CN111008746A - Load combination optimization method considering transferable load - Google Patents
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Abstract
The invention discloses a load combination optimization method considering transferable loads, which comprises the following steps: according to the comprehensive load characteristics of the user, a relation model of electricity purchasing cost and load rate of the electricity selling merchant is constructed; carrying out primary optimization on a relation model of electricity purchasing cost and load rate by taking the electricity selling income as an objective function to obtain a primary user and a primary comprehensive load characteristic curve; according to the comprehensive load characteristic curve, the electricity vendors select a combination for the users receiving the demand response adjustment instruction; acquiring an electricity vendor comprehensive cost model capable of transferring loads according to users selected by the electricity vendor to be combined; and acquiring an electricity vendor optimization model capable of transferring the load according to the electricity vendor comprehensive cost model, and selecting a high-quality user to participate in the optimization of the transferable load according to the electricity vendor optimization model. The invention can optimize the demand response of the user with the transferable load adjusting capability, and has guiding significance for guiding the user to orderly use the electricity.
Description
Technical Field
The invention relates to the technical field of power systems, in particular to a load combination optimization method considering transferable loads.
Background
At present, because the reform of the Chinese power selling side system is just performed, a market main body of a power vendor does not appear in the market, in the aspect of related load combination optimization problems, domestic scholars mostly consider the unit combination optimization problem of the power generation side, and have little research on the combination optimization problem of the load side to user loads, and mainly from the perspective of planning and reconstruction of a power distribution network, the domestic scholars do not stand in the market, and consider that after the reform of the power system is completed in the future, the power vendor considers the combination optimization problem of the client loads in order to reduce the power purchasing cost and does not combine transferable loads to consider the optimization regulation capability of the users.
Disclosure of Invention
The invention aims to provide a load combination optimization method considering transferable loads, which aims to solve the problem that the combination optimization of customer loads cannot be realized in the prior art.
In order to achieve the purpose, the invention is realized by adopting the following technical scheme:
a load combination optimization method considering transferable loads, comprising the steps of:
according to the comprehensive load characteristics of the user, a relation model of electricity purchasing cost and load rate of the electricity selling merchant is constructed;
carrying out primary optimization on the relation model of the electricity purchasing cost and the load rate by taking the electricity selling income as an objective function to obtain a primary user and a primary comprehensive load characteristic curve;
according to the comprehensive load characteristic curve, the electricity vendors select combinations for users receiving the demand response adjustment instructions, wherein the combinations selected for the users are determined according to the transferable load adjustment capacity of the users and the corresponding response cost;
acquiring an electricity vendor comprehensive cost model capable of transferring loads according to users selected by the electricity vendor to be combined;
and acquiring an electricity vendor optimization model capable of transferring the load according to the electricity vendor comprehensive cost model, and selecting a high-quality user to participate in the optimization of the transferable load according to the electricity vendor optimization model.
Further, the building of the relation model between the electricity purchasing cost and the load factor of the electricity selling merchant comprises the following steps:
acquiring a typical daily load characteristic model of users in a user group under a plurality of load sampling points;
acquiring the total electricity consumption of regional users in charge of an electricity vendor according to the load characteristic model of the users;
and acquiring a load rate formula according to the total power consumption, the total times of the load sampling points and the maximum load in a specified time period, and constructing a model between the electricity purchasing cost and the load rate of the electricity seller according to the load rate formula.
Further, the user selection combination of the electricity vendor for receiving the demand response adjustment instruction comprises the following steps:
calculating the average load of the users after the initial combination according to the initial comprehensive load characteristic curve;
acquiring the time when the transferable load needs to be transferred and the priority of the time when the transferable load can be transferred according to the average load of the user;
after receiving the adjustment instruction of the demand response, the user reports the transferable load adjustment capability and the corresponding price according to the self power utilization condition, and the electricity vendor selects and combines the user according to the transferable load adjustment capability and the corresponding price of the user, wherein the user who can be transferred at a plurality of moments can be preferentially considered to be transferred to a time period with high priority degree.
