CN109754335B - High-proportion new energy consumption method based on load alignment - Google Patents
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Abstract
The invention discloses a high proportion new energy consumption method based on load alignment in the power system and the automation technology field, which comprises extracting the shape of DR user load curve, calculating load alignment, establishing a model for measuring the similarity between the user actual load curve shape and the load alignment, providing a new concept, an algorithm and an alignment similarity index of the load alignment, using the alignment similarity index as a benefit evaluation index of the user participating in DR, leading the load alignment in large-scale DR, being the target of user response and the basis of benefit evaluation, having no relation with the user attribute, depending on the operation state of the power generation side, needing a large amount of user information when comparing with the load baseline calculation, the load alignment is easier to obtain, and easier to dispersedly deploy and lead the user to improve the power utilization mode through a regulating mode from bottom to top and the user self-optimization, thereby promoting the consumption of new energy.
Description
Technical Field
The invention relates to the technical field of power systems and automation thereof, in particular to a high-proportion new energy consumption method based on load alignment.
Background
China actively promotes the development of new energy, the accumulated installed machine is at the top of the world, but the phenomena of wind and light abandonment are also very serious. High-proportion new energy grid connection is a basic characteristic of a future power system, and how to improve the capability of the system for accepting large-scale new energy is one of the most important research problems at present.
The system for absorbing large-scale new energy has enough regulation capacity, and the insufficient peak regulation capacity can cause the phenomena of wind and light abandonment. However, in future power systems, a large number of conventional power sources are replaced by new energy power generation, and the system regulation capacity is very limited. Under the condition of not considering large amount of electric energy to be sent out or input, the conventional power supply does not only need to follow the load change, but also balances the fluctuation of the new energy, when the superposed fluctuation exceeds the regulation range of the system, the output of the new energy needs to be controlled to ensure the dynamic balance of the system, otherwise, wind and light abandoning is generated. It follows that relying solely on the regulation capability of a conventional power source, the system will have difficulty accommodating a high proportion of new energy.
Demand Response (DR) enables flexible loads in the system to participate in supply and Demand balance adjustment, adjustable space is added to the system, and the method is an effective way for promoting new energy consumption. In recent years, scholars at home and abroad have gained abundant research results in the field, and the technology can be mainly divided into two major aspects, namely how to implement DR and how to improve the system operation capacity by DR. In terms of how DR is implemented, DR is generally classified into two categories, electricity price-based and incentive-based.
Price-based DR leverages electricity prices to reflect wholesale side dynamic electricity prices to the retail side, indirectly adjusting supply and demand balance. Common pricing type DR includes time-of-use electricity prices, peak electricity prices, real-time electricity prices, etc., and incentive type DR includes interruptible loads, direct load control, peak subsidy, bonus ticket issuance, etc. Compared with the DR based on the electricity price, the incentive type DR does not relate to the basic electricity price, the influence on other links of the electric power market is small, a user does not face the risk of benefit loss, a large number of users are attracted to participate easily, and the contribution of a Load base line (CBL) to the user is widely adopted for evaluation by the current incentive type DR, and the method is also the basis for implementing the DR.
Although DR has been studied very extensively, the various mechanisms proposed at present mainly aim at reducing load spikes or improving the operating capability of the microgrid, and thus the range of implementation emphasizes a small percentage of user groups in the system, the frequency of implementation is low, and the implementation is usually carried out only in a specific period. In a future power system, the new energy accounts for more than 40% or even more, the adjustable resources are very limited, the promotion of the consumption of the new energy is the primary target for implementing DR, DR is developed for massive users, the load proportion participating in response is greatly improved, and normalized implementation is realized. Considering that the most important characteristic of the DR mechanism for promoting new energy consumption, namely, the DR mechanism is popularized and implemented on a large scale at the user side, and the DR mechanism which is currently researched is referred to as locally implemented DR, so that the DR mechanism is suitable for the new energy power system which is called as large-scale DR in the future, a mechanism for converting locally implemented DR into large-scale DR is urgently needed to be provided.
Disclosure of Invention
The present invention is directed to provide a high-ratio new energy consumption method based on load guideline, so as to solve the above-mentioned problems in the background art that it is urgently needed to provide a mechanism for local implementation of DR to large-scale DR transition.
In order to achieve the purpose, the invention provides the following technical scheme: a high-proportion new energy consumption method based on a load guideline comprises the following steps:
and 3, establishing a model for measuring the similarity between the actual load curve shape of the user and the load alignment.
