CN110222433B - Household intelligent power utilization optimization method considering uncertainty of user power utilization behavior - Google Patents
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Abstract
The invention provides a household intelligent power utilization optimization method considering uncertainty of power utilization behaviors of users, which aims to solve the problem that a power utilization plan cannot be normally carried out due to the uncertainty of the power utilization behaviors of power users. The uncertain behaviors of the electricity consumption of the power consumer are divided into tasks of adjusting the electricity consumption plan and increasing and decreasing the electricity consumption. For the uncertain behavior of the power utilization plan adjusted by the power consumer, a reliability index method is provided, the reliability indexes of various loads are normalized, and a day-ahead power utilization plan is made; and for the uncertain behaviors of increasing and decreasing the power utilization tasks of the power consumers, a power utilization emergency coefficient and a comprehensive power utilization emergency index are provided, the power utilization is rearranged according to the specific behaviors of the consumers, and a real-time power utilization plan is formulated. Based on the two types of uncertain behaviors of the user electricity utilization, the household intelligent electricity utilization optimization process is divided into two parts, so that the reliability of the household intelligent electricity utilization plan is improved.
Description
Technical Field
The invention relates to an energy management technology, in particular to a household intelligent power utilization optimization method considering uncertainty of power utilization behaviors of users.
Background
Along with the construction of the smart power grid, the interaction between the power grid and the power consumers is more convenient. The power grid attracts power consumers to participate in demand response and guides the power consumption behavior of the power consumers by formulating reasonable power price, so that the peak clipping and valley filling are achieved, and the problem of power consumption pressure is relieved; the user reasonably arranges the household power utilization plan by responding to the power price excitation of the power grid, thereby reducing the expenditure of the power utilization cost.
The household energy management system is an extension of a smart grid on the resident side, and is an important component of the smart grid. The household energy management system is based on historical data and electricity utilization habits of user electricity utilization, combines electricity price information of a power grid, and helps a user to make a reasonable household electricity utilization plan on the premise of ensuring the comfort level of the user electricity utilization. However, due to uncertainty of the user electricity utilization behavior, the electricity utilization plan formulated by the home energy management system cannot be normally carried out, and a home intelligent electricity utilization optimization strategy considering the uncertainty of the user electricity utilization behavior is provided aiming at the uncertainty of the user behavior, so that a home intelligent plan capable of resisting the uncertainty of the user behavior is formulated.
Disclosure of Invention
According to the technical problem that the power utilization plan made by the household energy management system cannot normally operate due to the uncertain behaviors of the user, the household intelligent power utilization optimization strategy is provided, and the influence of the uncertainty of the user behaviors on the power utilization plan can be further resisted.
The technical means adopted by the invention are as follows:
a household intelligent power utilization optimization method considering uncertainty of power utilization behaviors of users is characterized by comprising the following steps:
step 1: setting a household intelligent power utilization optimization cycle, and uniformly dividing the household intelligent power utilization optimization cycle into a plurality of sub-time periods;
step 2: setting an initial constraint condition, and acquiring power price information and an upper limit of household power consumption, wherein the initial constraint condition comprises a comfort level range of a user and a time range of the flexible load allowed to work;
and step 3: a user sets reliability indexes for various loads according to the requirement of the user on the power utilization reliability of the power utilization equipment, and normalizes the reliability indexes of the various loads;
and 4, step 4: constructing a family energy source optimization scheduling model taking the minimum family electricity cost as an objective function;
and 5: on the premise of meeting the initial constraint condition of the user, the current power utilization plan of the user is solved by considering the setting of various load reliability indexes of the user day ahead, and the household power utilization equipment works according to the current power utilization plan on the next day;
step 6: when the energy management system runs in real time, the household energy management system judges whether a user has an action of increasing and decreasing the power utilization plan, correspondingly adjusts the power utilization plan according to the specific action of increasing and decreasing the power utilization plan of the user, and formulates a real-time power utilization plan.
Further, the step 3 of setting the reliability index for each type of load includes setting:
a reliability index of the uninterruptible load;
a reliability index of the interruptible load;
reliability index of the air conditioner; and
and (4) reliability index of the water heater.
Further, the reliability index of the uninterruptible load is:
Δt＝t 1 -t 1 ′＝t 2 -t 2 ′
where Δ t denotes the uninterruptible load double-ended time margin value, t 1 A start time, t, representing the range of allowable operating times set by the user 2 Cutoff time, t, representing the range of allowable operating times set by the user 1 ' indicates the starting time, t, of the electricity consuming task for which the time margin value is reserved 2 ' represents the cut-off time of the power utilization task for which the time margin value is reserved;
the reliability index of the interruptible load is as follows:
wherein rho represents the completion rate of the power utilization task before a certain moment, and the value range of lambda is [0, 1%]，Q j Representing the total electric energy consumed by the load j to finish the electricity utilization task; q. q of t j Represents the power consumed by the interruptible load j at time t; t is t 1 A start time, t, representing the range of allowable operating times set by the user 2 An expiration time representing the allowable operating time range set by the user;
the reliability indexes of the air conditioner are as follows:
Δθ c ＝θ cmax -θ′ cmax ＝θ cmin -θ′ cmin
wherein, delta theta c Indicating air conditioner double-end temperature margin value theta cmax Represents the upper limit, theta, of the air conditioning comfort temperature range set by the user cmin Represents the lower limit, theta ', of the air-conditioning comfort temperature range set by the user' cmax Denotes an upper temperature limit of a reserve temperature margin of θ' cmin A lower temperature limit representing a retention temperature margin;
the reliability indexes of the water heater are as follows:
Δθ w ＝θ wmin -θ′ wmin
wherein, delta theta w Represents a lower temperature margin value, theta wmin Represents that a user sets a water heater water temperature lower limit theta' wmin The lower limit of the water temperature indicating the retention temperature margin.
