CN112749916A - User energy efficiency evaluation method based on resident fine-grained electricity consumption behavior data - Google Patents
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Abstract
The invention discloses a user energy efficiency evaluation method based on resident fine-grained electricity consumption behavior data, which comprises standby electrical appliance power consumption evaluation and heat preservation performance evaluation of heat preservation electrical appliances; the power consumption evaluation of the standby electrical appliance comprises the following steps: counting the active time interval and the inactive time interval of a user, and respectively calculating the standby power consumption of the active time interval and the standby power consumption of the inactive time interval of the user; the evaluation of the heat preservation performance of the heat preservation type electric appliance comprises the following steps: collecting fine-grained energy consumption data; judging a heat preservation heating event and heating time; analyzing data according to energy conservation; the insulation performance data is defined and referenced. The method captures the electric appliance types, the time sequence operation characteristics and the energy consumption conditions of the standby electric appliances and the heat-preservation electric appliances based on the fine-grained electricity consumption behavior data of residents, and performs 'black box' analysis and evaluation, thereby pertinently providing personalized energy consumption push suggestions to users.
Description
Technical Field
The invention relates to the technical field of power distribution and utilization and big data application, in particular to a user energy efficiency evaluation method based on resident fine-grained power utilization behavior data.
Background
With the improvement of comprehensive national power and the rapid development of national economy, the demand of various industries on power consumption is rapidly increased day by day, so that the supply and the demand of electric energy are greatly disconnected. Importantly, compared with the international advanced level, the electric energy utilization efficiency of China is low, and improvement on the electric energy utilization efficiency and the energy-saving technology is urgently needed to be solved.
The energy efficiency management is enhanced in production and life, so that energy is saved, and economic benefits are improved. For example, in residential electricity consumption, energy efficiency management is required to reduce unnecessary consumption because unnecessary electricity consumption is excessive due to a problem of electricity usage habits. The traditional energy efficiency management system has the defects that monitoring and management of energy consumption are relatively extensive, careful management of energy consumption conditions of energy consumption appliances, namely energy consumption processes, is lacked, at present, some main energy consumption nodes are mainly monitored, only statistics of the overall energy consumption condition is carried out, targeted management and control are lacked, manual recording is mostly adopted, the problems of asynchronous recording, real-time recording and the like exist, energy consumption data and operation parameters flow into a form, the user management efficiency is low, and the energy utilization rate is low. Therefore, it is important to provide a targeted energy efficiency management.
The non-invasive load identification advanced measurement technology is a leading-edge data acquisition technology in the field of power distribution and utilization, and realizes the purpose that massive fine-grained power utilization behavior data of the individual electric appliances can be acquired without entering a resident family, wherein the fine-grained power utilization behavior data comprises an electric appliance type, operation time and power consumption ternary sequence, and for example, an invention patent with the application number of 201811582689.8, which is provided by the institute of electrical power science in China, is also an improvement based on the technology. By fully utilizing the technology, the energy consumption condition analysis of the power consumption of the user can be realized in a targeted manner.
Disclosure of Invention
The invention aims to provide a user energy efficiency evaluation method based on resident fine-grained electricity consumption behavior data, which can be used for analyzing energy consumption of user electricity in a targeted manner, so that a personalized energy-saving suggestion scheme is provided for the user.
In order to achieve the above purpose, the invention provides the following technical scheme: a user energy efficiency assessment method based on resident fine-grained electricity consumption behavior data comprises standby electrical appliance power consumption assessment and heat preservation performance assessment of heat preservation electrical appliances;
the power consumption evaluation of the standby electrical appliance comprises the following steps: counting the active time interval and the inactive time interval of a user, and respectively calculating the standby power consumption of the active time interval and the standby power consumption of the inactive time interval of the user;
the evaluation of the heat preservation performance of the heat preservation type electric appliance comprises the following steps: collecting fine-grained energy consumption data; judging a heat preservation heating event and heating time; analyzing data according to energy conservation; the insulation performance data is defined and referenced.
Further, in the power consumption evaluation of the standby electrical appliance, the active period is defined as:
TA＝{t|Wt≥Wmin+0.3×(Wmax-Wmin)} (1)
in the formula: t is the set of active periods, WminMinimum power consumption in 15min of the day, WmaxMaximum power consumption for 15min on the day;
inactive period-total period of the day-active period
The active period standby power consumption and the inactive period standby power consumption are respectively the lowest values of the used electric power in the corresponding periods.
