CN104950720A - Energy supply system combining demand response and comfort feedback on basis of weather forecast - Google Patents
Energy supply system combining demand response and comfort feedback on basis of weather forecast Download PDFInfo
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- CN104950720A CN104950720A CN201510334635.XA CN201510334635A CN104950720A CN 104950720 A CN104950720 A CN 104950720A CN 201510334635 A CN201510334635 A CN 201510334635A CN 104950720 A CN104950720 A CN 104950720A
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- G—PHYSICS
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- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B19/00—Programme-control systems
- G05B19/02—Programme-control systems electric
- G05B19/04—Programme control other than numerical control, i.e. in sequence controllers or logic controllers
Abstract
The invention discloses an energy supply system combining demand response and comfort feedback on the basis of weather forecast. According to the system, a demand response control module regulates the electricity consumption behavior of a user; a load predicating system performs load predication through weather bureau meteorological data, historical load information, energy supply building information and demand response control behavior to obtain the cold and heat electricity energy consumption demand of the user; then, an energy source management center makes an optimal operation strategy of a distributed energy supply system according to the user energy consumption demand; if the deviation exists between the system energy supply and the user comfort degree, the user can feed back self energy consumption correction information to the energy source management center through a user end monitoring module; the energy source management center corrects the operation strategy of the demand response control module and the distributed energy supply system. The energy supply system has the advantages that the intelligent energy supply on a building or a region can be realized; the goals of energy saving and emission reduction can also be achieved; the energy supply system belongs to an important technical measure for developing an intelligent city and a low-carbon city.
Description
Technical field
The present invention relates to new energy development and HVAC field, particularly relate to a kind of intelligent energy supply system demand response and comfort level feedback combined based on weather forecast.
Background technology
The trend of global warming is in recent years obvious, Melting Glaciers:, sea level rise, the deterioration of the ecological environment, various frequent natural calamity, social each development division door is faced with severe tests, and realizes the energy, the coordinated development of environment and economy become the target that the mankind pursue jointly.China is the contracting party of United Nations Framework Convention on Climate Change and " Tokyo protocol ".Carbon emission reduction task is huge, China is again developing country simultaneously, it is energy-consuming big country, energy-consuming accounts for 11% of the world, leap to second place of the world, but China's standard coal equivalent output efficiency per ton is only equivalent to 10.3% of Japan, 16.8% of European Union, 28.6% of the U.S., energy dissipation is serious, utilization ratio is low.Therefore, energy and environment problem is the current the biggest problem faced of China.
In fact Global climate change is not only the energy and environmental problem, also brings energy security problem simultaneously.After 20 century 70 first oil crisis outbursts, western developed country proposes the concept of energy security.Along with Iranian revolution, Persian Gulf War, California, USA power events, the generation successively of the event such as massive blackout that USSR (Union of Soviet Socialist Republics) and Japanese nuclear leakage accident and Chinese severe snow cause, energy security is more and more subject to the attention of various countries.China starts to increase sharply from the nineties to the demand of the energy, and changes importer into from oil exporting country from 1993.Because domestic to energy demand continuous enlargement, allow China rely on foreign oil import gradually, relative to the 90 day strategic reserves of industrial country on Oil Projects, China only has the preparation of more than 20 day.Energy structure is particularly thorny, too much dependence traditional fossil energy, and energy transport exists hidden danger etc., and these Dou Shi China will solve the severe challenge that energy security problem faces.
Distributing-supplying-energy system is that one utilizes clean energy resource, provides the energy-provision way of cool and thermal power load simultaneously.Chinese scholars to distributed system done some research, China Wang Jiangjiang for Beijing, with photovoltaic, gas electricity generator, gas fired-boiler, solar thermal collector, heat recovery and memory storage, electricity refrigeration and absorption refrigeration construct the cool and thermal power system of a set of multipotency mixing
[1]; The Wu Qiong of China, for Japan, constructs the system that a set of CCHP is combined with donkey boiler, with economy, Environmental and primary energy economic ratio for target, has carried out comparative study to four kinds of different kinds of building in Japanese five typical weather cities
[2]; The Pierluigi Mancarell of Britain, for London, considers electric power repurchase, constructs a set of simple cooling heating and power generation system and to combine with additional combustion boiler, electric heating pump system, and be optimized system economy for the workload demand of Various Seasonal
[3].