Further, the step 5 of solving the user day-ahead power utilization plan includes:
on the basis of initial constraint conditions set by a user, reliability indexes of various power loads are considered, new constraint comprehensive original constraint conditions obtained through the reliability indexes are added to an intelligent power utilization optimization problem, and a day-ahead power utilization plan considering the reliability indexes is finally obtained.
Further, in step 6, the correspondingly adjusting the power utilization plan and making the real-time power utilization plan according to the behavior of the user for increasing or decreasing the power utilization plan specifically includes:
when the power utilization tasks are reduced, the rest power utilization tasks are re-planned in the current time period to obtain the latest power utilization arrangement;
when a new power utilization task is newly added, whether the total power of the load exceeds the upper limit of the household power utilization is judged when the new power utilization task and a task of a day-ahead power utilization plan are simultaneously carried out, if not, the day-ahead power utilization plan is not changed, otherwise, the priority ranking is carried out on the power utilization tasks in the period according to the power utilization emergency coefficient and the comprehensive power utilization emergency index, the power utilization tasks with low priority are stopped from working in the period, and the power utilization plan is re-planned.
Further, the electricity utilization emergency coefficient includes:
the power utilization emergency coefficient of the uninterruptible load is as follows:
wherein alpha is 1 Emergency coefficient of electricity, t, representing an uninterruptible load L Indicating the number of electricity consumption periods, t, required for uninterruptible load operation i Indicates the current time, t 2 A cutoff time indicating allowable power usage;
the electricity emergency coefficient of the interruptible load is as follows:
wherein alpha is 2 Electric emergency coefficient, W, representing interruptible load re Representing the difference between the total power consumed and the consumed power, q, required for the electricity consumption task up to the moment of the interruptible load cut-off max Representing the maximum power that the interruptible load may consume per unit time period, t i Indicates the current time, t 2 A cut-off time indicating allowable power usage;
the electricity utilization emergency coefficient of the air conditioner is as follows:
wherein alpha is 3 Represents the electricity utilization emergency coefficient of the air conditioner,
indicating the current room temperature at that moment, theta cmax 、θ cmin Respectively representing the upper and lower limits of the comfort temperature of the air conditioner.
The emergency coefficient of the power consumption of the water heater is as follows:
wherein alpha is 4 Represents the electricity utilization emergency coefficient of the water heater,
indicating the current water temperature at that moment, theta wmax 、θ wmin Respectively representing the upper and lower limits of the water heater temperature.
Further, the comprehensive electricity utilization emergency index is as follows:
β i ＝α i *Y i
wherein beta is i Indicating the combined electricity emergency index, alpha, of the load i i Power consumption emergency coefficient, Y, representing load i i And expressing the reliability index after the load i is normalized.
Compared with the prior art, the invention has the following advantages:
the invention provides a household intelligent power utilization optimization strategy considering uncertainty of user power utilization behaviors, which divides the uncertainty of user power utilization into two types: and adjusting the power utilization plan and increasing and decreasing the power utilization tasks. Aiming at the adjustment of the power utilization plan of the user, a reliability index method is provided, and a day-ahead power utilization plan is made; aiming at the increase and decrease of the power utilization tasks of the users, a power utilization emergency coefficient and a comprehensive power utilization emergency index are provided, and a real-time power utilization plan is formulated according to the specific behaviors of the users. Based on the two types of uncertain behaviors of the user electricity utilization, the household intelligent electricity utilization optimization process is divided into two parts, so that the reliability of the household intelligent electricity utilization plan is improved.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without creative efforts.
FIG. 1 is a schematic diagram of an uninterruptible load reliability indicator;
FIG. 2 is a schematic diagram of an interruptible load reliability indicator;
FIG. 3 is a schematic diagram of an air conditioner reliability index;
FIG. 4 is a schematic diagram of a water heater reliability index;
FIG. 5 is a flow chart of a day-ahead power plan;
fig. 6 is a flow of making a real-time power utilization plan.