Further, the obtaining of the priority of the time when the transferable load is transferred specifically includes: j times when the load is greater than the average load and T-j times when the load is less than the average load in all load collection time points are respectively recorded, sequenced and issued to a user, and the time when the transferable load needs to be transferred and the priority degree of the time when the transferable load can be transferred are determined:
o represents the sequence of priority levels to which transferable loads need to be transferred, I represents the sequence of priority levels to which transferable loads can be transferred, t1-tjRepresenting j times, t, at which the load needs to be transferred outj+1-tTAnd T-j moments when the load can be transferred are represented, wherein T is the total collection times.
Further, the step of obtaining the comprehensive cost model of the electricity vendors with transferable loads comprises the following steps:
calculating the user load rate after the demand response of the transferable load is adjusted;
and acquiring the cost of the electricity vendors according to the adjusted user load rate.
Further, the electricity vendor cost comprises the electricity purchasing cost and the corresponding cost of implementing the demand.
Further, the electricity vendor optimization model is as follows:
profit'≥profit
LF'≥LF
wherein p issellF (LF') is a relation model of electricity purchasing cost and load rate of the electricity selling merchant after the transferable load is optimized and adjusted,
representing that the ith user can be from tkTime shift to tlThe load at the moment is in kWh, lambdai DRThe ith user shifts the price of the load adjustment in units of yuan/kWh;
constraint function
The combined load at any moment in the T time cannot exceed the maximum load limit which can be borne by the electricity vendor;
the constraint function LF' is more than or equal to LF, which indicates that the comprehensive load rate after the transferable load adjustment is higher than the value before the adjustment;
the constraint function, profit' ≧ profit, indicates that the revenue is increased after adjusting based on transferable load, i.e., the cost of implementing demand response should be included in the increased revenue;
constraint function
Indicating that the transferable load size of each user cannot be larger than the original load value of the user at that moment.
According to the technical scheme, the embodiment of the invention at least has the following effects:
1. the user load combination optimization method based on the demand side response can determine how to select high-quality users under the scene of the maximum electricity selling income of the electricity selling merchants, combine user groups and adjust and optimize transferable loads of all combined users at all times.
2. The invention considers the influence of the load characteristics of the user on the electricity purchasing cost, the transferable load adjusting capacity of the user, the demand response cost of the transferable load adjustment of the user and other factors, considers the combination optimization of the user group from the viewpoint of reducing the electricity purchasing cost, simultaneously considers the transferable load, researches the demand response adjusting method after the electricity seller selects the high-quality user, preliminarily combines the user and then considers the transferable load adjusting optimization method, reduces the difficulty degree of operation, improves the feasibility, selects the high-quality user for the electricity selling company in the market environment, performs the demand response adjusting optimization for the user with the transferable load adjusting capacity, and has guiding significance for guiding the user to perform the ordered electricity utilization.
Drawings
FIG. 1 is a flow chart of a method according to an embodiment of the present invention.
Detailed Description
In order to make the technical means, the creation characteristics, the achievement purposes and the effects of the invention easy to understand, the invention is further described with the specific embodiments.
Under the condition of open power selling side in the power market, the power selling company can establish a load combination optimization model for daily load curves of different types of users according to own requirements, optimize and combine different types of loads, change comprehensive load characteristics of the users, and preferably select users with complementary load characteristics, so that the purposes of optimizing the whole load curve, improving the load rate and reducing the power purchasing cost are achieved. Meanwhile, the combination optimization of the load can improve the utilization rate of equipment, reduce the line loss and improve the safe operation level and the power supply quality of a power grid at the power supply side.
The demand side management refers to a system management project that a power supply side guides and encourages power consumers (demand sides) to adopt various effective energy-saving technologies to change power utilization modes through a series of administrative, economic and technical policies and measures, so that the operation efficiency of a power system is improved, and the operation cost is reduced.
