CN106056246A - Energy storage capacity optimization method of cooling heating and power multi-potent flow microgrid considering operation - Google Patents

Abstract

The invention relates to an energy storage capacity optimization method considering the operation of a cooling, heating, electric and multi-energy flow micro-grid, and belongs to the technical field of optimal scheduling in the operation of a multi-energy flow coupling system. This method considers the optimization of energy storage capacity and the operation optimization of multi-energy flow microgrid as a whole. On the one hand, it fully considers the economic benefits brought by cooling and heating power storage to the scheduling of cooling and heating power flows in multi-energy flow microgrids and the effect of peak shaving and valley filling on large power grids. On the other hand, it also considers the configuration of cooling and heating power storage. By coordinating with the multi-energy flow micro-grid operation optimization, different energy storage capacities of cooling, heating and power are optimized to achieve the optimization of the overall economic benefits of the system. This method can provide a reference for the microgrid operator to economically and reasonably select the type and capacity of energy storage and the exchange capacity with the upper-level grid, so as to achieve the optimal benefit of multi-energy flow microgrid operation.

Description

An energy storage capacity optimization method considering operation of cooling, heating, power and multi-energy flow microgrids

technical field

The invention relates to an energy storage capacity optimization method considering the operation of a cooling, heating, electric and multi-energy flow micro-grid, and belongs to the technical field of optimal scheduling in the operation of a multi-energy flow coupling system.

Background technique

Due to the increasingly prominent environmental and energy issues, various forms of new energy and energy utilization with the core content of developing clean energy, ensuring energy security, and solving environmental problems have been vigorously developed. With the continuous deepening of the network concept, it is gradually integrated with the concept of energy, resulting in the concept of energy Internet with "power system as the core", "main primary energy as renewable energy" and "closely integrated with other systems". The Energy Internet requires more efficient and sustainable use of energy. One of its important features is to break the isolation barriers of traditional energy supply and realize the collaborative optimization of various energy forms, including Combined Cooling Heating and Power System , CCHP) and distributed renewable energy microgrids are a typical form of Energy Internet implementation.

The multi-energy flow microgrid combines the two concepts of microgrid and energy Internet, and has multiple characteristics. One is to have combined cooling, heating and power multi-energy flow and renewable energy; the other is to have a variety of multi-energy flow equipment to achieve comprehensive energy supply. Since the multi-energy flow microgrid integrates renewable energy, traditional electric energy flow, newly added cold and heat energy flow, and various forms of cold, heat and electric loads and equipment, compared with the traditional microgrid, various energy flows in it are mutually Coupling and influence can generally achieve better economic operation benefits, but its operation characteristics are more complex.

The various forms of energy storage devices that may be configured in the multi-energy flow microgrid increase the diversity and flexibility of system operation scheduling, and can bring higher economic benefits to the time scheduling of cold and hot electric energy flows. The economic benefits and working characteristics of various types of cooling and heating electric energy storage are also different. On the one hand, multiple types of energy storage devices can play the role of peak-shaving and valley-filling, and on the other hand, they can also reduce uncertainty to a certain extent. In addition, due to the mutual coupling of various energy flows, the selection of energy storage capacity is closely related to the optimal operation process. The optimization of energy storage capacity and the optimal operation of the system have a strong coupling characteristic, which also makes the energy exchange between the microgrid and the upper-level grid become more complicated. At present, there is no method to optimize the energy storage capacity of the multi-energy flow microgrid, and the configuration of energy storage is generally expensive, so it is necessary to study the optimization method of the energy storage capacity in the multi-energy flow microgrid.

Contents of the invention

The purpose of the present invention is to propose an energy storage capacity optimization method that considers the operation of the multi-energy flow micro-grid of cold, heat and electricity, consider the operation optimization of the multi-energy flow micro-grid and the energy exchange with the upper power grid, and study the energy storage in the multi-energy flow micro-grid The collaborative optimization method of capacity and operation is used to find a more suitable energy storage capacity.