Detailed Description
In order to make those skilled in the art better understand the technical solutions of the present invention, 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 firstly divides the uncertain behaviors of power consumption of power consumers into two types: and adjusting the power utilization plan and increasing and decreasing the power utilization tasks. For the uncertain behavior of the power utilization plan adjusted by the power consumer, a reliability index method is provided, the reliability indexes of various loads are normalized, and a day-ahead power utilization plan is made; for the uncertain behaviors of increasing and decreasing the power utilization tasks of power consumers, a power utilization emergency coefficient and a comprehensive power utilization emergency index are provided, power utilization is rearranged according to the specific behaviors of the users, and a real-time power utilization plan is formulated, and the method specifically comprises the following steps:
step 1: one day is taken as a household intelligent power utilization optimization cycle, and the household intelligent power utilization optimization cycle is divided into 48 equal sub-periods.
And 2, step: acquiring power price information, an upper limit of household power consumption and initial constraint conditions set by a user, wherein the initial constraint conditions comprise a comfort range of the user and a time range of the flexible load allowed to work.
And step 3: according to the requirement of the user on the electricity reliability of the electric equipment, the user sets reliability indexes for various loads day before, and normalizes the reliability indexes of various loads. The method specifically comprises the following steps:
step 3.1: since the initial constraint condition is set by the user, even if the user makes an uncertainty adjustment to the time range of the load work, the comfort range of the user, and the like, the adjusted range fluctuates around the initial constraint condition. Therefore, in order to avoid the influence of the uncertainty of the user behavior on the power utilization plan, a reliability index method is provided.
The basic steps of the reliability index method are as follows: firstly, various load reliability indexes are defined, and then on the basis of the initial constraint condition, the new constraint condition meeting the reliability indexes is replaced by the initial constraint condition or is directly added to the intelligent power utilization optimization problem as the new constraint condition, so that a power utilization plan with certain reliability on the uncertain behaviors of the user is solved. The various load reliability indicators are defined as follows:
1. reliability index of uninterruptible load
According to the initial constraint condition, the user requires the electricity utilization task of the uninterruptible load to be t 1 ，t 2 ]The power utilization tasks are completed internally, but in the actual power utilization process, the time range of the work allowed by the power utilization tasks can be influenced artificially, namely the starting time or the ending time is advanced or delayed by a user, so that the power utilization tasks cannot be started normally or interrupted midway. Therefore, to avoid the power utilization mission being performed too early or too late, the time margin value is defined as a reliability indicator of the uninterruptible load to improve the reliability of the power utilization plan, as shown in fig. 1.
The uninterruptible load time margin values are defined as follows:
Δt 1 ＝t 1 -t′ 1
Δt 2 ＝t 2 -t′ 2
t 1 、t 2 starting time and deadline time t 'of allowable working time range set by user respectively' 1 、t′ 2 Respectively expressed as the start time and the end time, Δ t, of the electricity utilization mission with a reserved time margin value for increasing the reliability of the electricity utilization 1 、Δt 2 Representing the start time margin value and the deadline margin value, respectively, it is assumed herein for convenience of discussion that the start time margin value and the deadline margin value set by the user are equal, i.e., Δ t = Δ t 1 ＝Δt 2 And denoted by Δ t, collectively referred to as uninterruptible load double-ended time margin values.
After defining the uninterruptible load reliability index, when a user does not want self uncertain behaviors to influence the power utilization plan of the uninterruptible load, the reliability index of the uninterruptible load needs to be set on the basis of the initial allowable working time range to obtain a working time range considering a time margin value, the time range is used as a new constraint condition to replace the original time constraint condition in the intelligent power utilization optimization problem, and therefore the uninterruptible load power utilization plan with certain time reliability is solved, wherein the new constraint condition is specifically as follows:
wherein,
represents the rated power consumed by the uninterruptible load i in a unit time period;
the variable is a variable from 0 to 1 and is used for describing the working condition of the uninterruptible load i in a period t, wherein 0 represents off, and 1 represents work; q i Representing the total electrical energy required to be consumed by load i.
2. Interruptible load reliability index
Interruptible loads and uninterruptable loads have the same problem to deal with, and the electricity-consuming task requiring interruptible loads is [ t ] 1 ，t 2 ]The internal completion is realized, and in actual power utilization, the time range of the work allowed by the power utilization task can be influenced by human, namely the starting time or the ending time is advanced or delayed by a user, so that the power utilization task cannot be started normally or interrupted halfway. However, the interruptible load and the non-interruptible load have different power consumption characteristics, and the interruptible load power consumption task is more flexible to execute and can be separately executed, so that the completed processes of different power consumption plans can be greatly different even if the different power consumption plans are completed at the same time. As shown in the following figure, two different power plans are both at t e The moment is completed, but the process is completely different, at t i The completion rate of the electricity utilization task before the moment is different, as shown in fig. 2.