Further, the specific steps of the evaluation of the heat preservation performance of the heat preservation type electric appliance are as follows:
s1, collecting fine-grained energy data: recording the starting and stopping time, the heating power and the electric quantity consumption value of the heat-preservation electric appliance, and judging the heating event of the heat-preservation electric appliance caused by natural heat dissipation according to the heating power and the electric quantity consumption value;
s2, judging heat preservation heating events and heating time: counting the heating times and the heating duration of the heat-preservation electric appliance on time, and selecting the heating duration with the most frequent heating duration as the heating duration of the heat-preservation heating event and the corresponding heating times;
s3, analyzing data according to energy conservation: the heat loss of the water body in the heat preservation type electric appliance which is lower than the heat preservation value and the electric energy conservation consumed by the heat preservation type electric appliance for heating the water body to the heat preservation value are as follows:
finishing to obtain:
in the formula: eheatThe unit is kW.h for consumed electric quantity; pheatThe unit is kW which is the heating power of the heat-preservation electric appliance; c is the specific heat capacity of water, i.e. 4.2X 103J/(kg. DEG C); the temperature T of the water body is the insulation value set by the insulation type electrical appliancesetAnd a heating start temperature TbottomIs normally Δ T ∈ [3,5 ]]DEG C; ρ is the density of water, ρ is 1 × 103kg/m3；VhThe volume of the heat preservation type electric appliance is L.
S4, defining and referring to the thermal insulation performance parameters: counting the stable distribution condition of the time interval between the heat preservation heating event and the last heating event, and defining the stable distribution condition as measuring the actual heat preservation performance parameters of the heat preservation type electric appliance, namely:
combining formulas (3) and (4) to obtain:
in the formula, λbwThe temperature per hour of the unit volume of the heat-insulating electric appliance is shown as ℃/(L.h).
Compared with the prior art, the invention has the advantages that: the method captures the electric appliance types, the time sequence operation characteristics and the energy consumption conditions of the standby electric appliances and the heat-preservation electric appliances based on the fine-grained electricity consumption behavior data of residents, and performs 'black box' analysis and evaluation, thereby pertinently providing personalized energy consumption push suggestions to users.
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FIG. 1 is a block flow diagram of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further specifically described below by way of embodiments in combination with the accompanying drawings.
Example (b): a user energy efficiency evaluation method based on resident fine-grained electricity consumption behavior data is mainly reflected in user energy characteristic analysis, and comprises power consumption evaluation on air conditioners, televisions, lamp waiting machine type electric appliances and heat preservation performance evaluation on heat preservation type electric appliances such as electric water heaters and the like, as shown in figure 1.
The standby type electric appliance power consumption evaluation obtains the standby power consumption of the user by counting the power consumption of the user in idle time. And establishing a Gaussian distribution model, and carrying out a proposal of standby power consumption aiming at a user with higher standby power consumption to remind related users of managing a standby machine, a lamp and the like.
Specifically, the calculation of the standby power consumption needs to count the active periods of the users, and calculate the standby power consumption of the active periods and the standby power consumption of the inactive periods of the users respectively.
The active period is defined as:
TA＝{t|Wt≥Wmin+0.3×(Wmax-Wmin)} (1)
in the formula: t is the set of active periods, WminMinimum power consumption in 15min of the day, WmaxMaximum power consumption for 15min on the day;
inactive period-total period of the day-active period
After the active time periods and the inactive time periods of the users are collected, the lowest value of electric power used in all the time periods is respectively counted as the standby power consumption of each time period, and therefore the users with high standby power consumption are advised to perform standby power consumption, and related users are reminded to manage the standby electric appliances in the characteristic time periods.
The evaluation of the heat preservation performance of the heat preservation type electric appliance is to obtain the heat preservation power consumption of the user through statistical analysis of the heating event, the heating time and the heating time interval of the heat preservation type electric appliance of the user. And establishing a Gaussian distribution model, and carrying out heat preservation power consumption suggestion aiming at a user with higher heat preservation power consumption to remind related users of managing the operation state and the heat preservation performance of the heat preservation type electric appliance.
Taking the thermal insulation performance evaluation of the electric water heater as an example, the evaluation method comprises the following steps:
1) fine-grained energy usage data is collected. Recording the starting and stopping time, heating power and electric quantity consumption value of the electric water heater, and judging the heating event of the electric water heater caused by natural heat dissipation according to the time.
2) And judging the heat preservation heating event and the heating time. The heating times and the heating duration of the electric water heater are counted on time, the heating duration with the most frequent heating duration is selected as the heating duration of the heat preservation heating event, the value of the heating duration is 1-6 s, and the corresponding heating times are 30-900.
3) Data analysis was performed based on conservation of energy. The heat loss of the water body in the electric water heater, which is lower than the heat preservation value, and the electric energy conservation consumed by the electric water heater to heat the water body to the heat preservation value are as follows:
after the treatment, the product is obtained,
in the formula: eheatThe unit is kW.h for consumed electric quantity; pheatThe unit is kW which is the heating power of the heat-preservation electric appliance; c is the specific heat capacity of water, i.e. 4.2X 103J/(kg. DEG C); the temperature T of the water body is the insulation value set by the insulation type electrical appliancesetAnd a heating start temperature TbottomIs normally Δ T ∈ [3,5 ]]DEG C; ρ is the density of water, ρ is 1 × 103kg/m3；VhThe volume of the heat preservation type electric appliance is L.
