting Methodology, the time series data obtaining according to systematic observation, sets up mathematical model by curve and parameter estimation, and then by this mathematical model, carrys out the data of predict future.

6. the two-way energy conservation optimizing method for high energy load power supply of new forms of energy according to claim 5 and thermoelectricity, it is characterized in that, in step 1, in described seasonal effect in time series ultra-short term wind energy Forecasting Methodology, adopt autoregression moving average arma modeling as seasonal effect in time series model, wind power is predicted;

The structure of described autoregression moving average arma modeling is as follows:

$X_t=\underset{j=1}{\overset{p}{\mathrm{\&Sigma;}}}{a}_j{X}_{t-j}+\underset{k=0}{\overset{q}{\mathrm{\&Sigma;}}}{b}_k{e}_{t-k};$

In formula, X _tfor the time series of wind power, it is a process of ARMA (p, q); a _jfor AR parameter; b _kfor MA parameter; e _t-kfor representing the time series of white-noise process; P and q are respectively AR exponent number and MA exponent number.

7. according to the new forms of energy described in any one in claim 1-4 and the two-way energy conservation optimizing method for the power supply of high energy load of thermoelectricity, it is characterized in that, in step 2, the existing load prediction mathematical model of described employing is carried out the operation of ultra-short term to the high energy load data in following Preset Time section, specifically comprises:

5min is to the ultra-short term of 60min, and its prediction principle is to utilize existing historical data, adopts suitable mathematical forecasting model to estimate the load value of prediction day; Described historical data comprises historical daily load data and weather data.

8. according to the new forms of energy described in any one in claim 1-4 and the two-way energy conservation optimizing method for the power supply of high energy load of thermoelectricity, it is characterized in that, in step 5, the two-way energy saving optimizing model for the power supply of high energy load of described new forms of energy and thermoelectricity, is specially:

Take and adopt new forms of energy and the two-way fired power generating unit energy consumption of saving as high energy load power supply station of thermoelectricity to be target to the maximum, consider the Optimized model of the multiple constraint conditions such as power constraint, fired power generating unit technology units limits.

9. the two-way energy conservation optimizing method for high energy load power supply of new forms of energy according to claim 8 and thermoelectricity, it is characterized in that, described take adopt that new forms of energy and thermoelectricity are two-way is target to the maximum for the load fired power generating unit energy consumption of power supply station's saving of high energy, consider the operation of the Optimized model of the multiple constraint conditions such as power constraint, fired power generating unit technology units limits, specifically comprise:

The objective function of considering to adopt new forms of energy and the two-way fired power generating unit energy consumption maximum for the saving of high energy load power supply station of thermoelectricity, its mathematical description is as follows:

max C _save；

In formula,

C _save=C ₁-C ₂

；

$C_1=\underset{t=1}{\overset{T}{\mathrm{\&Sigma;}}}\underset{i=1}{\overset{G_1}{\mathrm{\&Sigma;}}}{f}_i\left(p_{g,i}^t\right)=\underset{t=1}{\overset{T}{\mathrm{\&Sigma;}}}\underset{i=1}{\overset{G}{\mathrm{\&Sigma;}}}{a}_i{p}_{g,i}^t+b_i;$

$C_2=\underset{t=1}{\overset{T}{\mathrm{\&Sigma;}}}\underset{j=1}{\overset{G_2}{\mathrm{\&Sigma;}}}g(p_{g,j}^t-p_w^t)=\underset{t=1}{\overset{T}{\mathrm{\&Sigma;}}}\underset{j=1}{\overset{G_2}{\mathrm{\&Sigma;}}}{a}_j^{\&prime;}(p_{g,j}^t-p_w^t)+b_j^{\&prime;};$

According to the operation characteristic of fired power generating unit, fired power generating unit can be divided into base lotus unit and economic load dispatching unit;

When only adopting fired power generating unit to be the power supply of high energy load, because high energy workload demand is comparatively stable, load variations is little, and therefore can adopt the base lotus unit that coal consumption amount is low is the power supply of high energy load; When adopting that new forms of energy and fired power generating unit are two-way powers for high energy load, although new forms of energy do not consume primary energy, the wave characteristic of new forms of energy needs the low base lotus unit of economic load dispatching unit replacement coal consumption amount that coal consumption amount is higher to bear corresponding load;

C _savefor adopting the two-way fired power generating unit coal consumption amount for the saving of high energy load power supply station of new forms of energy and thermoelectricity; C ₁for adopting fired power generating unit, it is the coal consumption amount of high energy load power supply; C ₂for adopting the two-way coal consumption amount for the power supply of high energy load of new forms of energy and thermoelectricity; for the coal consumption amount function of base lotus unit, for the output power of base lotus unit i at period t, a _iand b _ifor the coal consumption amount characteristic coefficient of base lotus unit i, G ₁for base lotus unit number; for the coal consumption amount function of economic load dispatching unit, for the output power of economic load dispatching unit j at period t, a' _jand b' _jcoal consumption amount characteristic coefficient for economic load dispatching unit j; G ₂for economic load dispatching unit number; the wind power predicted value of dissolving for high energy load.

10. the two-way energy conservation optimizing method for the power supply of high energy load of new forms of energy according to claim 9 and thermoelectricity, is characterized in that, described bound for objective function, comprising:

(1) system power Constraints of Equilibrium:

$\underset{i=1}{\overset{G_1}{\mathrm{\&Sigma;}}}{p}_{g,i}^t+\underset{j=1}{\overset{G_2}{\mathrm{\&Sigma;}}}{p}_{g,j}^t-p_w^t=p_l^t;$

In formula, for load prediction value;

(2) conventional Unit commitment

Genset units limits:

$p_{\min ,i}\&le;p_{g,i}^t\&le;p_{\max ,i};p_{\min ,j}\&le;p_{g,j}^t\&le;p_{\max ,j};$

In formula, p _{min, i}, p _{max, i}be respectively minimum load and the maximum output of base lotus unit i; p _{min, j}, p _{max, j}be respectively minimum load and the maximum output of economic load dispatching unit j;

(3) genset climbing rate constraint:

$\left\{\begin{array}{c}{p}_{g,i}^{t-1}-p_{g,i}^t\&le;r_{d,i}\\ p_{g,i}^t-p_{g,i}^{t-1}\&le;r_{u,i}\end{array}\right.;\left\{\begin{array}{c}{p}_{g,j}^{t-1}-p_{g,j}^t\&le;r_{d,j}\\ p_{g,j}^t-p_{g,j}^{t-1}\&le;r_{u,j}\end{array}\right.;$

In formula, r _d,i, r _u,ibe respectively descending Ramp Rate and the up Ramp Rate of base lotus unit i; r _d,j, r _u,jbe respectively descending Ramp Rate and the up Ramp Rate of economic load dispatching unit j.