Through the above analysis, the double ended time margin for the uninterruptible load is not applicable to the interruptible load. And will therefore be in the allowed operating time t 1 ，t 2 ]Before a certain time within the range, the completion rate of the electricity utilization task is used as a reliability index of the interruptible load, and is specifically defined as follows:
wherein, the value range of lambda is [0, 1%]In the text, lambda is 0.5; q j The total electric energy consumed by the load j to finish the electricity utilization task is represented;
represents the power consumed by the interruptible load j at time t; ρ represents the completion rate of the power usage task before a certain time. As can be seen by comparing FIG. 2 according to a defined interruptible load reliability indicator, t i Before the time, the completion rate of the power plan 1 is higher than that of the power plan 2, so the power reliability of the power plan 1 is higher than that of the power plan 2.
After the interruptible load reliability index is defined, when a user does not want self uncertain behaviors to influence the power utilization plan of the interruptible load, the completion rate of a power utilization task of the interruptible load before a certain moment needs to be set, and the power utilization task is set at a certain momentAdding the completion rate before the moment as a new constraint condition into the intelligent power utilization optimization problem so as to obtain an interruptible load power utilization plan with certain reliability, wherein the added new constraint condition is specifically as follows, wherein rho re Indicating the completion rate of the electricity utilization task before a certain time required by the user:
3. reliability index of air conditioner
For the air conditioner, according to the initial constraint condition, the temperature comfort degree range set by the user is [ theta ] cmin ，θ cmax ]However, in the actual electricity utilization process, the user can adjust the temperature range of the air conditioner according to the self demand and weather factors, namely, the lower limit or the upper limit of the temperature is increased or decreased. Such adjustment of the temperature range may affect the normal operation of the power utilization plan, for example, when the user raises the lower temperature limit, the air conditioner may increase the power consumption, which may affect the power utilization plan of the air conditioner or other power utilization equipment. Therefore, the temperature margin value is used as an index of reliability of the air conditioner to attenuate the influence of the adjustment temperature range on the electricity usage plan, as shown in fig. 3.
The air conditioning temperature margin value is defined as follows:
Δθ cmax ＝θ cmax -θ′ cmax
Δθ cmin ＝θ cmin -θ′ cmin
θ cmax 、θ cmin respectively representing the upper limit and the lower limit theta 'of the air conditioner comfort temperature range set by the user' cmax 、θ′ cmin Respectively expressed as upper and lower temperature limits, delta theta, for improving the power utilization reliability of the air conditioner and preserving the temperature margin cmax 、Δθ cmin Representing the upper and lower temperature margin values, respectively, for ease of discussion it is assumed herein that the upper and lower temperature margin values are equal, i.e., Δ θ c ＝Δθ cmax ＝Δθ cmin Using a combination of Delta theta c Meaning, collectively referred to as air conditioning pairsEnd temperature margin values.
After the reliability index of the air conditioner is defined, when a user does not want self uncertainty behavior to affect the temperature comfort level, the reliability index of the air conditioner needs to be set on the basis of an initial air conditioner temperature allowable range, a temperature range with a double-end temperature tolerance value taken into consideration is obtained, the temperature range is used as a new constraint condition to replace an original temperature constraint condition in the intelligent power utilization optimization problem, and therefore an air conditioner power utilization plan with certain temperature reliability is obtained, wherein the new constraint condition is as follows:
4. reliability index of water heater
The water heater is similar to the air conditioner, but for the water heater, the upper limit temperature of the water heater is generally set to be the highest, and a user can adjust the lower limit of the water temperature of the water heater according to the self demand and weather factors, namely, the lower limit of the water temperature is increased or decreased. Such adjustment of the water temperature range may also affect the normal operation of the power utilization plan, for example, when the user raises the lower limit of the water temperature, the water temperature of the original power utilization plan may not meet the user's requirement, and the comfort of the user may be responded, which causes the water heater to increase the power consumption, and thus may affect the power utilization plan of the water heater or other power utilization equipment. Therefore, for such a case of adjusting only the lower temperature limit, a single-end temperature margin value is defined as a reliability index of the water heater to weaken the influence of the increase of the user's heat consumption on the power consumption plan, as shown in fig. 4.
The single-end temperature margin value of the water heater is defined as follows:
Δθ w ＝θ wmin -θ′ wmin
θ wmin indicates that a user sets a water heater water temperature lower limit theta' wmin Lower water temperature limit, Δ θ, expressed as a temperature margin reserved to improve reliability of water heater power usage w Respectively, lower limit temperature margin values.
After the reliability index of the water heater is defined, when a user does not want self uncertain behaviors to influence the water temperature comfort level, the single-end temperature margin of the water heater needs to be set on the basis of the initial water heater temperature allowable range, the temperature range with the single-end temperature margin value taken into consideration is obtained, the temperature range is used as a new constraint condition to replace the original temperature constraint condition in the intelligent power utilization optimization problem, and therefore a water heater power utilization plan with certain temperature reliability is solved, wherein the new constraint condition is specifically as follows:
step 3.2: since the reliability index is set by the user, a higher user setting for the reliability index of the load indicates that the user is less likely to influence the power plan of the load due to his/her behavioral uncertainty. However, because the dimensions and magnitude of different loads are different, the reliability indexes of different loads cannot be directly compared, so the reliability indexes of various loads need to be normalized and converted into unit-free quantities, and the comparison is convenient. Normalization is performed herein using the dispersion normalization method, as follows:
wherein X i Indicates the reliability index, X, set by the load i max And X min Respectively representing a maximum reliability index and a minimum reliability index which can be set for the load i, Y i Representing the reliability index after load i normalization.