The present invention proposes a method for optimizing the energy storage capacity of a micro-grid with cold, heat, electricity and multi-energy flows, which includes the following steps:

(1) Establish an optimization model for the operation of the cold-heat-electric multi-energy flow microgrid, the process is as follows:

(1-1) Establish an optimization model for the operation of cooling-heating-power cogeneration equipment in the cold-heating-electricity multi-energy flow microgrid:

The model of the power supply equipment in the cooling-heat-power cogeneration equipment model is as follows:

P _{l min} ≤ P _l (i) ≤ P _{l max}

-RD _l ≤P _l (i+1)-P _l (i)≤RU _l

Among them: i is the number of the running period, P _l is the active power of the cooling-heat-power cogeneration equipment, P _{l min} and P _{l max} are the upper limit and lower limit of the active power of the cooling-heat-power cogeneration equipment, RD _l is the upward ramp rate of the active power of the combined cooling-heat-electricity equipment, RU _l is the downward ramp rate of the active power of the combined cooling-heat-electricity equipment, RD _l and RU _l are determined by the combined cooling-heat-electricity The product manual of the equipment is provided;

The model of the heating/cooling equipment in the cooling-heating-power cogeneration equipment model is as follows:

H _{l min} ≤ H _l (i) ≤ H _{l max}

-RD _hl ≤H _l (i+1)-H _l (i)≤RU _hl

H _l (i)≥H _lh (i)/η _hex +L _lc (i)/η _COP

Among them: H _l is the thermal output of the cooling-heat-electricity cogeneration equipment, H _{l min} and H _{l max} are the upper and lower limits of the thermal output of the cooling-heat-electricity cogeneration equipment, RD _hl is the cooling-heat-electricity The upward ramp rate of the heat output of the cogeneration equipment, RU _hl is the downward ramp rate of the heat output of the cooling-heat-power cogeneration equipment, RD _hl and RU _hl are obtained from the product manual of the cooling-heat-power cogeneration equipment, H _lh is the heating power of the cold-heat-electricity combined supply equipment, L _lc is the cooling power of the cold-heat-electricity combined supply equipment, η _hex is the heat supply conversion efficiency factor of the cold-heat-electricity combined supply equipment, η _cop is the cooling conversion efficiency factor of the cooling-heat-power cogeneration equipment, and η _hex and η _cop are obtained from the product manual of the cooling-heat-power cogeneration equipment;

The coupling relationship between electricity, heat and cold in the cooling-heat-electricity cogeneration equipment model is:

a _f P _l (i)+b _f H _l (i)=F _l (i)

H _l (i) = c ₁ P _l (i) + c ₂

Among them: F _l is the air consumption of cooling-heating-electricity cogeneration equipment, a _f and b _f are the air consumption efficiency factors of cooling-heating-electricity cogeneration equipment respectively, c ₁ and c ₂ are cooling-heating-electricity cogeneration equipment The electric-heat output coupling factors of the power supply equipment, a _f , b _f , c ₁ and c ₂ are respectively obtained from the product manual of the cooling-heat-power cogeneration equipment;

(1-2) Establish the optimization model for the operation of the heating boiler in the cold-heat-electric multi-energy flow microgrid as follows:

0≤H(i) _≤Hmax

-RD _h ≤H(i+1)-H(i)≤RU _h

H(i)=ηF(i)

Where: H is the thermal power of the heating boiler, H _max is the upper limit of the thermal power of the heating boiler, RD _h is the upward ramp rate of the heating boiler, RU _h is the downward ramp rate of the heating boiler, F is the Gas consumption of the heating boiler, η is the thermal efficiency factor of the heating boiler, H _max , RD _h , RU _h and η are obtained from the product nameplate of the heating boiler;

(1-3) Establish the optimization model for the operation of energy conversion equipment in the cold-heat-electric multi-energy flow microgrid as follows:

0≤P _EH (i)≤P _{EH max}

H _EH (i) = η _EH P _EH (i)

0≤P _EC (i)≤P _{EC max}

L _EC (i) = η _EC P _EC (i)

Where: P _EH is the electrothermal conversion electric power of the energy conversion equipment, P _{EH max} is the upper limit of the electrothermal conversion electric power of the energy conversion equipment, H _EH is the electrothermal conversion heat output power of the energy conversion equipment, η _EH is the electrothermal conversion efficiency factor of the energy conversion equipment, P _EC is the electrical cooling conversion electric power of the energy conversion equipment, P _{EC max} is the electrical cooling conversion electric power upper limit of the energy conversion equipment, L _EC is the electrical cooling conversion cold output power of the energy conversion equipment, η _EC is the electrical cooling conversion of the energy conversion equipment The efficiency factors, P _{EH max} , η _EH , P _{EC max} and η _EC are obtained from the product specification of the energy conversion equipment;

(1-4) Establish the optimization model for the operation of multi-energy flow energy storage equipment in the cold-heat-electricity multi-energy flow microgrid as follows:

The optimization model for the operation of electric energy storage equipment is as follows:

0≤P _{dis, char} (i)≤P _{E max}

SoC(i)＝SoC(i-1)+η _c P _char (i)-P _dis (i)/η _d

SoC _min ≤ SoC(i) ≤ SoC _max

P _dis (i) · P _char (i) = 0

Among them: P _dis and P _char are the charging power and discharging power of the electric energy storage device respectively, P _{E max} is the maximum charging power and the maximum discharging power of the electric energy storage device, SoC is the electric energy storage current capacity of the electric energy storage device, SoC _min is the minimum electric energy storage capacity of the electric energy storage device, SoC _max is the maximum electric energy storage capacity of the electric energy storage device, η _c and η _d are the charging efficiency factor and discharge efficiency factor of the electric energy storage device, respectively, where, P _{E max} , SoC _min , SoC _max , η _c and η _d are obtained from the product specification of the electric energy storage device;

The optimization model for thermal energy storage equipment operation is as follows:

0≤H _TI,TO (i)≤H _TI,TO,max

HE _T (i)=η _H HE _T (i-1)+η _HI H _TI (i)-H _TO (i)/η _HO

HE _T,min ≤HE _T (i)≤HE _T,max

H _TO (i) · H _TI (i) = 0

Among them: H _TI and H _TO are the heat storage power and heat release power of the thermal energy storage device respectively, H _TI,TO,max are the maximum heat storage power and maximum heat release power of the thermal energy storage device, HE _T is the heat storage power The current thermal energy storage capacity of the equipment, HE _T,min is the minimum thermal energy storage capacity of the thermal energy storage device, HE _T,max is the maximum thermal energy storage capacity of the thermal energy storage device, η _HI and η _HO are the thermal energy storage The heat storage efficiency factor and heat release efficiency factor of the equipment, η _H is the thermal energy dissipation factor of the thermal energy storage equipment, where H _TI,TO,max , HE _T,min , HE _T,max , η _HI , η _HO and η _H Obtained from the product manual of the thermal energy storage device;

The optimization model for the operation of cold energy storage equipment is as follows:

0≤L _TI,TO (i)≤L _TI,TO,max

LE _T (i)=η _C LE _T (i-1)+η _CI L _TI (i)-L _TO (i)/η _CO

LE _T,min ≤LE _T (i)≤LE _T,max

L _TO (i) · L _TI (i) = 0

Among them: L _TI and L _TO are the cold storage power and cooling power of the cold energy storage equipment respectively, L _TI,TO,max are the maximum cold storage power and maximum cooling power of the cold energy storage equipment, LE _T is the cold energy storage The current cold storage capacity of the equipment, LE _T,min is the minimum cold storage capacity of the cold storage device, LE _T,max is the maximum cold storage capacity of the cold storage device, η _CI and η _CO are the cold storage capacity The cold storage efficiency factor and cooling efficiency factor of the equipment, η _C is the cooling energy dissipation factor of the cold energy storage equipment, where L _TI,TO,max , LE _T,min , LE _T,max , η _CI , η _CO and _ηC are obtained from the product specification of the cold energy storage device;

