CN104730923A - Combined cooling-heating-power based comprehensive energy optimizing and controlling method for smart power grid region - Google Patents

Abstract

The invention discloses a combined cooling-heating-power based comprehensive energy optimizing and controlling method for a smart power grid region. By aiming at the characteristics of the cooling load, the electrical load, the heating load and various loads in the smart power grid region, by combining the fundamental principle of the combined cooling-heating-power and the working characteristics of various devices, the optimal utilization of multi-class energy is achieved; during implementation, the kilowatt is utilized as the measurement unit, the equivalent calculation of the various energy is combined, and the optimal management of the energy is prompted. The energy optimizing and controlling method has the advantages of being effective, practical and scientific, and beneficial to popularization and application of energy conservation.

Description

Based on the intelligent grid garden comprehensive energy optimal control method of cold, heat and electricity triple supply

Technical field

The present invention relates to technical field of power systems, particularly a kind of intelligent grid garden comprehensive energy optimal control method based on distributed cold and heat electricity trilogy supply.

Background technology

Along with country is to the great attention of energy-saving and emission-reduction, the requirement on flexibility that modern power systems is higher in addition, distributed cold and heat CCHP (distributed combined cool and heat and power, DCCHP) is paid much attention to.DCCHP is the cooling heating and power generation system based on distributed power source, and it can not only realize supply that is cold and hot and electric load, realizes cascaded utilization of energy, can also decreasing pollution gas discharging, has good Social benefit and economic benefit.Therefore, distributed cold and heat electricity trilogy supply is the effective means realizing energy-saving and emission-reduction, improve capacity usage ratio.

There is various dissimilar user in intelligent grid garden, due to user type with by the difference that can be accustomed to, present each other with can family curve also different.While energy ezpenditure, in garden, also there is the various multi-form distributed energies such as wind-force, luminous energy, waterpower, underground heat.The form of these energy often power supply in a distributed manner, is present in the middle of intelligent grid garden.More current technology only consider the cold, heat and electricity triple supply based on miniature gas turbine, consider not enough to some other joint supply facilities situation.How realizing the cascade utilization of the energy in intelligent grid garden, make full use of multi-form distributed energy, play the management and control advantage of intelligent grid garden to the energy and plurality of devices, is the outstanding problem of pendulum in face of intelligent grid park building person.

Summary of the invention

The technical matters solved: for the deficiencies in the prior art, the present invention proposes a kind of intelligent grid garden comprehensive energy optimal control method based on cold, heat and electricity triple supply, for solve existing intelligent grid garden in the process of cold, heat and electricity triple supply, only consider miniature gas turbine and to intelligent grid garden in other equipment that can be used as alliance of existing consider not enough technical matters.

Technical scheme: for solving the problems of the technologies described above, the present invention by the following technical solutions:

Based on an intelligent grid garden comprehensive energy optimal control method for cold, heat and electricity triple supply, multiclass powering device in intelligent grid garden and energy storage device are carried out cold, heat and electricity triple supply as distributed energy to the multiple user with different load;

First powering device and energy storage device and corresponding capacity is selected; Then optimization object function is determined; The constraint condition run in conjunction with selected powering device, energy storage device and intelligent grid garden three and the load curve of all types of user, utilize intelligent optimization genetic algorithm to solve optimization object function;

In implementation process, utilize solving result to dispatch powering device and energy storage device, realize the Optimum utilization of the intelligent grid garden energy.

Wherein, determine optimization object function, its step comprises:

Step (1), determine the electric energy switching cost function of intelligent grid garden and external electrical network:

${\mathrm{pri}}_{\mathrm{Grid}}=\underset{1}{\overset{24}{\mathrm{\Σ}}}{c}_{\mathrm{Grid}}^t\×P_{\mathrm{Grid}}^t$

In formula, be by time electricity price; be intelligent grid garden and external electrical network by time exchange of electric power value.

Step (2), determine the fuel cost function of miniature gas turbine and gas fired-boiler in intelligent grid garden:

${\mathrm{pri}}_{\mathrm{fuel}}=\underset{t=1}{\overset{24}{\mathrm{\Σ}}}\underset{i=1}{\overset{n_{\mathrm{CHP}}}{\mathrm{\Σ}}}{c}_{\mathrm{Gas}}^t\×f_{\mathrm{CHpi}}\left(P_i^t\right)+\underset{t=1}{\overset{24}{\mathrm{\Σ}}}\underset{i=1}{\overset{n_{\mathrm{boiler}}}{\mathrm{\Σ}}}{c}_{\mathrm{Gas}}^t\×H_{\mathrm{boileri}}^t/{\mathrm{\η}}_{\mathrm{boileri}};$

In formula, f _cHPifor miniature gas turbine is about power and the function using combustion gas, unit is kW; P _ibe the electric power output of i-th miniature gas turbine, unit is kW; n _cHPfor the quantity of miniature gas turbine; be by time gas price; be exerting oneself of i-th gas fired-boiler; η _boileriit is the energy conversion efficiency of i-th gas fired-boiler; T is time span, and unit is hour; n _boilerfor the quantity of gas fired-boiler.