But limit due to the coupling of distributed system cool and thermal power load, the not high factor of the imbalance of load supply and demand and intelligence degree, causes distributed system economy not ideal, and its applying at home is greatly limited.
Summary of the invention
The invention provides a kind of energy supplying system demand response control and comfort level feedback combined based on weather forecast, the present invention is while meeting the different comfort level needs of user, achieve energy-saving and emission-reduction again, meet the needs in practical application, described below:
Based on the energy supplying system that demand response control and comfort level feedback combine by weather forecast, described energy supplying system comprises:
Demand response control module, for monitoring the illumination of user and indoor temperature information, in conjunction with the demand response control strategy of operation of power networks information, indoor temperature, monochrome information output ustomer premises access equipment, and demand response control strategy is transferred to load prediction module;
Load prediction module, carries out load prediction for the historical load information by forecasting, meteorologic parameter and structure parameter, and is revised by energy demand forecast result by described demand response control strategy;
System equipment effectiveness models module, for according to the service data of each equipment or producer's sample data, make system equipment effectiveness models, the optimization aim for energy management center provides input data;
Energy management center, for by revised can demand forecast result and system equipment effectiveness models, according to each plant efficiency of distributing-supplying-energy system variation relation with rate of load condensate and temperature, with economy, optimum or Environmental optimum is for objective function, formulate operation reserve and control, the information then provided by user side monitoring modular is revised in real time to operation reserve again.
Wherein, described system equipment effectiveness models is specially:
Between the different-energy form of equipment, transformation efficiency η or COP is with the variation relation of rate of load condensate x and temperature T.
Wherein, the load prediction of described load prediction module is specially:
Q＝f(Q
h,T
o,T,d,F)
Wherein, Q
hfor history energy demand information, T
ofor outdoor temperature, T is the comfort temperature of indoor requirement, and d is outside humidity, and F is intensity of solar radiation.
The beneficial effect of technical scheme provided by the invention is: the present invention can realize the intelligent energy supply to building and region.By the accurate prediction using energy demand in real time with demand response combine with technique, the operation reserve of each equipment optimum of distributing-supplying-energy system can be made, revised operation reserve and demand response strategy by user side monitoring modular system, the comfort level needs that can meet user different can realize energy-saving and emission-reduction again again.
Accompanying drawing explanation
Fig. 1 is this intelligent energy supply system schematic;
Fig. 2 is distributed energy resource system schematic diagram;
In accompanying drawing, the list of parts representated by each label is as follows:
1: demand response control module; 2: distributing-supplying-energy system;
3: load prediction module; 4: energy management center;
5: user side monitoring modular; 6: system equipment effectiveness models module.
Embodiment
For making the object, technical solutions and advantages of the present invention clearly, below embodiment of the present invention is described further in detail.
Embodiment 1
Based on the energy supplying system that demand response control and comfort level feedback combine by weather forecast, see Fig. 1, this energy supplying system comprises:
Demand response control module 1, for monitoring the illumination of user and indoor temperature information, in conjunction with the demand response control strategy of operation of power networks information, indoor temperature, monochrome information output ustomer premises access equipment, and demand response control strategy is transferred to load prediction module 3;
Load prediction module 3, carries out load prediction for the historical load information by forecasting, meteorologic parameter and structure parameter, and is revised by energy demand forecast result by demand response control strategy;
System equipment effectiveness models module 6, for according to the service data of each equipment or producer's sample data, make system equipment effectiveness models, the optimization aim for energy management center 4 provides input data;
Energy management center 4, for by revised can demand forecast result and system equipment effectiveness models, according to each plant efficiency of distributing-supplying-energy system 2 variation relation with rate of load condensate and temperature, with economy, optimum or Environmental optimum is for objective function, formulate operation reserve and control, the information then provided by user side monitoring modular 5 is revised in real time to operation reserve again.
Wherein, system equipment effectiveness models is specially:
Between the different-energy form of equipment, transformation efficiency η or COP is with the variation relation of rate of load condensate x and temperature T.