And 4, step 4: constructing a family energy source optimization scheduling model taking the minimum family electricity consumption cost as an objective function;
considering that the main concern of users is the economic problem of electricity utilization, an objective function with the minimum electricity utilization cost as a target is constructed, which is as follows:
wherein Cost represents the total Cost of the electricity charge of the user; p is a radical of t Represents the electricity rate in the time period t;
respectively representing the electric energy consumed by the air conditioner and the water heater in the time period t; u represents a set of uninterruptible loads; v denotes a set of interruptible loads.
And 5: under the premise of meeting the initial constraint condition of the user, the setting of various load reliability indexes by the user in the day ahead is considered, the new constraint comprehensive original constraint condition obtained by the reliability index is added into the intelligent power utilization optimization problem, and if the new constraint condition obtained by the reliability index is not in the initial original condition, the new constraint condition is directly added into the optimization problem; if the new constraint derived from the indicator of reliability is smaller than a certain constraint range of the original condition, it is replaced with a new constraint. By the scheme, the day-ahead power utilization plan of the user is solved, and the household power utilization equipment in the next day works according to the day-ahead power utilization plan, as shown in fig. 5. Step 6: when the energy management system runs in real time, the energy management system judges whether the user has the behavior of increasing or decreasing the power utilization plan, correspondingly adjusts the power utilization plan according to the specific behavior of increasing or decreasing the power utilization plan of the user, and formulates a real-time power utilization plan, as shown in fig. 6.
Step 6.1: the increase and decrease of the power utilization tasks are different from the adjustment of the power utilization plan, the adjustment of the power utilization plan does not increase or decrease the number of the power utilization tasks, only the initial constraint condition is adjusted, the increase and decrease of the power utilization tasks are based on the day-ahead power utilization tasks, the power utilization tasks which are not available in the day-ahead power utilization plan are increased or decreased, and the uncertainty of the increase and decrease of the power utilization tasks is specifically analyzed as follows:
6.1.1 because the behavior uncertainty of the user power utilization reduces the power utilization task, the power utilization plan in the day ahead is probably not the optimal scheme, the treatment for reducing the power utilization task is easier, and only the rest power utilization tasks need to be re-planned from the time slot to obtain the latest power utilization arrangement.
6.1.2 because the power consumption of the user is uncertain, the new power consumption task can occur in two situations: in the first situation, if a newly added power utilization task and a task of a day-ahead power utilization plan are simultaneously carried out, and the total power of the load does not exceed the upper limit of the household power utilization, the day-ahead power utilization plan does not need to be changed and is carried out according to the day-ahead power utilization plan; in the second situation, if the total power of the load exceeds the upper limit of the household power consumption when the new power consumption task and the task of the power consumption plan in the day ahead are simultaneously performed, so that the power consumption tasks in the period can not be normally performed, even the power consumption hidden danger and other problems occur, the power consumption tasks in the period need to be subjected to priority sequencing according to the power consumption emergency coefficient and the comprehensive power consumption emergency index, the power consumption tasks with low priority are stopped from working in the period, and the power consumption plan is re-planned.
Step 6.2: the method for establishing the power utilization emergency coefficient comprises the following steps:
the power emergency coefficient of the uninterruptible load must be continued for the ongoing uninterruptible load, and the interruption will have an inevitable effect on the user, so the power emergency coefficient of the ongoing uninterruptible load is 1. The electricity emergency coefficient of the uninterruptible load prepared to start the period is defined as the ratio of the number of electricity utilization periods required for the operation of the uninterruptible load to the number of periods from the moment to the electricity utilization cutoff moment, and is specifically expressed as follows:
wherein alpha is 1 Emergency coefficient of electricity, t, representing uninterruptible load L Indicating the number of electricity consumption periods, t, required for uninterruptible load operation i Indicates the current time, t 2 Indicating the cut-off time at which electricity is allowed to be used.
The emergency coefficient of the electricity consumption of the interruptible load can be stopped at any time, so that whether the interruptible load needs to be stopped or not can be judged according to the priority even if the interruptible load is running at the moment. For the interruptible load, the power utilization emergency coefficient is defined as the ratio of the difference between the total power required to be consumed and the consumed power of the power utilization task to the maximum power which can be consumed from the moment to the cutoff moment, and is specifically expressed as follows:
wherein alpha is 2 Power emergency coefficient, W, representing interruptible load re Representing the difference between the total power consumed and the consumed power, q, required for the electricity consumption task up to the moment of the interruptible load cut-off max Represents the maximum power that the interruptible load may consume per unit time period, t i Indicates the current time, t 2 Indicating the cut-off time at which electricity is allowed to be used.