Preferably, in step 1, the shape of the DR user load curve is extracted, specifically,
1-1) recording l (T) as a load curve, the total electric quantity in the time period T is
1-2) defining a normalized load curve l*(t)＝fu(l(t))＝l(t)/αt＝1,2,…,T，l*(t) load curve l (t) normalized by algorithm fuAfter (-) the load curve is characterized by magnitude elimination, and the curve shape is characterized by retention.
Preferably, in step 2, a load guideline is calculated, specifically,
2-1) establishing an objective function of economic dispatching;
2-2) establishing a constraint.
Preferably, in step 2-1), the objective function of the economic dispatch is:
wherein,
the active power output of the ith adjustable generator in the system in the t period is shown, and N is totalGA stage adjustable generator; pR(t) the output of all photovoltaic and wind power new energy power generation in the system in a time period t; pR.max(t) is the maximum value of the new energy output in the time period t, and can be obtained by prediction in the day ahead; a isi,bi,ciFee for ith controllable unitUsing the first term of the coefficient and the objective function, i.e. the sum of the operating costs of all controllable generator sets, CRThe second term of the objective function, namely the cost generated by not consuming the new energy, is the cost for wind and light abandoning, and the cost for fully consuming the new energy CRSetting to a very large coefficient will only incur wind and light curtailment costs if the constraints are difficult to satisfy.
Preferably, in step 2-2), the non-adjustable new energy power generation and the non-responsive demand-side resource are balanced by using the flexibly controllable power generation resource and the responsive demand-side resource, that is:
PD(t) and PC(t) power consumption for all loads participating in and not participating in DR within the system during time t, respectively;
is according to the formula to PD(t) value to be converted, aDI.e. the total power consumption of the load participating in DR during the period T.
The constraint conditions are as follows:
Preferably, step 3, a model for measuring the similarity between the actual load curve shape of the user and the load alignment is established, specifically,
wherein l*(t) is the normalized value of the load curve to be measured according to the formula, d is the Euclidean distance of the two sequences, E is the conversion of the Euclidean distance to (0, 1)]Metric index after interval.
Compared with the prior art, the invention has the beneficial effects that: the invention provides a new concept, an algorithm and a guideline similarity index of a load guideline, the guideline similarity index is used as a benefit evaluation index of a user participating in DR, the load guideline plays a guiding role in large-scale DR, is a target of user response and is a basis of benefit evaluation, the determination of the load guideline is irrelevant to the user attribute and depends on the running state of a power generation side, compared with the condition that a large amount of user information is needed when a load baseline is calculated, the load guideline is easier to obtain, and the user is easier to be deployed and guided in a decentralized mode to improve the electricity utilization mode through a regulating mode from bottom to top in which the user tends to be optimal, thereby promoting the consumption of new energy.
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In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a schematic view of a load alignment of the present invention;
FIG. 2 is a schematic diagram showing the variation trend of the amount of abandoned wind and abandoned light with E according to the present invention;
FIG. 3 is a net load curve corresponding to different alignment similarity degrees E according to the present invention;
fig. 4 is a new energy consumption curve corresponding to different alignment similarity E according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The invention provides a technical scheme that: a high-proportion new energy consumption method based on a load guideline comprises the following steps:
and 3, establishing a model for measuring the similarity between the actual load curve shape of the user and the load alignment.
Preferably, in step 1, the shape of the DR user load curve is extracted, specifically,
1-1) recording l (T) as a load curve, the total electric quantity in the time period T is
1-2) defining a normalized load curve l*(t)＝fu(l(t))＝l(t)/αt＝1,2,…,T，l*(t) load curve l (t) normalized by algorithm fuAfter (-) the load curve is characterized by magnitude elimination, and the curve shape is characterized by retention.
Preferably, in step 2, a load guideline is calculated, specifically,
2-1) establishing an objective function of economic dispatching;
2-2) establishing a constraint.
Preferably, in step 2-1), considering that most of current DR projects consider that a load aggregation business integrates a certain magnitude of load, and then develop DR of a macro layer with a power company and the like, at a system level, ISO and a power company control center can be generally used as a DR center, which aims to completely consume new energy and minimize operating cost, and an objective function of economic scheduling is as follows:
wherein,
the active power output of the ith adjustable generator in the system in the t period is shown, and N is totalGA stage adjustable generator; pR(t) the output of all photovoltaic and wind power new energy power generation in the system in a time period t; pR.max(t) is the maximum value of the new energy output in the time period t, and can be obtained by prediction in the day ahead; a isi,bi,ciFor the cost coefficient of the ith controllable generator set, the first term of the objective function, i.e. the sum of the operating costs of all controllable generator sets, CRThe second term of the objective function, namely the cost generated by not consuming the new energy, is the cost for wind and light abandoning, and the cost for fully consuming the new energy CRSetting to a very large coefficient will only incur wind and light curtailment costs if the constraints are difficult to satisfy.