Wherein, the load prediction of load prediction module 3 is specially:
Q＝f(Q
h,T
o,T,d,F)
Wherein, Q
hfor history energy demand information, T
ofor outdoor temperature, T is the comfort temperature of indoor requirement, and d is outside humidity, and F is intensity of solar radiation.
Below in conjunction with concrete computing formula and example, the scheme in embodiment 1 is described in detail, described below:
Embodiment 2
A kind of energy supplying system demand response control and comfort level feedback combined based on weather forecast, this energy supplying system comprises: demand response control module 1, distributing-supplying-energy system 2, load prediction module 3, energy management center 4, user side monitoring modular 5 and system equipment effectiveness models module 6, wherein
Demand response control module 1, for monitoring the illumination of user and indoor temperature information, in conjunction with the demand response control strategy of operation of power networks information, indoor temperature, monochrome information output ustomer premises access equipment, and demand response control strategy is transferred to load prediction module 3.
The demand response control strategy of above-mentioned ustomer premises access equipment is namely: the air-conditioning in the room of lower for Summer Indoor temperature (winter, indoor temperature was higher) is closed or opened in advance by force by the air-conditioning in the room of higher for Summer Indoor temperature (winter, indoor temperature was lower) before power surges load by electric load peak period by force; The light fixture in not high for lighting demand room cuts out by force;
Effectively can save energy resource consumption by above-mentioned control strategy, realize grid power load peak load shifting, ensure its safe operation.The brightness of concrete temperature and illumination sets according to the needs in practical application, such as: Summer Indoor temperature can be 26 degree.
Load prediction module 3, for the historical load information by forecast, meteorologic parameter (is obtained by weather bureau, meteorologic parameter comprises historical load, outdoor temperature, humidity, intensity of solar radiation, wind speed etc.) and structure parameter (by energy supply building obtain, structure parameter comprises building occupancy, materials for wall, thickness, door and window area, towards, doors structure, area, personal information etc.) carry out load prediction, the demand response control strategy of oneself is passed to load prediction module 3 by demand response control module 1, the result of load prediction is revised, finally draw the accurate user's Real-time Load demand with demand response combine with technique.
Wherein, load prediction module 3 is based on weather forecast, carries out the prediction of user by energy demand according to meteorologic parameter and architecture information to energy supply building or region; And the demand response control combined room lighting and air conditioning equipment, the result of load prediction is revised, predicts the workload demand of following mid-term, short-term.
This load prediction module 3 is a kind of based on weather forecast, has the Forecasting Methodology of feed-forward characteristic, and predict the outcome accurately, convenient energy administrative center 4 makes the scheduling strategy of distributing-supplying-energy system 2 in advance.Concrete forecast model form is as follows, wherein Q
hfor history energy demand information, T
ofor outdoor temperature, T is the comfort temperature of indoor requirement, and d is outside humidity, and F is intensity of solar radiation:
Q＝f(Q
h,T
o,T,d,F)
See in Fig. 2, system equipment effectiveness models module 6, according to the service data of each equipment or producer's sample data, makes system equipment effectiveness models.
Wherein, system equipment effectiveness models refers to the performance curve of each equipment of system, namely plant efficiency is with rate of load condensate (ratio of real power and rated power) and temperature (cooling water temperature, supply and return water temperature etc.) variation relation, by system equipment effectiveness models, energy management center 4 can should be run and could meet workload demand with what rate of load condensate and temperature according to making by energy demand each equipment of system, and can calculate the energy input of this equipment according to plant efficiency, the optimization aim for energy management center 4 provides input data.
Such as: system equipment effectiveness models is the performance curve of each equipment of system, between the different-energy form of i.e. equipment, transformation efficiency η (or COP) is with the variation relation of rate of load condensate x and temperature T, and the energy conversion that distributing-supplying-energy system 2 can be exported by this model is the energy of input.And then energy management center 4 can be made each equipment of system should be run with what rate of load condensate and temperature by the relation between this output and input, the energy that guarantee system exports and using of prediction can demand be mated, can ensure that again objective function is optimum, system equipment effectiveness models form is as follows:
η＝f(x,T)
cop＝f(x,T)
Wherein, cop is energy efficiency coefficient, represents the ratio of refrigeration or heating capacity and input electric power.