Step (3), determine the maintenance cost function of intelligent grid garden energy resource system:

$\begin{array}{c}{\mathrm{pri}}_{\mathrm{maintain}}=\underset{t=1}{\overset{24}{\mathrm{\Σ}}}\underset{i=1}{\overset{n_{\mathrm{CHP}}}{\mathrm{\Σ}}}{p}_{\mathrm{mCHPi}}\×P_i^t+\underset{t=1}{\overset{24}{\mathrm{\Σ}}}\underset{i=1}{\overset{n_{\mathrm{distri}}}{\mathrm{\Σ}}}{p}_{\mathrm{mdistri}}\×P_{\mathrm{distri}}^t\\ +\underset{t=1}{\overset{24}{\mathrm{\Σ}}}{p}_{\mathrm{mstor}}\×H_{\mathrm{in}}^t+\underset{t=1}{\overset{24}{\mathrm{\Σ}}}{p}_{\mathrm{mstor}}\×H_{\mathrm{out}}^t+\underset{t=1}{\overset{24}{\mathrm{\Σ}}}{p}_{\mathrm{mEH}}\×P_{\mathrm{EH}}^t\end{array}$

In formula, p _mCHPifor the specific power operation expense of miniature gas turbine; p _mdistrifor the specific power operation expense of renewable energy power generation equipment; p _msstorfor the specific power operation expense of hot energy storage device; p _mEHfor the specific power operation expense of electric heating conversion equipment; be the electric power output of i-th renewable energy power generation equipment, unit is kW; with be respectively the charge and discharge thermal power of hot energy storage device, unit is kW; for the power of electric heating conversion equipment, unit is kW; n _distrifor the quantity of renewable energy power generation equipment.Due to gas fired-boiler in use general Maintenance free, therefore in maintenance cost function, do not relate to the continuous item of gas fired-boiler.

Step (4), superposed by three major types cost, be optimized objective function:

min price＝min(pri _Grid+pri _fuel+pri _maintain)

Be optimized after objective function, row write the constraint condition that selected powering device, energy storage device and intelligent grid garden three run, and its step comprises:

Step (1), determine electric power Constraints of Equilibrium function:

$P_{\mathrm{Grid}}^t+\underset{i=1}{\overset{n_{\mathrm{CHP}}}{\mathrm{\Σ}}}{P}_i^t+\underset{i=1}{\overset{n_{\mathrm{distri}}}{\mathrm{\Σ}}}{P}_{\mathrm{distri}}^t=P_{\mathrm{Load}}^t+P_{\mathrm{EH}}^t$

In formula, be intelligent grid garden and external electrical network by time exchange of electric power value, unit is kW; for load value, unit is kW.

Step (2), determine heating power balance constraint function;

$\underset{i=1}{\overset{n_{\mathrm{CHP}}}{\mathrm{\Σ}}}{H}_i^t+\underset{i=1}{\overset{n_{\mathrm{boiler}}}{\mathrm{\Σ}}}{H}_{\mathrm{boileri}}^t+{\mathrm{\η}}_{\mathrm{EH}}\×P_{\mathrm{EH}}^t+{\mathrm{\η}}_{\mathrm{out}}\×H_{\mathrm{out}}^t-H_{\mathrm{in}}^t\≥H_{\mathrm{Load}}^t$

In formula, it is the heat production value of i-th miniature gas turbine; it is the heat production value of i-th gas fired-boiler; η _eH, η _outbe respectively the exothermal efficiency of the efficiency of electric heating conversion equipment, hot energy storage; for the heat load by time of intelligent grid garden.

Step (3), determine cold power-balance constraint function;

$\underset{i=1}{\overset{n_{\mathrm{CHP}}}{\mathrm{\Σ}}}{C}_i^t+C_{\mathrm{cond}}^t\≥C_{\mathrm{Load}}^t$

In formula, the tail gas refrigeration work consumption of i-th miniature gas turbine by Absorption Refrigerator; for air conditioner refrigerating power; for the hourly cooling load of intelligent grid garden.

