CN109767080A - A kind of Demand Side Response appraisal procedure of Communities ' Integrated energy resource system - Google Patents
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Abstract
The present invention relates to a kind of Demand Side Response appraisal procedures of Communities ' Integrated energy resource system, the following steps are included: 1) using economic indicator, environmental index, target energy and reliability index as the first class index of assessment models, and determine the two-level index under each first class index；2) coupled weight for considering each first class index and two-level index and each two-level index, constructs Demand Side Response assessment models；3) assessment result of side response assessment models carries out Optimized Operation a few days ago to selected system requirements side flexible load according to demand.Compared with prior art, the present invention has many advantages, such as that comprehensive assessment, consideration are comprehensive.
Description
Technical Field
The invention relates to the field of community source-load scheduling, in particular to a demand side response evaluation method of a community comprehensive energy system.
Background
At present, the research on the demand side mainly considers the peak clipping of the electric energy, and the demand side of the comprehensive energy system is greatly different from the demand side in the traditional sense. Specifically, since the demand side of the integrated energy system contains three energy sources of electricity, heat, and cold, which are supplied through a CCHP (combined cooling-heating-electricity) system, the response of the flexible loads of the three energy sources must be fully considered in scheduling thereof, not just the single response of the electric energy.
The evaluation of the demand side of the comprehensive energy system is only slightly researched at the present stage, and the evaluation method for the demand side of the comprehensive energy system is different from the evaluation of the demand response effect by load peak clipping load of the demand side in the prior art, and the evaluation of the effect after the demand response is carried out by the influence on environment, economy, energy and environment after the demand response.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provide a demand side response evaluation method of a community integrated energy system.
The purpose of the invention can be realized by the following technical scheme:
a demand side response evaluation method of a community integrated energy system comprises the following steps:
1) taking an economic index, an environmental index, an energy index and a reliability index as primary indexes of an evaluation model, and determining secondary indexes under each primary index;
2) considering each first-level index, each second-level index and the subjective and objective coupling weight of each second-level index, and constructing a demand side response evaluation model;
3) and obtaining index values before and after the response of the demand side according to the demand side response evaluation model, comparing the index values, and performing optimized response according to the comparison result.
The secondary indexes under the economic indexes comprise daily operation comprehensive cost, the secondary indexes under the environmental indexes comprise daily emission of carbon dioxide and equivalent daily emission reduction of carbon dioxide, the secondary indexes under the energy indexes comprise daily consumption of primary energy and utilization rate of clean energy, and the secondary indexes under the reliability indexes comprise energy shortage rate.
In the step 2), the expression of each secondary index is as follows:
daily emission of carbon dioxide AI：
Therein, ζ1、ζ2、ζ3Respectively the amount of carbon dioxide generated by the unit heat output of the gas boiler, the amount of carbon dioxide generated by the unit electric energy produced by the gas turbine and the amount of carbon dioxide generated by the unit electric energy produced by the traditional coal-fired power plant, PGB、PMT、PnetRespectively outputting thermal power, electric power output by a gas turbine and electric power purchased to a large power grid for the gas-fired boiler in the time t;
daily equivalent carbon dioxide emission reduction AII：
Wherein,the method is characterized in that the method is the amount of carbon dioxide generated when all electric, hot and cold flexible loads do not participate in optimized scheduling and no coupling exists among the electric, hot and cold loads in a day;
energy deficit rate BI：
Wherein,purchasing electric power from the grid for the system in one day, WE+WH/γ+WCGamma is the amount of all loads of the system converted into electric loads in one day, gamma is the energy efficiency ratio of electric heating and cooling, WEFor electric energy consumed by the system during one day, WHFor thermal energy consumed by the system in one day, WCThe cold energy consumed in one day by the system.
Daily running integrated cost CI：
CI＝FGB+Fnet+FMT+FDG
Wherein, FGB、Fnet、FMT、FDGRespectively the operation cost of the gas boiler, the cost of purchasing electricity from a power grid, the operation cost of the gas turbine, the cost of outputting new energy, KGB、Kb、KMT、Kw、KpvThe cost coefficient of each output unit of thermal power of the gas boiler, the time-of-use electricity price for purchasing electricity to the power grid, the cost coefficient of each output unit of electric power of the gas turbine, the output cost of the wind turbine, the photovoltaic output cost, Pw、PpvWind power generator and photovoltaic output power respectively;
daily consumption of primary energy DI：
Wherein m is1、m2Respectively the standard coal consumed by the traditional coal-fired power plant per unit of electric power production and the equivalent standard coal consumed by the gas-fired boiler per unit of thermal power outputAnd (4) the coefficient.