As shown in fig. 1, a load combination optimization method considering transferable loads of the present invention includes the following steps:
step 1, constructing an electricity purchasing cost model related to the load rate of an electricity seller:
sampling a plurality of typical days of each user from a user group, and calculating an average value to obtain a typical daily load characteristic model of each user under T load sampling points:
Li＝[Li1,Li2,...,LiT]＝[li1gΔt,li2gΔt,...,liTgΔt]
wherein L isiRepresenting the power utilization condition of the user i in one day, namely the load quantity Q of each sampling small time pointiRepresenting the total electricity in kWh for the ith user during the day; l isitThe unit of the electric quantity of the ith user at the tth moment is kWh; litThe load magnitude of the ith user at the t-th moment is represented, namely the specific load value of the user at each moment is acquired by a load control system according to the acquisition frequency once per Δ t time interval by a typical daily load curve of the user, and the average power of the user at the t-th moment can be understood as the unit of kW; delta T is the user load size acquisition time interval, is equal to 24/T in numerical value and has the unit of hour; t is the total number of times of collection, i.e. 24 hours a day is divided into T time periods liTg Δ T represents the magnitude of the load for the T-th period.
The total electric quantity of the regional users in charge of the electricity vendor is as follows:
calculation formula of load factor:
wherein:
is the average load over a specified time period T; pmIs the maximum load in a specified time period; q is the total electricity consumption in the specified time; and N is the total number of users needing load combination.
Constructing a mathematical relation between the electricity purchasing cost and the load rate of an electricity selling merchant:
pcost＝f(LF)
wherein p iscostThe unit of the electricity purchasing price is yuan/kwh when an electricity seller purchases electricity from a power generation manufacturer; (ii) a The function concrete expression can be obtained by a function fitting method according to historical data of electricity vendors and power plant electricity purchasing.
Step 2, performing preliminary combined optimization, taking the electricity selling income as an objective function, and constructing a load combined optimization model with the electricity selling income as the maximum optimization objective:
Li∈LN
wherein p issellFor selling electricity, PnmaxRepresenting the maximum electricity purchasing capacity of the electricity vendor, LNRepresenting the power usage of the entire user group.
The power consumption representing all the users cannot exceed the maximum power purchasing capacity of the electricity vendors, in the model, the power consumption will increase with the increase of the number of the users, but the load characteristics of the users will become worse with the increase of the users, so that the electricity purchasing cost is increased, and therefore, a preliminarily selected user and a preliminary comprehensive load characteristic curve can be obtained through the first combined optimization.
And 3, considering a model of the transferable load adjusting capacity of the user according to the preliminary combination optimization result of the step 2.
And (3) calculating the average load of the combined user by the electricity vendor according to the comprehensive load characteristic curve obtained by the preliminary optimization:
then j moments when the load is larger than the average load and T-j moments when the load is smaller than the average load in all load collection time points are respectively recorded, sequenced and issued to a user, and the moment when the transferable load needs to be transferred is determinedAnd the degree of priority of the time instants that can be transferred:
wherein, O represents the priority sequence that the transferable load needs to be transferred out, I represents the priority sequence that the transferable load can be transferred into, t1-tjRepresenting j times, t, at which the load needs to be transferred outj+1-tTRepresenting the T-j times that the load can go.
The user reports the transferable load regulation capacity and the price according to the self power utilization condition, after the user receives a regulation instruction of demand response, the transferable load regulation capacity and the corresponding price can be reported according to the self power utilization condition, and the user can be supplied to an electricity vendor to select and combine, and for the user capable of transferring a plurality of time intervals, the user can be preferentially considered to be transferred to the time interval with high priority degree.
Wherein
Representing that the ith user can be from tkTime shift to tlThe load at the moment is in kWh, lambdai DRThe ith user shifts the price of the load adjustment in units of dollars/kWh.
And 4, considering the electricity vendor comprehensive cost model of the transferable load according to the transferable load adjusting capacity model of the user in the step 3.