Step (4), determine the capacity constraint function of distributed energy in intelligent grid garden, these capacity constraint functions easily obtain according to concrete equipment;

For miniature gas turbine: $P_i^{\min }\≤P_i^t\≤P_i^{\max },i\∈n_{\mathrm{CHP}}$

For gas fired-boiler: $0\≤H_{\mathrm{boileri}}^t\≤H_{\mathrm{boileri}}^{\max },i\∈n_{\mathrm{boiler}}$

For electric heating conversion equipment:

For hot energy storage device: $0\≤H_{\mathrm{in}}^t\≤H_{\mathrm{in}}^{\max },0\≤H_{\mathrm{out}}^t\≤H_{\mathrm{out}}^{\max },S_{\mathrm{stor}}^{\min }\≤S_{\mathrm{stor}}^t\≤S_{\mathrm{stor}}^{\max };$

For renewable energy power generation equipment:

In formula, with be respectively hot energy storage device power input and the output power of t, with be respectively the hot energy storage device power input limit and the output power limit, for the lotus Warm status of hot energy storage device, hot energy storage device meets η _inthe thermal efficiency is filled, η for hot energy storage device _storrefer to the energy storage efficiency of hot energy storage device; The charge and discharge Warm status that this formula describes is a dynamic process.

Finally, utilize intelligent optimization genetic algorithm to solve optimization object function in conjunction with the load curve of all types of user, thus obtain operation plan a few days ago, carry out energy scheduling according to above-mentioned plan.

Beneficial effect:

The feature of polynary energy utilization in combined with intelligent electrical network garden of the present invention, consider the polynary energy energy situation of all types of user, distributed cold and heat electricity trilogy supply technology is utilized to be optimized control and management to the energy polynary in intelligent grid garden, all kinds of distributed energies in garden can be made full use of, realize the cascade utilization of the energy.

Concrete, the present invention has considered the feature of the multiclass powering device such as miniature gas turbine, gas fired-boiler, electric heating conversion equipment, hot energy storage device and renewable energy power generation equipment and energy storage device, and the feature of user's cool and thermal power different load in intelligent grid garden is investigated, the energy cascade utilization in intelligent grid garden is achieved by the ruuning situation of the distributed plurality of energy supplies equipment of algorithm optimization;

The present invention has also given full play to the advantage of intelligent grid garden in data acquisition and the advantage in powering device diversity, also give full play to the advantage of intelligent optimization genetic algorithm in solving-optimizing problem simultaneously, achieve the compartmentalization of energy source optimization, robotization and intellectuality, improve the comprehensive energy efficiency of intelligent grid garden, promote respond well.

Accompanying drawing explanation

Fig. 1 is process flow diagram of the present invention.

Fig. 2 is intelligent grid garden of the present invention cool and thermal power load curve.

Fig. 3 is the process flow diagram of genetic algorithm for solving intelligent grid garden provided by the invention comprehensive energy optimization problem.

When Fig. 4 is the adjustment of operation plan a few days ago according to genetic algorithm formulation provided by the invention, the operation electric power curves of plurality of energy supplies equipment.

When Fig. 5 is the adjustment of operation plan a few days ago according to genetic algorithm formulation provided by the invention, the operation thermal power curve of plurality of energy supplies equipment.

When Fig. 6 is the adjustment of operation plan a few days ago according to genetic algorithm formulation provided by the invention, the cold powertrace of operation of plurality of energy supplies equipment.

Embodiment

Below in conjunction with accompanying drawing, the present invention is further described.

The present invention proposes one and utilizes distributed cold and heat electricity trilogy supply technology to be optimized control and management method to the energy polynary in intelligent grid garden, concrete grammar of the present invention is as follows: first by the miniature gas turbine in intelligent grid garden, gas fired-boiler, electric heating conversion equipment, hot energy storage device and these powering device of renewable energy power generation equipment and energy storage device are as distributing-supplying-energy system, and determine the capacity of each equipment above-mentioned, by load polytype in intelligent grid garden (i.e. cool and thermal power three kinds of loads), the part throttle characteristics of polytype distributing-supplying-energy system is all embodied in load curve, as shown in Figure 2, wherein intelligent grid garden thermal load is hot water load's curve in figure and Space Thermal load curve sum, intelligent grid garden refrigeration duty is refrigeration duty curve and freeze load curve sum in figure, intelligent grid garden electric load is pure electric load curve in figure, and then determine optimization object function, row write the constraint condition run each equipment in distributing-supplying-energy system and intelligent grid garden, said process is specifically see summary of the invention part.