Clean energy utilization rate:
in the step 2), a comprehensive weighting method considering a network analysis method and an entropy weight method is adopted to obtain the subjective and objective coupling weight p of the ith secondary indexiThen, there are:
wherein, ω isiThe weight, mu, obtained by network analysis for the ith secondary indexiWeights obtained by entropy weighting for the ith secondary indicator, αi、βiIs an intermediate variable.
The demand side response evaluation model is the multiplication sum of each secondary index and each secondary index coupling weight.
And in the step 3), obtaining the secondary index with the maximum score improvement according to the scores before and after the response of the demand side and each secondary index value, and performing response optimization according to the secondary indexes.
Compared with the prior art, the invention has the following advantages:
firstly, comprehensive evaluation: the existing demand side response evaluation only considers the single evaluation of the electric load response, and the invention considers the effect evaluation of the simultaneous response of the three loads of electricity, heat and cold of the comprehensive energy system.
Secondly, the consideration is comprehensive: the index in evaluating the demand response is no longer limited to a single quantitative index of load peak-clipping load amount, but the level of demand response is evaluated from the aspects of economy, environment, energy, reliability, and the like.
Drawings
FIG. 1 is an evaluation flow chart of the present invention.
FIG. 2 is a diagram of an evaluation index system.
Fig. 3 is a schematic structural diagram of the integrated energy system.
Fig. 4 is a load prediction diagram.
Detailed Description
The invention is described in detail below with reference to the figures and specific embodiments.
Examples
The present invention will be described in detail below with reference to a flowchart and specific examples.
1. As shown in fig. 1, fig. 1 is an evaluation flow chart of the present invention.
2. Demand side flexible load analysis
The comprehensive energy system divides the user load into 4 types according to the mode that the load participates in demand response:
(1) basic load: this type of load is an uncontrollable load, which responds completely to the needs of the user, and the system cannot change its energy use mode and time.
(2) Translatable load: the load power supply time can change according to a plan, the load needs to be integrally translated, and the power utilization time also spans a plurality of scheduling time intervals.
(3) The load can be reduced: the system can bear certain interruption or power reduction, reduce the load of time operation and partially or completely reduce the load according to the supply and demand conditions.
(4) The transferable load: the power consumption of each time period can be flexibly adjusted, but the total load of the whole period after the transfer is kept unchanged with the total load before the transfer.
Wherein, the 'translatable load' and the 'translatable load' both have the characteristic that the power supply time of the load changes according to a plan, but the two are also distinguished: the 'translatable load' needs to be translated integrally, the electricity utilization time cannot be interrupted, the duration time is fixed, and the power required by the electricity utilization time period cannot be changed, such as a washing machine, a disinfection cabinet and the like; the transferable load is more flexible than the transferable load, the electricity consumption in the electricity consumption period can be flexibly adjusted, the electricity consumption period is allowed to be interrupted, the duration is not fixed, the total amount of the load requirements before and after transferring is only required to be met, the electric automobile is a typical transferable load, the charging time and the charging power of the electric automobile can be adjusted in the ordered charging mode, and the required total charging amount is not changed. Considering that users are more sensitive to heat loads, only translatable, reducible load characteristics of heat and cold loads are considered herein.
3. Demand response optimized scheduling
The invention aims at the lowest daily operation cost of the comprehensive energy system, predicts the load and the new energy output day before, takes 24 hours as a scheduling period and takes 1 hour as a scheduling interval to optimally schedule the flexible load, and the result is shown in figure 3.