Preferably, in step 2-2), the non-adjustable new energy power generation and the non-responsive demand-side resource are balanced by using the flexibly controllable power generation resource and the responsive demand-side resource, that is:
PD(t) and PC(t) power consumption for all loads participating in and not participating in DR within the system during time t, respectively;
is according to the formula to PD(t) value to be converted, aDI.e. the total power consumption of the load participating in DR during the period T.
The constraint conditions are as follows:
at this point, the load curve shape of the ideal DR user which can sufficiently absorb new energy can be solved, that is, the load curve shape of the ideal DR user can be obtained
As a load guideline, a DR center, such as a power regulation center, only needs to publish the load guideline publicly, and all users participating in DR change own power utilization modes and promote the current situation of own load curves to be close to the load guideline under the excitation.
The DR center only issues a determined load alignment, which is a curve only reflecting curve shape characteristics but neglecting magnitude characteristics, and is the same for all users participating in DR, so that unfairness caused by inaccurate or deliberate change is avoided, and the promotion effect on new energy consumption can be ensured.
Preferably, step 3, a model for measuring the similarity between the actual load curve shape of the user and the load alignment is established, specifically,
wherein l*(t) is the normalized value of the load curve to be measured according to the formula, d is the Euclidean distance of the two sequences, E is the conversion of the Euclidean distance to (0, 1)]Metric index after interval.
The measurement mode based on the Euclidean distance belongs to the existing application, and the measurement of the degree of closeness of the actual load curve of the user and the alignment line is objective and reliable. The index E reflects the promotion effect of the load curve on the new energy consumption, the incentive which can be obtained by the DR user is calculated according to the index, the larger the index E is, namely, the more contribution of the user to the promotion of the new energy consumption is shown, the more incentive is obtained, the maximum incentive is obtained when the boundary condition is that the E is 1, and no incentive can be obtained when the E → 0.
One specific application of this embodiment is: the DR center needs to calculate a load guideline according to the controllable unit parameters, the new energy data to be consumed, the non-DR load data and the total load participating in DR, and the result is shown in fig. 1.
After receiving the load guideline, the aggregator or other large users can adjust their own power utilization modes as much as possible to improve the similarity between their own load curves and the guideline, i.e. improve the index E, to obtain more incentives, simulate the decision process of the aggregator, and gradually improve Δ E until E is 1, to obtain 10 groups of incremental E; after the shaped load curve is obtained, the corresponding wind curtailment and light curtailment amount is calculated by considering an economic dispatching algorithm for dispatching new energy preferentially, and the result is shown in fig. 2. With the improvement of the similarity degree E, the wind abandoning light abandoning amount is obviously reduced, and when the DR user shapes the load curve and is completely consistent with the load standard line, the new energy can be completely absorbed.
In a high-proportion new energy power system, if the delivery of electric energy is not considered, under the condition that the regulation capacity of a conventional power supply is certain, the consumption capacity of new energy mainly depends on the net load in the system. Assuming that the new energy source is completely consumed, the net load is formed by adding the actual load to the new energy source to be consumed, which is also a regulation task required to be undertaken by the conventional power supply. If the net load is within the regulation range of the conventional power supply, the new energy can be completely consumed; if the net load fluctuation range is too large and exceeds the conventional power supply regulation range, wind and light abandoning can be generated. Fig. 3 and 4 are a net load curve corresponding to different guideline similarity indexes E and a new energy output curve that can be practically absorbed in economic dispatch, respectively. As can be seen in fig. 3, when the index E is low, the net load curve is lower than the lower limit of the peak-shaving capacity of the system (3:00-7:00), and when such a problem occurs, the system dispatcher must choose to limit the output of the new energy to ensure the peak-shaving capacity of the system; correspondingly, it can be found in fig. 4 that the electric quantity actually consumed by the new energy at this time is far lower than the upper limit of the new energy output, and the wind and light abandoning phenomena also exist. In addition, when the index E is low, the change rate of the net load may be very high and exceed the maximum climbing capability of the controllable unit, for example, in the time periods of 9:00-11:00, 12:00-14:00, and the like; in fig. 3, the wind and light abandoning phenomenon may occur in this period and several periods before this period.