Then according to the genetic algorithm flow process shown in Fig. 3, optimization object function is solved, obtain the optimum results as Fig. 4, Fig. 5 and Fig. 6, eventually through by solving the optimum results obtained, various energy supply and energy storage device being dispatched, realizing the Optimum utilization of the garden energy.

The above is only the preferred embodiment of the present invention; be noted that for those skilled in the art; under the premise without departing from the principles of the invention, can also make some improvements and modifications, these improvements and modifications also should be considered as protection scope of the present invention.

Claims (9)

1. based on an intelligent grid garden comprehensive energy optimal control method for cold, heat and electricity triple supply, it is characterized in that: multiclass powering device in intelligent grid garden and energy storage device are carried out cold, heat and electricity triple supply as distributed energy to the multiple user with different load;

First powering device and energy storage device and corresponding capacity is selected; Then optimization object function is determined; The constraint condition run in conjunction with selected powering device, energy storage device and intelligent grid garden three and the load curve of all types of user, utilize genetic algorithm to solve optimization object function and obtain operation plan a few days ago;

In implementation process, the operation plan a few days ago solving acquisition is utilized to dispatch powering device and energy storage device.

2. the intelligent grid garden comprehensive energy optimal control method based on cold, heat and electricity triple supply according to claim 1, is characterized in that: described distributed energy comprises miniature gas turbine, gas fired-boiler, electric heating conversion equipment, hot energy storage device and renewable energy power generation equipment; Determine that optimization object function comprises the following steps: the electric energy switching cost function pri determining intelligent grid garden and external electrical network _grid; Determine the fuel cost function pri of miniature gas turbine and gas fired-boiler in intelligent grid garden _fuel; Determine the maintenance cost function pri of intelligent grid garden energy resource system _maintain; Then superposed by above-mentioned three class costs, be optimized objective function min price=min (pri _grid+ pri _fuel+ pri _maintain).

3. the intelligent grid garden comprehensive energy optimal control method based on cold, heat and electricity triple supply according to claim 1, is characterized in that: described constraint condition comprises satisfied following 4 class constraint functions: electric power Constraints of Equilibrium function; Heating power balance constraint function; Cold power-balance constraint function; In intelligent grid garden distributed energy capacity constraint function.

4. the intelligent grid garden comprehensive energy optimal control method based on cold, heat and electricity triple supply according to claim 2, is characterized in that: described intelligent grid garden and external electrical network electric energy switching cost function computing formula as follows:

${\mathrm{pri}}_{\mathrm{Grid}}=\underset{1}{\overset{24}{\mathrm{\Σ}}}{c}_{\mathrm{Grid}}^t\×P_{\mathrm{Grid}}^t---\left(1\right)$

(1) in formula, be by time electricity price; be intelligent grid garden and external electrical network by time exchange of electric power value.

5. the intelligent grid garden comprehensive energy optimal control method based on cold, heat and electricity triple supply according to claim 2, is characterized in that: the fuel cost function computing formula of described miniature gas turbine and gas fired-boiler is as follows:

${\mathrm{pri}}_{\mathrm{fuel}}=\underset{t=1}{\overset{24}{\mathrm{\Σ}}}\underset{i=1}{\overset{n_{\mathrm{CHP}}}{\mathrm{\Σ}}}{c}_{\mathrm{Gas}}^t\×f_{\mathrm{CHPi}}\left({P_i}^t\right)+\underset{t=1}{\overset{24}{\mathrm{\Σ}}}\underset{i=1}{\overset{n_{\mathrm{boiler}}}{\mathrm{\Σ}}}{c}_{\mathrm{Gas}}^t\×H_{\mathrm{boileri}}^t/{\mathrm{\η}}_{\mathrm{boileri}}---\left(2\right)$

(2) in formula, f _cHPifor miniature gas turbine is about power and the function using combustion gas, unit is kW; P _ibe the electric power output of i-th miniature gas turbine, unit is kW; n _cHPfor the quantity of miniature gas turbine; be by time gas price; be exerting oneself of i-th gas fired-boiler; η _boileriit is the energy conversion efficiency of i-th gas fired-boiler; T is time span, and unit is hour; n _boilerfor the quantity of gas fired-boiler.