The following data are respectively the influence data on economy, environment, energy and reliability before and after demand side scheduling:
TABLE 1 impact on economics
| Economy of production | Daily operating cost (Yuan/Ri) |
| Demand side unresponsive | 8768.5 |
| Demand side response | 7996.7 |
TABLE 2 Effect on the Environment
| Environment(s) | Daily emission of carbon dioxide (t/day) | Daily equivalent carbon dioxide emission reduction (t/day) |
| Demand side unresponsive | 1.59 | 1.12 |
| Demand side response | 1.35 | 1.36 |
TABLE 3 Effect on energy
| Energy source | Daily consumption of primary energy (t/day) | Clean energy utilization (/) |
| Demand side unresponsive | 3.7 | 20.3％ |
| Demand side response | 3.35 | 21.5％ |
TABLE 4 Effect on reliability
As can be seen from the above table, based on the optimized scheduling of the electricity, heat and cold flexible loads on the demand side, in the aspect of the economic index of the comprehensive energy system, the energy outsourcing cost can be saved by 8.8% every day; in the aspect of environmental indexes, the carbon dioxide emission amount per day is reduced from 1.59t to 1.35t, and the equivalent carbon dioxide emission reduction amount per day is increased from 1.12t to 1.36 t; in the aspect of energy indexes, the daily consumption of primary energy is reduced from 3.7t to 3.35t, and the utilization rate of clean energy is not increased much because the depreciation cost of equipment is considered; in terms of reliability, the energy shortage rate is reduced from the former 35.4% to 31.1%. In conclusion, in the front-back comparison considering the response of the demand side, all indexes can be intuitively seen to be improved. In particular, relatively large results are achieved in economic and environmental aspects.
4. Index empowerment
The invention adopts a subjective and objective weighting method, namely a network analysis method is used as the subjective weighting method, and an entropy weighting method is used as the objective weighting method. The following table shows the index weights of the network analysis:
TABLE 5 subjective weights
| Index (I) | A1 | B1 | B2 | C1 | C2 | D1 |
| Weight of | 0.2664 | 0.1052 | 0.1225 | 0.0951 | 0.0947 | 0.3161 |
The following table is the entropy weight method weight:
TABLE 6 Objective weights
| Index (I) | A1 | B1 | B2 | C1 | C2 | D1 |
| Weight of | 0.1667 | 0.1667 | 0.1667 | 0.1667 | 0.1667 | 0.1667 |
Calculating the weight omega of each index by using an analytic hierarchy process1、ω2、····ωn. Then, the entropy weight method is used to calculate the weight mu of each index1、μ2、····μn。Coupling weight
TABLE 7 Objective and subjective weights
| Index (I) | A1 | B1 | B2 | C1 | C2 | D1 |
| Composite weight | 0.1634 | 0.1628 | 0.1540 | 0.1707 | 0.1711 | 0.1780 |
5. Scoring function
And respectively judging the corresponding relation between the index values before and after the demand response and the scores of the index values according to the numerical values of the indexes before and after the demand side response and a Delphi method, and fitting the corresponding relation between the index values and the scores into a scoring function by adopting a least square method. And substituting various index values before and after the demand response into a scoring function to obtain the evaluation score of the index value, and finally multiplying the evaluation scores of all links by the corresponding coupling weights and summing to obtain the total score of the system demand response evaluation.
The grade set by the invention is as follows:
TABLE 8 Scoring rating
| Grade | Height of | Is higher than | Medium and high grade | Is lower than | Is low in |
| Score of | ≥80 | ≥70 | ≥60 | ≥50 | ＜50 |
The method comprises the following steps:
TABLE 9 score of each link
| Score table | Not considering demand response | Considering demand response |
| Economy of production | 54.9 | 73.3 |
| Environment(s) | 62.1 | 74.5 |
| Energy source | 61.2 | 67.3 |
| Reliability | 60.9 | 66.5 |
| Total score | 60.5 | 70.4 |
It can be seen from the above table that thanks to the demand response, the economic cost of the system is increased from a lower development level to a higher development level, the environmental aspect is increased from a medium development level to a higher development level, and the scores in the energy aspect and the reliability aspect are increased to some extent, so that the overall score of the construction level of the demand side of the system is increased from the medium development level to the higher development level, and the importance of the demand side construction is verified.
Claims (6)
1. A demand side response evaluation method of a community integrated energy system is characterized by comprising the following steps:
1) taking an economic index, an environmental index, an energy index and a reliability index as primary indexes of an evaluation model, and determining secondary indexes under each primary index;
2) considering each first-level index, each second-level index and the subjective and objective coupling weight of each second-level index, and constructing a demand side response evaluation model;
3) and obtaining index values before and after the response of the demand side according to the demand side response evaluation model, comparing the index values, and performing optimized response according to the comparison result.