See Fig. 1, energy management center 4 is cores of intelligent energy supply system, for using energy demand and system equipment effectiveness models by what predict, and according to the variation relation of each plant efficiency of distributing-supplying-energy system 2 with rate of load condensate and temperature, optimum or Environmental the most excellent for objective function with economy, make operation reserve and control each equipment of system, the information then provided by user side monitoring modular 5 is revised in real time to operation reserve again, obtains correction strategy.
Wherein, optimum or Environmental the most excellent for objective function with economy, make system running policy and the known technology be operating as in this area that each equipment of system is controlled, such as: can see operating process disclosed in publication number CN104216368A, during specific implementation, the embodiment of the present invention does not repeat this.
See Fig. 1, when user is unsatisfied with oneself comfort level, the load update information (such as: the load update informations such as cool and thermal power) of oneself is fed back to energy management center 4 by user side monitoring modular 5 by user, energy management center 4 is revised the operation reserve of distributing-supplying-energy system 2 again, to meet the different comfort level demands of different user.
Such as, if when the load supply of user to system is unsatisfied with: be unsatisfied with the indoor temperature preset before or brightness, demands of individuals information can be fed back to energy management center 4 and demand response control module 1 by user side monitoring modular 5.Energy management center 4 and demand response control module 1 are revised respective operation reserve, to meet the different comfort level demands of different user.
Wherein, distributing-supplying-energy system 2 can provide cool and thermal power demand simultaneously, using various clean energy resource as input, and can rely on the combination of the different energy sources conversion equipment of electrical network or independent operating, as shown in Figure 2.
The energy management center 4 that the present invention proposes is cores of this intelligent energy supply system.Energy management center 4 is dispatching platforms of an intension optimized algorithm, using energy for building demand (such as: the workload demands such as cool and thermal power) and system equipment effectiveness models as input, using distributing-supplying-energy system 2 economy, optimum or Environmental optimum is as objective function, using the equilibrium of supply and demand of the energy as constraint, made the optimized operation strategy of each equipment of distributing-supplying-energy system 2 by certain optimized algorithm.
Objective function and constraint condition as follows:
Economy is optimum:
In formula, ρ
f,
with
be respectively rock gas purchasing price, sell electricity price lattice, F from electrical network power purchase price with to electrical network
ifor buying amount of natural gas, W
ifor from electrical network purchase of electricity, buy in as just, sell as negative.
Environmental optimum:
min{u
fF
iη
e+u
emax{W
i,0}+(u
e-u
f)min{W
i,0}}
In formula, u
fand u
efor the carbon emission coefficient of every kilowatt hour fuel gas generation and coal fired power generation (electricity of acquiescence electrical network is coal fired power generation), η
efor the generating efficiency of gas electricity generator, (u
e-u
f) min{W
i, when 0} represents that fuel gas generation oppositely sells telegram in reply net, every kilowatt of diminishbb carbon emission amount.
Constraint condition:
F (α)=0 (constraint of the load equilibrium of supply and demand)
G (α)≤0 (equipment peak power restriction)
Wherein, the energy that load equilibrium of supply and demand constraint representation system provides equals by energy demand; Equipment peak power restriction represents that each equipment operate power can not be greater than the rated power of equipment.
In sum, the intelligent energy supply system that the present invention proposes, can realize the intelligent energy supply to building and region.By having the demand forecast of accurate energy and the system equipment performance curve of feed-forward characteristic, the operation reserve of each equipment optimum of distributing-supplying-energy system can be made, revised operation reserve and demand response strategy by user side monitoring modular, the comfort level needs that can meet user different can realize energy-saving and emission-reduction again again.
The embodiment of the present invention is to the model of each device except doing specified otherwise, and the model of other devices does not limit, as long as can complete the device of above-mentioned functions.
It will be appreciated by those skilled in the art that accompanying drawing is the schematic diagram of a preferred embodiment, the invention described above embodiment sequence number, just to describing, does not represent the quality of embodiment.