In the description herein, references to the description of "one embodiment," "an example," "a specific example" or the like are intended to mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
The preferred embodiments of the invention disclosed above are intended to be illustrative only. The preferred embodiments are not intended to be exhaustive or to limit the invention to the precise embodiments disclosed. Obviously, many modifications and variations are possible in light of the above teaching. The embodiments were chosen and described in order to best explain the principles of the invention and the practical application, to thereby enable others skilled in the art to best utilize the invention. The invention is limited only by the claims and their full scope and equivalents.
Claims (1)
1. A high-proportion new energy consumption method based on load alignment is characterized in that: the method comprises the following steps:
step 1, extracting the shape of a DR user load curve;
step 2, calculating a load alignment;
step 3, establishing a model for measuring the similarity between the actual load curve shape of the user and the load alignment;
in the step 1, the shape of the DR user load curve is extracted, specifically:
1-1) recording l (T) as a load curve, the total electric quantity in the time period T is
1-2) defining a normalized load curve l*(t)＝fu(l(t))＝l(t)/αt＝1,2,…,T，l*(t) load curve l (t) normalized by algorithm fuAfter the value is corrected, the characteristics of the load curve on the magnitude are eliminated, and the characteristics of the curve shape are reserved;
in the step 2, calculating the load guideline specifically includes:
2-1) establishing an objective function of economic dispatching;
2-2) establishing constraint conditions;
in the step 2-1), the objective function of the economic dispatching is as follows:
wherein,
the active power output of the ith adjustable generator in the system in the t period is shown, and N is totalGA stage adjustable generator; pR(t) the output of all photovoltaic and wind power new energy power generation in the system in a time period t; pR.max(t) is the maximum value of the new energy output in the time period t, and is obtained by prediction in the day ahead; a isi,bi,ciFor the cost coefficient of the ith controllable generator set, the first term of the objective function, i.e. the sum of the operating costs of all controllable generator sets, CRThe second term of the objective function, namely the cost generated by not consuming the new energy, is the cost for wind and light abandoning, and the cost for fully consuming the new energy CRSet to very large coefficients;
in the step 2-2), the non-adjustable new energy power generation and the non-responsive demand side resource are balanced by using the flexible and controllable power generation resource and the demand side resource participating in the response, namely:
PD(t) and PC(t) power consumption for all loads participating in and not participating in DR within the system during time t, respectively;
is according to the formula to PD(t) value to be converted, aDNamely the total power consumption of the load participating in DR in the T period;
the constraint conditions are as follows:
step 3, establishing a model for measuring the similarity between the actual load curve shape of the user and the load alignment, specifically,
wherein l*(t) is the normalized value of the load curve to be measured according to the formula, d is the Euclidean distance of the two sequences, E is the conversion of the Euclidean distance to (0, 1)]Metric index after interval.
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Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105846423A (en) * | 2016-03-28 | 2016-08-10 | 华北电力大学 | Method for photovoltaic microgrid energy storage multi-target capacity configuration by taking demand response into consideration |
| CN107832919A (en) * | 2017-10-17 | 2018-03-23 | 国网江苏省电力公司盐城供电公司 | A kind of source net lotus coordinated control system for intermittent renewable energy access power network |
| CN108376996A (en) * | 2018-03-19 | 2018-08-07 | 国网江西省电力有限公司经济技术研究院 | A kind of power distribution network distributed photovoltaic receiving ability evaluation method of practicality |
| CN108805388A (en) * | 2018-04-09 | 2018-11-13 | 中国电力科学研究院有限公司 | A kind of determination method and apparatus of non-coming year Load Time Series scene |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105846423A (en) * | 2016-03-28 | 2016-08-10 | 华北电力大学 | Method for photovoltaic microgrid energy storage multi-target capacity configuration by taking demand response into consideration |
| CN107832919A (en) * | 2017-10-17 | 2018-03-23 | 国网江苏省电力公司盐城供电公司 | A kind of source net lotus coordinated control system for intermittent renewable energy access power network |
| CN108376996A (en) * | 2018-03-19 | 2018-08-07 | 国网江西省电力有限公司经济技术研究院 | A kind of power distribution network distributed photovoltaic receiving ability evaluation method of practicality |
| CN108805388A (en) * | 2018-04-09 | 2018-11-13 | 中国电力科学研究院有限公司 | A kind of determination method and apparatus of non-coming year Load Time Series scene |
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