After the demand response adjustment of the transferable load is carried out, the load characteristic of the user can be improved, which is reflected in that the load rate of the user can be increased, the electricity purchasing cost can be reduced, but the adjustment of the transferable load needs cost, so that an adjustment optimization model of the transferable load is constructed, and how the transferable load of the user is adjusted is determined. For the user, if the electricity vendor chooses to participate in the adjustment of the transferable load, the load characteristics after participation in the response are as follows:
i.e. at the k-th moment will
The load is transferred out, and the first moment is
Load transfer into, total quantity of electricity QiMay be considered to remain unchanged. For the comprehensive load rate of the user, since the total power amount is not changed, the average power amount is not changed, and after the transferable load adjustment, the maximum power amount of the user is changed, which can be calculated as Δ p, so the load rate after the adjustment is calculated as:
wherein, Pm' represents the maximum load for a specified period of time after the transferable load adjustment. The cost of the electricity seller is divided into two parts, one part is the electricity purchasing cost, and through improvement, the cost of the part is reduced along with the increase of the load factor:
the second part cost is the cost incurred in implementing the demand response, which, after determining the users participating in the transferable load adjustment, is as follows:
step 5, the electricity vendors considering the transferable loads according to the comprehensive transferable loads cost in the step 4
And optimizing the model. And calculating and selecting a high-quality user to participate in the optimization of the transferable load by the electricity vendor optimization model.
Within a certain period of time, the electricity seller and the user make an electricity purchasing contract, and the selling price of the electric energy is not changed within a short period of time, namely psell is constant. Thus, the revenue for joining the transferable load adjusted electricity vendor is as follows:
the load combination optimization model with the maximum benefit of the load aggregation commercial power sale as the optimization target is as follows:
profit'≥profit
LF'≥LF
wherein the constraint function
The combined load at any moment in the T time cannot exceed the maximum load limit which can be borne by the electricity vendor;
the constraint function LF' is more than or equal to LF, which indicates that the comprehensive load rate after the transferable load adjustment is higher than the value before the adjustment;
the constraint function, profit' ≧ profit, indicates that the revenue is increased after adjusting based on transferable load, i.e., the cost of implementing demand response should be included in the increased revenue;
constraint function
To representThe transferable load size of each user cannot be larger than the original load value of the user at that moment.
Wherein, the profit 'represents the benefit after the transferable load is optimally adjusted, the LF' represents the load rate after the transferable load is optimally adjusted,
representing the load of the user shifting from time K to time l.
In conclusion, the invention relates to a method for combined optimization of user load by considering the electricity vendors with transferable loads, which is a method for initially combining the electricity vendors with the aim of maximizing electricity selling benefits of the electricity vendors in an open environment of an electric power market and optimizing demand response adjustment by considering the transferable load adjustment capacity of a user group at different time intervals.
It will be appreciated by those skilled in the art that the invention may be embodied in other specific forms without departing from the spirit or essential characteristics thereof. The embodiments disclosed above are therefore to be considered in all respects as illustrative and not restrictive. All changes which come within the scope of or equivalence to the invention are intended to be embraced therein.
Claims (7)
1. A load combination optimization method considering transferable loads, comprising the steps of:
according to the comprehensive load characteristics of the user, a relation model of electricity purchasing cost and load rate of the electricity selling merchant is constructed;
carrying out primary optimization on the relation model of the electricity purchasing cost and the load rate by taking the electricity selling income as an objective function to obtain a primary user and a primary comprehensive load characteristic curve;
according to the comprehensive load characteristic curve, the electricity vendors select combinations for users receiving the demand response adjustment instructions, wherein the combinations selected for the users are determined according to the transferable load adjustment capacity of the users and the corresponding response cost;
acquiring an electricity vendor comprehensive cost model capable of transferring loads according to users selected by the electricity vendor to be combined;
and acquiring an electricity vendor optimization model capable of transferring the load according to the electricity vendor comprehensive cost model, and selecting a high-quality user to participate in the optimization of the transferable load according to the electricity vendor optimization model.
2. The method for optimizing a load combination considering transferable loads according to claim 1, wherein the step of constructing the relation model between the electricity purchasing cost of the electricity selling company and the load rate comprises the following steps:
acquiring a typical daily load characteristic model of users in a user group under a plurality of load sampling points;
acquiring the total electricity consumption of regional users in charge of an electricity vendor according to the load characteristic model of the users;
and acquiring a load rate formula according to the total power consumption, the total times of the load sampling points and the maximum load in a specified time period, and constructing a model between the electricity purchasing cost and the load rate of the electricity seller according to the load rate formula.