The foregoing is only preferred embodiment of the present invention, not in order to limit the present invention, within the spirit and principles in the present invention all, any amendment done, equivalent replacement, improvement etc., all should be included within protection scope of the present invention.
List of references
[1]Wang J,Yang Y,Mao T,et al.Life cycle assessment(LCA)optimization of solar-assisted hybrid CCHP system[J].Applied Energy,2015,146:38-52.
[2]Wu Qiong,Ren Hongbo,Gao Wei,et al.Multi-criteria assessment of combined cooling,heating and power systems located in different regions in Japan[J].Applied Thermal Engineering,2014,73(1):658-668.
[3]Mancarella P,Chicco G.Real-time demand response from energy shifting in distributed multi-generation[J].IEEE Transactions on Smart Grid,2013,4(4):1928-1938.
Claims (3)
1., based on the energy supplying system that demand response control and comfort level feedback combine by weather forecast, it is characterized in that, described energy supplying system comprises:
Demand response control module, for monitoring the illumination of user and indoor temperature information, in conjunction with the demand response control strategy of operation of power networks information, indoor temperature, monochrome information output ustomer premises access equipment, and demand response control strategy is transferred to load prediction module;
Load prediction module, carries out load prediction for the historical load information by forecasting, meteorologic parameter and structure parameter, and is revised by energy demand forecast result by described demand response control strategy;
System equipment effectiveness models module, for according to the service data of each equipment or producer's sample data, make system equipment effectiveness models, the optimization aim for energy management center provides input data;
Energy management center, for by revised can demand forecast result and system equipment effectiveness models, according to each plant efficiency of distributing-supplying-energy system variation relation with rate of load condensate and temperature, with economy, optimum or Environmental optimum is for objective function, formulate operation reserve and control, the information then provided by user side monitoring modular is revised in real time to operation reserve again.
2. a kind of energy supplying system demand response control and comfort level feedback combined based on weather forecast according to claim 1, it is characterized in that, described system equipment effectiveness models is specially:
Between the different-energy form of equipment, transformation efficiency η or COP is with the variation relation of rate of load condensate x and temperature T.
3. a kind of energy supplying system demand response control and comfort level feedback combined based on weather forecast according to claim 1, it is characterized in that, the load prediction of described load prediction module is specially:
Q＝f(Q
h,T
o,T,d,F)
Wherein, Q
hfor history energy demand information, T
ofor outdoor temperature, T is the comfort temperature of indoor requirement, and d is outside humidity, and F is intensity of solar radiation.
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| CN111144628A (en) * | 2019-12-16 | 2020-05-12 | 茂盟（上海）工程技术股份有限公司 | Distributed energy supply type cooling, heating and power load prediction model system and method |
| CN111487939A (en) * | 2020-04-17 | 2020-08-04 | 内蒙古润泰新能源科技有限公司 | Intelligent system for heating, power supply and refrigeration integrated natural energy and control method |
| US10823446B2 (en) | 2018-10-12 | 2020-11-03 | Chicony Power Technology Co., Ltd. | System of adjusting load of air conditioning and method of adjusting the same |
| CN113218109A (en) * | 2021-04-15 | 2021-08-06 | 北京华远意通热力科技股份有限公司 | Intelligent regulation and control device and method for deep waste heat recovery |
| CN113776119A (en) * | 2021-09-24 | 2021-12-10 | 武汉蓝颖新能源有限公司 | Biomass boiler heating system based on indoor comfort degree self-adaptation |
| TWI757691B (en) * | 2019-02-26 | 2022-03-11 | 日商三菱重工業股份有限公司 | Operation index presentation device, operation index presentation method, and program |
| CN116014818A (en) * | 2023-03-29 | 2023-04-25 | 河北思悟新能源科技有限公司 | Comprehensive energy supply management system for climate change area |
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| CN113776119A (en) * | 2021-09-24 | 2021-12-10 | 武汉蓝颖新能源有限公司 | Biomass boiler heating system based on indoor comfort degree self-adaptation |
| CN116014818A (en) * | 2023-03-29 | 2023-04-25 | 河北思悟新能源科技有限公司 | Comprehensive energy supply management system for climate change area |
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