(1-5) Establish the energy exchange model between the cold-heat-electric multi-energy flow microgrid and the upper-level grid as follows:

0≤P _buy (i)≤P _{grid max}

0≤P _sell (i)≤P _{grid max}

P _buy (i) · P _sell (i) = 0

Among them: P _buy is the power purchased by the cold-heat-electricity multi-energy flow microgrid from the upper-level grid, P _sell is the power sold by the cold-heat-electricity multi-energy flow microgrid to the upper-level grid, and P _{grid max} is the cooling-heat- The maximum power of energy exchange between the electric multi-energy flow microgrid and the upper grid;

(1-6) Establish the energy balance model in the cold-heat-electric multi-energy flow microgrid as follows:

The power balance model is:

$\underset{\mathrm{<span\; class="notranslate">\; j</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{\mathrm{<span\; class="notranslate">\; m</span>}}{<span\; class="notranslate">\; \&Sigma;</span>}}{\mathrm{<span\; class="notranslate">\; P</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; P</span>}}_{\mathrm{<span\; class="notranslate">\; l</span>}}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; P</span>}}_{\mathrm{<span\; class="notranslate">\; b</span>}\mathrm{<span\; class="notranslate">\; u</span>}\mathrm{<span\; class="notranslate">\; the\; y</span>}}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; P</span>}}_{\mathrm{<span\; class="notranslate">\; d</span>}\mathrm{<span\; class="notranslate">\; i</span>}\mathrm{<span\; class="notranslate">\; the\; s</span>}}<span\; class="notranslate">\; =</span>{\mathrm{<span\; class="notranslate">\; E.</span>}}_{\mathrm{<span\; class="notranslate">\; l</span>}\mathrm{<span\; class="notranslate">\; o</span>}\mathrm{<span\; class="notranslate">\; a</span>}\mathrm{<span\; class="notranslate">\; d</span>}}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; P</span>}}_{\mathrm{<span\; class="notranslate">\; the\; s</span>}\mathrm{<span\; class="notranslate">\; e</span>}\mathrm{<span\; class="notranslate">\; l</span>}\mathrm{<span\; class="notranslate">\; l</span>}}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; P</span>}}_{\mathrm{<span\; class="notranslate">\; c</span>}\mathrm{<span\; class="notranslate">\; h</span>}\mathrm{<span\; class="notranslate">\; a</span>}\mathrm{<span\; class="notranslate">\; r</span>}}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; P</span>}}_{\mathrm{<span\; class="notranslate">\; E.</span>}\mathrm{<span\; class="notranslate">\; h</span>}}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; P</span>}}_{\mathrm{<span\; class="notranslate">\; E.</span>}\mathrm{<span\; class="notranslate">\; C</span>}}$

Among them: P _j is the active power of renewable energy in the cold-heat-electric multi-energy flow microgrid, m is the number of renewable energy units in the cold-heat-electric multi-energy flow microgrid, and E _load is the cold-heat-electricity multi-energy flow microgrid. The total electric energy load of the multi-energy flow microgrid, and the meanings of other symbols are the same as above;

The heat balance model is:

H _lh +H+H _EH +H _TO ≥H _load +H _TI

Among them: H _load is the total heat load of the cold-heat-electric multi-energy flow microgrid, and the meanings of other symbols are the same as above;

The cold energy balance model is:

L _lc +L _EC +L _TO ≥L _load +L _TI

Among them: L _load is the total cooling energy load of the cold-heat-electric multi-energy flow microgrid, and the meanings of other symbols are the same as above;

(1-7) Establish the optimization objective function for the operation of the cold-heat-electric multi-energy flow microgrid as follows:

Based on the operating economy and security of the microgrid operator, the optimization goal of the multi-energy flow microgrid can be described as minimizing the overall operating cost of the multi-energy flow microgrid, that is, maximizing the operating benefits. The optimization objective can be described as follows:

$\mathrm{<span\; class="notranslate">\; min</span>}\underset{\mathrm{<span\; class="notranslate">\; i</span>}}{<span\; class="notranslate">\; \&Sigma;</span>}\left(\begin{array}{c}{\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; P</span>}\mathrm{<span\; class="notranslate">\; b</span>}\mathrm{<span\; class="notranslate">\; u</span>}\mathrm{<span\; class="notranslate">\; the\; y</span>}}<span\; class="notranslate">\; \&Center\; Dot;</span>{\mathrm{<span\; class="notranslate">\; P</span>}}_{\mathrm{<span\; class="notranslate">\; b</span>}\mathrm{<span\; class="notranslate">\; u</span>}\mathrm{<span\; class="notranslate">\; the\; y</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; P</span>}\mathrm{<span\; class="notranslate">\; the\; s</span>}\mathrm{<span\; class="notranslate">\; e</span>}\mathrm{<span\; class="notranslate">\; l</span>}\mathrm{<span\; class="notranslate">\; l</span>}}<span\; class="notranslate">\; \&Center\; Dot;</span>{\mathrm{<span\; class="notranslate">\; P</span>}}_{\mathrm{<span\; class="notranslate">\; the\; s</span>}\mathrm{<span\; class="notranslate">\; e</span>}\mathrm{<span\; class="notranslate">\; l</span>}\mathrm{<span\; class="notranslate">\; l</span>}}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; g</span>}\mathrm{<span\; class="notranslate">\; a</span>}\mathrm{<span\; class="notranslate">\; the\; s</span>}}<span\; class="notranslate">\; \&Center\; Dot;</span>{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; l</span>}}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; g</span>}\mathrm{<span\; class="notranslate">\; a</span>}\mathrm{<span\; class="notranslate">\; the\; s</span>}}<span\; class="notranslate">\; \&Center\; Dot;</span>\mathrm{<span\; class="notranslate">\; f</span>}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; E.</span>}\mathrm{<span\; class="notranslate">\; c</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; P</span>}}_{\mathrm{<span\; class="notranslate">\; c</span>}\mathrm{<span\; class="notranslate">\; h</span>}\mathrm{<span\; class="notranslate">\; a</span>}\mathrm{<span\; class="notranslate">\; r</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; E.</span>}\mathrm{<span\; class="notranslate">\; d</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; P</span>}}_{\mathrm{<span\; class="notranslate">\; d</span>}\mathrm{<span\; class="notranslate">\; i</span>}\mathrm{<span\; class="notranslate">\; the\; s</span>}}<span\; class="notranslate">\; )</span>\\ <span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; h</span>}\mathrm{<span\; class="notranslate">\; c</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; T</span>}\mathrm{<span\; class="notranslate">\; I</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; h</span>}\mathrm{<span\; class="notranslate">\; d</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; T</span>}\mathrm{<span\; class="notranslate">\; o</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; L</span>}\mathrm{<span\; class="notranslate">\; c</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; L</span>}}_{\mathrm{<span\; class="notranslate">\; T</span>}\mathrm{<span\; class="notranslate">\; I</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; L</span>}\mathrm{<span\; class="notranslate">\; d</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; L</span>}}_{\mathrm{<span\; class="notranslate">\; T</span>}\mathrm{<span\; class="notranslate">\; o</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; a</span>}\mathrm{<span\; class="notranslate">\; l</span>}\mathrm{<span\; class="notranslate">\; l</span>}}<span\; class="notranslate">\; \&Center\; Dot;</span>{\mathrm{<span\; class="notranslate">\; P</span>}}_{\mathrm{<span\; class="notranslate">\; l</span>}}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; t</span>}\mathrm{<span\; class="notranslate">\; r</span>}\mathrm{<span\; class="notranslate">\; a</span>}\mathrm{<span\; class="notranslate">\; the\; s</span>}}{\mathrm{<span\; class="notranslate">\; P</span>}}_{\mathrm{<span\; class="notranslate">\; g</span>}\mathrm{<span\; class="notranslate">\; r</span>}\mathrm{<span\; class="notranslate">\; i</span>}\mathrm{<span\; class="notranslate">\; d</span>}\mathrm{<span\; class="notranslate">\; max</span>}}\end{array}\right)$