3. The method of claim 1, wherein the customer selected combination of the electricity vendors receiving demand response adjustment instructions comprises the steps of:
calculating the average load of the users after the initial combination according to the initial comprehensive load characteristic curve;
acquiring the time when the transferable load needs to be transferred and the priority of the time when the transferable load can be transferred according to the average load of the user;
after receiving the adjustment instruction of the demand response, the user reports the transferable load adjustment capability and the corresponding price according to the self power utilization condition, and the electricity vendor selects and combines the user according to the transferable load adjustment capability and the corresponding price of the user, wherein the user who can be transferred at a plurality of moments can be preferentially considered to be transferred to a time period with high priority degree.
4. The method according to claim 3, wherein the obtaining the priority of the time when the transferable load is transferred specifically comprises: j times when the load is greater than the average load and T-j times when the load is less than the average load in all load collection time points are respectively recorded, sequenced and issued to a user, and the time when the transferable load needs to be transferred and the priority degree of the time when the transferable load can be transferred are determined:
o represents the sequence of priority levels to which transferable loads need to be transferred, I represents the sequence of priority levels to which transferable loads can be transferred, t1-tjRepresenting j times, t, at which the load needs to be transferred outj+1-tTAnd T-j moments when the load can be transferred are represented, wherein T is the total collection times.
5. The method for load portfolio optimization with consideration of transferable loads according to claim 1, wherein the step of obtaining the comprehensive cost model of the electricity vendors of transferable loads comprises the steps of:
calculating the user load rate after the demand response of the transferable load is adjusted;
and acquiring the cost of the electricity vendors according to the adjusted user load rate.
6. The method of claim 5, wherein the electricity vendor costs include a cost of purchasing electricity and a cost associated with the demand for implementation.
7. The method of claim 1, wherein the vendor optimization model is:
profit'≥profit
LF'≥LF
wherein p issellF (LF') is a relation model of electricity purchasing cost and load rate of the electricity selling merchant after the transferable load is optimized and adjusted,
representing that the ith user can be from tkTime shift to tlThe load at the moment is in kWh, lambdai DRThe ith user shifts the price of the load adjustment in units of yuan/kWh;
constraint function
The combined load at any moment in the T time cannot exceed the maximum load limit which can be borne by the electricity vendor;
the constraint function LF' is more than or equal to LF, which indicates that the comprehensive load rate after the transferable load adjustment is higher than the value before the adjustment;
the constraint function, profit' ≧ profit, indicates that the revenue is increased after adjusting based on transferable load, i.e., the cost of implementing demand response should be included in the increased revenue;
constraint function
Representing transferable load size of individual usersAnd cannot be larger than the original load value of the user at that moment.
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Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104953594A (en) * | 2015-07-02 | 2015-09-30 | 东南大学 | Optimal scheduling method for power selling company containing distributed power sources and transferable loads |
| CN109256775A (en) * | 2018-11-15 | 2019-01-22 | 南方电网科学研究院有限责任公司 | A kind of load combined optimization method, device and storage medium based on Demand-side |
| CN109784594A (en) * | 2017-11-10 | 2019-05-21 | 中国电力科学研究院有限公司 | A kind of sale of electricity quotient deferrable load decision-making technique and system |
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Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104953594A (en) * | 2015-07-02 | 2015-09-30 | 东南大学 | Optimal scheduling method for power selling company containing distributed power sources and transferable loads |
| CN109784594A (en) * | 2017-11-10 | 2019-05-21 | 中国电力科学研究院有限公司 | A kind of sale of electricity quotient deferrable load decision-making technique and system |
| CN109256775A (en) * | 2018-11-15 | 2019-01-22 | 南方电网科学研究院有限责任公司 | A kind of load combined optimization method, device and storage medium based on Demand-side |
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