The power utilization emergency coefficient of the air conditioner is defined as the ratio of the difference between the current temperature and the lower limit of the temperature comfort degree to the difference between the upper limit and the lower limit of the temperature comfort degree, and is specifically represented as follows:
wherein alpha is 3 Represents the electricity utilization emergency coefficient of the air conditioner,
indicating the current room temperature at that moment, theta cmax 、θ cmin Respectively representing the upper and lower limits of the comfort temperature of the air conditioner.
For the water heater, the electricity emergency coefficient is defined as the ratio of the difference between the upper limit of the temperature comfort degree and the current temperature to the difference between the upper limit and the lower limit of the temperature comfort degree, and is specifically represented as follows:
wherein，α 4 Represents the electricity utilization emergency coefficient of the water heater,
indicating the current water temperature at that moment, theta wmax 、θ wmin Respectively representing the upper and lower limits of the water heater temperature.
Step 6.3: the comprehensive electricity utilization emergency index is formulated as follows:
in the actual priority judgment process, the power utilization emergency coefficients of the two loads are likely to be equal or similar, so that the priority levels of the two loads cannot be accurately judged, and the comprehensive power utilization emergency index is further defined.
Since the reliability index is defined by the user, a higher user setting for the reliability index of the load indicates that the user is less likely to influence the power plan of the load due to his own behavioral uncertainty. Therefore, the product of the normalized reliability index and the load electricity emergency coefficient is defined as a comprehensive electricity emergency index, and even if the electricity emergency coefficients of the two loads are equal, the priority order of the two loads can be determined by the comprehensive electricity emergency index, which is specifically expressed as follows:
β i ＝α i *Y i
wherein, beta i Integral electricity utilization emergency index, alpha, representing load i i Electric power consumption emergency coefficient, Y, representing load i i And representing the reliability index after the load i is normalized. For the uninterruptible loads in operation, the comprehensive electricity utilization emergency index of the uninterruptible loads is directly set to be the highest, and then the comprehensive electricity utilization emergency indexes of the rest of the loads are sorted to obtain the final priority sorting, as shown in table 1.
TABLE 1 comprehensive power utilization emergency index for power load
The scheme and the effect of the invention are further explained by a specific application example. As shown in fig. 1 to 6, the method for optimizing household intelligent power consumption considering uncertainty of user power consumption behavior includes the following specific steps:
step 1: taking one day as a household intelligent power utilization optimization cycle, and dividing the cycle into 48 equal sub-periods;
step 2: acquiring electricity price information, an upper limit of household power consumption and initial constraint conditions set by a user, wherein the initial constraint conditions comprise a comfort level range of the user and a time range of the flexible load allowed to work;
the electricity price information obtained in this embodiment is time-of-use electricity price, and the peak period is 7:00 to 11:00 and 19:00 to 23:00; the usual time period is 11:00 to 19:00; the trough period was 23: 00-day 7:00. the electricity prices of the peak, the flat and the valley are respectively 0.787 yuan, 0.52 yuan and 0.208 yuan. The upper limit of the household electric power is 7kW.
The power consumption information and the initial constraint conditions of the household electric equipment are shown in table 2:
table 2 power consumption information and initial constraint conditions of home power consumption devices
And step 3: the user sets reliability indexes for various loads in the day ahead according to the requirement of the user on the power utilization reliability of the electric equipment, and the reliability indexes of various loads are subjected to normalization processing;
step 3.1: and setting a reliability index by a user, and replacing the initial constraint condition with a new constraint condition meeting the reliability index or directly adding the new constraint condition into the intelligent power utilization optimization problem as the new constraint condition on the basis of the initial constraint condition according to the definition of the reliability index, so that a power utilization plan with certain reliability on uncertain behaviors of the user is solved.
Step 3.2: since the reliability index is set by the user, a higher user setting for the reliability index of the load indicates that the user is less likely to influence the power plan of the load due to his/her behavioral uncertainty. However, because the dimensions and magnitude of different loads are different, the levels of the reliability indexes of different loads cannot be directly compared, so that the reliability indexes of various loads need to be normalized to be converted into unit-free quantities, and the comparison is convenient. Normalization is performed herein using the dispersion normalization method, as follows:
wherein X i Indicates the reliability index, X, set by the load i max And X min Respectively representing a maximum reliability index and a minimum reliability index which can be set for the load i, Y i Representing the reliability index after load i normalization.
In this embodiment, the reliability index and the normalization result of each type of load are set as shown in table 3.
And 4, step 4: constructing a family energy source optimization scheduling model taking the minimum family electricity consumption cost as an objective function;
considering that the main concern of users is the economic problem of electricity utilization, an objective function with the minimum electricity utilization cost as a target is constructed, which is as follows:
wherein Cost represents the total Cost of the electricity charge of the user; p is a radical of formula t Represents the electricity rate in the time period t;
respectively representing the electric energy consumed by the air conditioner and the water heater in the time period t; u represents a set of uninterruptible loads; v denotes a set of interruptible loads.