4) Defining and referring to the thermal insulation performance parameters: the stable distribution condition of the time interval between the heat preservation heating event and the last heating event is counted, and the stable distribution condition is defined as measuring the actual heat preservation performance parameters of the electric water heater, namely:
the two types are combined to obtain
In the formula, λbwThe temperature per hour of the unit volume of the heat-insulating electric appliance is shown as ℃/(L.h). The larger the formula is, the worse the actual heat insulation performance of the electric water heater is, and on the contrary, the actual heat insulation performance of the electric water heater is better.
In the embodiment, through capturing the electric appliance types, the time sequence operation characteristics and the energy consumption conditions of the standby electric appliance and the heat-preservation electric appliance, personalized energy use pushing suggestions are provided for users in a targeted manner, wherein the suggestions include suggestions for pushing electrical appliance switches for turning off standby televisions, lamps and the like to users with higher standby power consumption in time; pushing a reasonable use suggestion of the electric water heater to a user with higher heat preservation power consumption; and the health state of the heat preservation electric appliance is pushed to the user by counting and analyzing the heating times and the heating duration of the users in the area.
The above embodiments are merely illustrative of the technical ideas and features of the present invention, and the purpose thereof is to enable those skilled in the art to understand the contents of the present invention and implement the present invention, and not to limit the protection scope of the present invention. All equivalent changes and modifications made according to the spirit of the present invention should be covered within the protection scope of the present invention.
Claims (3)
1. A user energy efficiency assessment method based on resident fine-grained electricity consumption behavior data is characterized by comprising standby electrical appliance power consumption assessment and heat preservation performance assessment of heat preservation electrical appliances;
the power consumption evaluation of the standby electrical appliance comprises the following steps: counting the active time interval and the inactive time interval of a user, and respectively calculating the standby power consumption of the active time interval and the standby power consumption of the inactive time interval of the user;
the evaluation of the heat preservation performance of the heat preservation type electric appliance comprises the following steps: collecting fine-grained energy consumption data; judging a heat preservation heating event and heating time; analyzing data according to energy conservation; the insulation performance data is defined and referenced.
2. The method according to claim 1, wherein in the power consumption evaluation of the standby electrical appliance, the active time period is defined as:
TA＝{t|Wt≥Wmin+0.3×(Wmax-Wmin)} (1)
in the formula: t is the set of active periods, WminMinimum power consumption in 15min of the day, WmaxMaximum power consumption for 15min on the day;
inactive period-total period of the day-active period
The active period standby power consumption and the inactive period standby power consumption are respectively the lowest values of the used electric power in the corresponding periods.
3. The user energy efficiency evaluation method based on resident fine-grained electricity consumption behavior data according to claim 1, characterized in that the specific steps of the heat preservation performance evaluation of the heat preservation type electric appliance are as follows:
s1, collecting fine-grained energy data: recording the starting and stopping time, the heating power and the electric quantity consumption value of the heat-preservation electric appliance, and judging the heating event of the heat-preservation electric appliance caused by natural heat dissipation according to the heating power and the electric quantity consumption value;
s2, judging heat preservation heating events and heating time: counting the heating times and the heating duration of the heat-preservation electric appliance on time, and selecting the heating duration with the most frequent heating duration as the heating duration of the heat-preservation heating event and the corresponding heating times;
s3, analyzing data according to energy conservation: the heat loss of the water body in the heat preservation type electric appliance which is lower than the heat preservation value and the electric energy conservation consumed by the heat preservation type electric appliance for heating the water body to the heat preservation value are as follows:
finishing to obtain:
in the formula: eheatThe unit is kW.h for consumed electric quantity; pheatThe unit is kW which is the heating power of the heat-preservation electric appliance; c is the specific heat capacity of water, i.e. 4.2X 103J/(kg. DEG C); the temperature T of the water body is the insulation value set by the insulation type electrical appliancesetAnd a heating start temperature TbottomIs normally Δ T ∈ [3,5 ]]DEG C; ρ is the density of water, ρ is 1 × 103kg/m3；VhThe volume of the heat preservation type electric appliance is L.
S4, defining and referring to the thermal insulation performance parameters: counting the stable distribution condition of the time interval between the heat preservation heating event and the last heating event, and defining the stable distribution condition as measuring the actual heat preservation performance parameters of the heat preservation type electric appliance, namely:
combining formulas (3) and (4) to obtain:
in the formula, λbwThe temperature per hour of the unit volume of the heat-insulating electric appliance is shown as ℃/(L.h).
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| CN110765595A (en) * | 2019-10-10 | 2020-02-07 | 内蒙古农业大学 | SDN data center network flow scheduling algorithm based on multi-layer virtual topology energy saving |
| CN111859611A (en) * | 2020-06-05 | 2020-10-30 | 国网山东省电力公司济南供电公司 | Method for evaluating actual heat-insulating performance of electric water heater based on fine-grained energy consumption data |
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| CN110765595A (en) * | 2019-10-10 | 2020-02-07 | 内蒙古农业大学 | SDN data center network flow scheduling algorithm based on multi-layer virtual topology energy saving |
| CN111859611A (en) * | 2020-06-05 | 2020-10-30 | 国网山东省电力公司济南供电公司 | Method for evaluating actual heat-insulating performance of electric water heater based on fine-grained energy consumption data |
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