6. the intelligent grid garden comprehensive energy optimal control method based on cold, heat and electricity triple supply according to claim 2, is characterized in that: the maintenance cost function computing method of described intelligent grid garden energy resource system are as follows:

$\begin{array}{c}{\mathrm{pri}}_{\mathrm{maintain}}=\underset{t=1}{\overset{24}{\mathrm{\Σ}}}\underset{i=1}{\overset{n_{\mathrm{CHP}}}{\mathrm{\Σ}}}{p}_{\mathrm{mCHPi}}\×{P_i}^t+\underset{t=1}{\overset{24}{\mathrm{\Σ}}}\underset{i=1}{\overset{n_{\mathrm{distri}}}{\mathrm{\Σ}}}{p}_{\mathrm{mdistri}}\×P_{\mathrm{distri}}^t\\ +\underset{t=1}{\overset{24}{\mathrm{\Σ}}}{p}_{\mathrm{mstor}}\×H_{\mathrm{in}}^t+\underset{t=1}{\overset{24}{\mathrm{\Σ}}}{p}_{\mathrm{mstor}}\×H_{\mathrm{out}}^t+\underset{t=1}{\overset{24}{\mathrm{\Σ}}}{p}_{\mathrm{mEH}}\×P_{\mathrm{EH}}^t\end{array}---\left(3\right)$

(3) in formula, p _mCHPifor the specific power operation expense of miniature gas turbine; p _mdistrifor the specific power operation expense of renewable energy power generation equipment; p _msstorfor the specific power operation expense of hot energy storage device; p _mEHfor the specific power operation expense of electric heating conversion equipment; P _ibe the electric power output of i-th miniature gas turbine, unit is kW; be the electric power output of i-th renewable energy power generation equipment, unit is kW; with be respectively the charge and discharge thermal power of hot energy storage device, unit is kW; for the power of electric heating conversion equipment, unit is kW; n _cHPfor the quantity of miniature gas turbine; n _distrifor the quantity of renewable energy power generation equipment.

7. the intelligent grid garden comprehensive energy optimal control method based on cold, heat and electricity triple supply according to claim 3, is characterized in that: described electric power Constraints of Equilibrium function computing formula is as follows:

$P_{\mathrm{Grid}}^t+\underset{i=1}{\overset{n_{\mathrm{CHP}}}{\mathrm{\Σ}}}{P_i}^t+\underset{i=1}{\overset{n_{\mathrm{distri}}}{\mathrm{\Σ}}}{P}_{\mathrm{distri}}^t=P_{\mathrm{Load}}^t+P_{\mathrm{EH}}^t---\left(4\right)$

(4) in formula, be intelligent grid garden and external electrical network by time exchange of electric power value, unit is kW; P _ibe the electric power output of i-th miniature gas turbine, unit is kW; be the electric power output of i-th renewable energy power generation equipment, unit is kW; for load value, unit is kW; for the power of electric heating conversion equipment, unit is kW; n _cHPfor the quantity of miniature gas turbine; n _distrifor the quantity of renewable energy power generation equipment.

8. the intelligent grid garden comprehensive energy optimal control method based on cold, heat and electricity triple supply according to claim 3, is characterized in that: described heating power balance constraint function computing formula is as follows:

$\underset{i=1}{\overset{n_{\mathrm{CHP}}}{\mathrm{\Σ}}}{H}_i^t+\underset{i=1}{\overset{n_{\mathrm{boiler}}}{\mathrm{\Σ}}}{H}_{\mathrm{boileri}}^t+{\mathrm{\η}}_{\mathrm{EH}}\×P_{\mathrm{EH}}^t+{\mathrm{\η}}_{\mathrm{out}}\×H_{\mathrm{out}}^t-H_{\mathrm{in}}^t\≥H_{\mathrm{Load}}^t---\left(5\right)$

(5) in formula, it is the heat production value of i-th miniature gas turbine; it is the heat production value of i-th gas fired-boiler; η _eH, η _outbe respectively the exothermal efficiency of the efficiency of electric heating conversion equipment, hot energy storage; for the heat load by time of intelligent grid garden; n _cHPfor the quantity of miniature gas turbine; n _boilerfor the quantity of gas fired-boiler.

9. the intelligent grid garden comprehensive energy optimal control method based on cold, heat and electricity triple supply according to claim 3, is characterized in that: described cold power-balance constraint function computing formula is as follows:

$\underset{i=1}{\overset{n_{\mathrm{CHP}}}{\mathrm{\Σ}}}{C}_i^t+C_{\mathrm{cond}}^t\≥C_{\mathrm{Load}}^t---\left(6\right)$

(6) in formula, the tail gas refrigeration work consumption of i-th miniature gas turbine by Absorption Refrigerator; n _cHPfor the quantity of miniature gas turbine; for air conditioner refrigerating power; for the hourly cooling load of intelligent grid garden.