TABLE 3 various load reliability indexes and normalization results
And 5: on the premise of meeting the initial constraint condition of the user, the setting of various load reliability indexes by the user in the day ahead is considered, the day-ahead power utilization plan of the user is solved, and the household power utilization equipment in the next day works according to the day-ahead power utilization plan, as shown in fig. 5.
Step 6: when the energy management system runs in real time, the energy management system judges whether the user has the behavior of increasing or decreasing the power utilization plan, correspondingly adjusts the power utilization plan according to the specific behavior of increasing or decreasing the power utilization plan of the user, and formulates a real-time power utilization plan, as shown in fig. 6.
Step 6.1: the increase and decrease of the electricity utilization tasks are different from the adjustment of the electricity utilization plan, the adjustment of the electricity utilization plan does not increase or decrease the number of the electricity utilization tasks, only the initial constraint condition is adjusted, the increase and decrease of the electricity utilization tasks are based on the day-ahead electricity utilization tasks, the electricity utilization tasks which are not available in the day-ahead electricity utilization plan are increased or decreased, and the uncertainty of the increase and decrease of the electricity utilization tasks is specifically analyzed as follows:
6.1.1 because the behavior uncertainty of the user power utilization reduces the power utilization task, the power utilization plan in the day ahead is probably not the optimal scheme, the treatment for reducing the power utilization task is easier, and only the rest power utilization tasks need to be re-planned from the time slot to obtain the latest power utilization arrangement.
6.1.2 because the new power consumption task of the action uncertainty of user's power consumption can appear two kinds of situations: in the first case, if the newly added power utilization task and the task of the day-ahead power utilization plan are simultaneously carried out, and the total power of the load does not exceed the upper limit of the household power utilization, the day-ahead power utilization plan does not need to be changed and is carried out according to the day-ahead power utilization plan; in the second situation, if the total power of the load exceeds the upper limit of the household power consumption when the new power consumption task and the task of the power consumption plan in the day ahead are simultaneously performed, so that the power consumption tasks in the period can not be normally performed, even the power consumption hidden danger and other problems occur, the power consumption tasks in the period need to be subjected to priority sequencing according to the power consumption emergency coefficient and the comprehensive power consumption emergency index, the power consumption tasks with low priority are stopped from working in the period, and the power consumption plan is re-planned.
In this embodiment, a user newly adds an electricity utilization task at a certain time, and the newly added electricity utilization task causes that the electricity utilization task in the time period cannot be normally performed, calculates an electricity utilization emergency coefficient of the electricity utilization task in the time period according to the electricity utilization emergency coefficient, and calculates a comprehensive electricity utilization emergency index by combining with a reliability index. And finally, according to the comprehensive electricity utilization emergency index, performing priority sequencing on the electricity utilization tasks, stopping the electricity utilization task with the lowest priority from working in the period, and re-planning the electricity utilization plan.
TABLE 4 electric load comprehensive power utilization emergency index
According to the table 4, the priority ranking sequence of the comprehensive power utilization emergency indexes of the power utilization equipment in the time period is known, namely dish washing machine 2 > washing machine = air conditioner > water heater > electric vehicle, so that the priority of the electric vehicle is lowest, the electric vehicle stops working in the time period, whether the total load power exceeds the upper limit of the household power utilization power is judged again, if the total load power still exceeds the upper limit of the household power utilization power, the water heater stops working in the time period \8230 \ 8230, the water heater stops working in the time period until the constraint of the household power utilization power is met, and the power utilization plan of the stopped power utilization equipment is planned again.
Finally, it should be noted that: the above embodiments are only used to illustrate the technical solution of the present invention, and not to limit the same; while the invention has been described in detail and with reference to the foregoing embodiments, it will be understood by those skilled in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the scope of the technical solutions of the embodiments of the present invention.