2. The method as claimed in claim 1, wherein the secondary indicators of the economic indicators include daily running total cost, the secondary indicators of the environmental indicators include daily emission of carbon dioxide and equivalent daily emission reduction of carbon dioxide, the secondary indicators of the energy indicators include daily consumption of primary energy and utilization of clean energy, and the secondary indicators of the reliability indicators include energy shortage.
3. The method for assessing the demand side response of the community integrated energy system according to claim 2, wherein in the step 2), the expressions of the secondary indexes are as follows:
daily emission of carbon dioxide AI：
Therein, ζ1、ζ2、ζ3Respectively the amount of carbon dioxide generated by the unit heat output of the gas boiler, the amount of carbon dioxide generated by the unit electric energy produced by the gas turbine and the amount of carbon dioxide generated by the unit electric energy produced by the traditional coal-fired power plant, PGB、PMT、PnetRespectively outputting thermal power, electric power output by a gas turbine and electric power purchased to a large power grid for the gas-fired boiler in the time t;
daily equivalent carbon dioxide emission reduction AII：
Wherein,all electricity and heat in one dayThe cold flexible load does not participate in the optimized scheduling, and the quantity of carbon dioxide generated when no coupling exists among electricity, heat and cold;
energy deficit rate BI：
Wherein,purchasing electric power from the grid for the system in one day, WE+WH/γ+WCGamma is the amount of all loads of the system converted into electric loads in one day, gamma is the energy efficiency ratio of electric heating and cooling, WEFor electric energy consumed by the system during one day, WHFor thermal energy consumed by the system in one day, WCThe cold energy consumed in one day by the system.
Daily running integrated cost CI：
CI＝FGB+Fnet+FMT+FDG
Wherein, FGB、Fnet、FMT、FDGRespectively the operation cost of the gas boiler, the cost of purchasing electricity from a power grid, the operation cost of the gas turbine, the cost of outputting new energy, KGB、Kb、KMT、Kw、KpvAre respectively asCost coefficient of thermal power per output unit of gas boiler, time-of-use electricity price for purchasing electricity to power grid, cost coefficient of electric power per output unit of gas turbine, output cost of wind turbine, photovoltaic output cost, Pw、PpvWind power generator and photovoltaic output power respectively;
daily consumption of primary energy DI：
Wherein m is1、m2The standard coal consumption of the traditional coal-fired power plant per unit of electric power production and the equivalent standard coal coefficient of the traditional gas-fired power plant per unit of thermal power output are respectively consumed.
Clean energy utilization rate:
4. the method for assessing the response of the demand side of the community integrated energy system as claimed in claim 3, wherein in the step 2), the comprehensive weighting method considering the network analysis method and the entropy weighting method is adopted to obtain the subjective and objective coupling weight p of the ith secondary indexiThen, there are:
wherein, ω isiThe weight, mu, obtained by network analysis for the ith secondary indexiWeights obtained by entropy weighting for the ith secondary indicator, αi、βiIs an intermediate variable.
5. The method as claimed in claim 3, wherein the demand-side response estimation model is a summation of multiplication of each secondary index and each secondary index coupling weight.
6. The method for assessing the response of the demand side of the community integrated energy system according to claim 1, wherein in the step 3), the secondary index which maximizes the score improvement is obtained according to the scores before and after the response of the demand side and the respective secondary index values, and the response optimization is performed according to the obtained secondary index.
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| CN111191876A (en) * | 2019-12-05 | 2020-05-22 | 国家电网有限公司 | Comprehensive energy system evaluation method for college park |
| CN112465240A (en) * | 2020-12-03 | 2021-03-09 | 上海电力大学 | Cooperative game-based multi-park energy scheduling optimization method for comprehensive energy system |
| CN113159540A (en) * | 2021-04-07 | 2021-07-23 | 国家电网公司华中分部 | Demand side resource cascade calling method and device considering load value |
| CN113469533A (en) * | 2021-07-02 | 2021-10-01 | 河海大学 | Power distribution network operation evaluation method containing comprehensive energy system |
| CN113554296A (en) * | 2021-07-16 | 2021-10-26 | 国网江苏省电力有限公司经济技术研究院 | Multi-index evaluation method for planning of park comprehensive energy system |
| CN115498668A (en) * | 2022-09-15 | 2022-12-20 | 国网上海市电力公司 | Optimization method of comprehensive energy system |
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