Claims (3)
1. A household intelligent power utilization optimization method considering uncertainty of power utilization behaviors of users is characterized by comprising the following steps:
step 1: setting a household intelligent power utilization optimization cycle, and uniformly dividing the household intelligent power utilization optimization cycle into a plurality of sub-time periods;
and 2, step: setting an initial constraint condition, and acquiring power price information and an upper limit of household power consumption, wherein the initial constraint condition comprises a comfort level range of a user and a time range of the flexible load allowed to work;
and step 3: a user sets reliability indexes for various loads according to the requirement of the user on the power utilization reliability of the power utilization equipment, and normalizes the reliability indexes of the various loads;
and 4, step 4: constructing a family energy source optimization scheduling model taking the minimum family electricity consumption cost as an objective function;
and 5: on the premise of meeting the initial constraint condition of the user, the current power utilization plan of the user is solved by considering the setting of various load reliability indexes of the user day ahead, and the household power utilization equipment works according to the current power utilization plan on the next day;
the solving of the user day-ahead power utilization plan comprises the following steps:
on the basis of initial constraint conditions set by a user, the reliability indexes of various power loads are considered, new constraint comprehensive original constraint conditions obtained by the reliability indexes are added into an intelligent power utilization optimization problem, and a day-ahead power utilization plan considering the reliability indexes is finally obtained; and 6: when the real-time operation, whether family's energy management system judges the user has the action of increase and decrease power consumption plan, according to the user increase and decrease power consumption plan's concrete action, corresponding adjustment power consumption plan formulates real-time power consumption plan, specifically includes:
when the power utilization tasks are reduced, the rest power utilization tasks are re-planned in the current time period to obtain the latest power utilization arrangement;
when a new power utilization task is newly added, whether the total power of the load exceeds the upper limit of the household power utilization is judged when the new power utilization task and a task of a day-ahead power utilization plan are simultaneously carried out, if not, the day-ahead power utilization plan is not changed, otherwise, the priority ranking is carried out on the power utilization tasks in the period according to the power utilization emergency coefficient and the comprehensive power utilization emergency index, the power utilization tasks with low priority are stopped from working in the period, and the power utilization plan is re-planned;
the electricity utilization emergency coefficient comprises:
the power utilization emergency coefficient of the uninterruptible load is as follows:
wherein alpha is 1 Emergency coefficient of electricity, t, representing an uninterruptible load L Indicating the number of electricity consumption periods, t, required for the operation of an uninterruptible load i Indicates the current time, t 2 A cut-off time indicating allowable power usage;
the power utilization emergency coefficient of the interruptible load is as follows:
wherein alpha is 2 Power emergency coefficient, W, representing interruptible load re Representing the difference between the total power consumed and the consumed power required by the electricity consumption task at the current moment after the interruptible load is cut off, q max Representing the maximum power that the interruptible load may consume per unit time period, t i Indicates the current time, t 2 A cutoff time indicating allowable power usage;
the power utilization emergency coefficient of the air conditioner is as follows:
wherein alpha is 3 Represents the electricity utilization emergency coefficient of the air conditioner,
indicating the current room temperature at that moment, theta cmax 、θ cmin Respectively representing the upper limit and the lower limit of the comfort temperature of the air conditioner;
the emergency coefficient of the water heater is as follows:
wherein alpha is 4 Represents the electricity utilization emergency coefficient of the water heater,
indicates the current water temperature at that time, theta wmax 、θ wmin Respectively representing the upper limit and the lower limit of the temperature of the water heater;
the comprehensive electricity utilization emergency index is as follows:
β i ＝α i Y i
wherein, beta i Indicating the combined electricity emergency index, alpha, of the load i i Power consumption emergency coefficient, Y, representing load i i And representing the reliability index after the load i is normalized.
2. The household intelligent power utilization optimization method according to claim 1, wherein the setting of the reliability index for each type of load in step 3 includes setting:
a reliability index of the uninterruptible load;
a reliability index of the interruptible load;
reliability index of the air conditioner; and
and (4) reliability index of the water heater.
3. The household intelligent power utilization optimization method according to claim 2,
the reliability indexes of the uninterruptible load are as follows:
Δt＝t 1 -t 1 ′＝t 2 -t 2 ′
where Δ t denotes the uninterruptible load double-ended time margin value, t 1 Starting time, t, representing the range of permissible operating times set by the user 2 Cutoff time, t, representing the range of allowable operating times set by the user 1 ' indicates the starting time, t, of the electricity consuming task for which the time margin value is reserved 2 ' represents the cut-off time of the power utilization task for which the time margin value is reserved;
the reliability index of the interruptible load is as follows:
wherein rho represents the completion rate of the power utilization task before a certain moment, and the value range of lambda is [0, 1%]，Q j Representing the total electric energy consumed by the load j to finish the electricity utilization task;
represents the power consumed by the interruptible load j at time t; t is t 1 A start time, t, representing the range of allowable operating times set by the user 2 An expiration time representing the allowable operating time range set by the user;
the reliability indexes of the air conditioner are as follows:
Δθ c ＝θ cmax -θ′ cmax ＝θ cmin -θ′ cmin
wherein, delta theta c Indicating air conditioner double-end temperature margin value theta cmax Represents the upper limit, theta, of the air conditioning comfort temperature range set by the user cmin Represents the lower limit, theta ', of the air-conditioning comfort temperature range set by the user' cmax Denotes the upper temperature limit, θ' cmin A lower temperature limit representing a retention temperature margin;
the reliability indexes of the water heater are as follows:
Δθ w ＝θ wmin -θ′ wmin
wherein, delta theta w Represents a lower temperature margin value, theta wmin Represents that a user sets a water heater water temperature lower limit theta' wmin The lower limit of the water temperature indicating the retention temperature margin.
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| CN104778504A (en) * | 2015-03-18 | 2015-07-15 | 南京邮电大学 | Electricity utilization arrangement optimization method for intelligent household electrical appliances |
| CN107451931A (en) * | 2017-07-28 | 2017-12-08 | 河海大学 | The Optimization Scheduling of home intelligent power equipment |
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| CN104778504A (en) * | 2015-03-18 | 2015-07-15 | 南京邮电大学 | Electricity utilization arrangement optimization method for intelligent household electrical appliances |
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