Among them: C _Pbuy is the electricity price purchased by the cold-heat-electricity multi-energy flow microgrid from the upper-level grid, C _Psell is the electricity price for the cold-heat-electricity multi-energy flow microgrid to sell electricity to the upper-level grid, and C _gas is the price of natural gas. C _Ec and C _Ed are the charging and discharging costs of electric energy storage equipment in the cold-heat-electric multi-energy flow microgrid, respectively, and _CHc and _CHd are the thermal energy storage in the cold-heat-electric multi-energy flow microgrid, respectively. The heat storage cost and heat release cost of the equipment, C _Lc and C _Ld are the cold storage cost and cooling cost of the cold energy storage equipment in the cold-heat-electricity multi-energy flow microgrid, respectively, C _all is the cold-heat-electricity multi- The operation subsidy for the cooling, heating and power cogeneration equipment in the energy flow microgrid, C _trans is the capacity fee for the energy exchange between the cooling-heating-electricity multi-energy flow microgrid and the upper-level grid;

(2) Establish an energy storage capacity optimization model considering the operation of cold-heat-electric multi-energy flow microgrid as follows:

min(S _eec EEC+S _hec HEC+S _lec LEC+min(C ₀ ^T x ₀ +S _trans P _trans ))

Among them: the internal minimization model min(C ₀ ^T x ₀ +S _trans P _trans ) is the optimization objective function of the cold-heat-electric multi-energy flow microgrid operation in the above step (1), where x ₀ represents -Other optimization variables other than the exchange capacity between the heat-electricity multi-energy flow micro-grid and the upper-level power grid, including: air consumption of combined cooling, heating and power, power generation of combined cooling, heating and power, heat production of combined cooling, heating and power, multi-energy flow micro The grid purchases electricity from the upper-level grid, sells electricity to the upper-level grid, the gas consumption of the heating boiler, the charging and discharging power of electric energy storage, the charging and discharging power of thermal energy storage, the charging and discharging power of cold energy storage, etc. EEC, HEC and LEC are cold- The capacity optimization variables of electric energy storage, thermal energy storage and cold energy storage of heat-electricity multi-energy flow microgrid, S _eec , S _hec , S _lec represent the electric energy storage, The cost per unit capacity of hot energy storage and cold energy storage (can be calculated in days);

(3) Solve the energy storage capacity optimization model in the above step (2), and decompose the energy storage capacity optimization model into two stages during the solution process:

In the first stage, EEC, HEC, and LEC are set as fixed values respectively, and the exchange capacity P _trans with the upper-level power grid is an optimization variable. The expression of the energy storage capacity optimization model in the first stage is:

$\underset{{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}<span\; class="notranslate">\; ,</span>{\mathrm{<span\; class="notranslate">\; P</span>}}_{\mathrm{<span\; class="notranslate">\; t</span>}\mathrm{<span\; class="notranslate">\; r</span>}\mathrm{<span\; class="notranslate">\; a</span>}\mathrm{<span\; class="notranslate">\; no</span>}\mathrm{<span\; class="notranslate">\; the\; s</span>}}}{\mathrm{<span\; class="notranslate">\; m</span>}\mathrm{<span\; class="notranslate">\; i</span>}\mathrm{<span\; class="notranslate">\; no</span>}}<span\; class="notranslate">\; (</span>{{\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}}^{\mathrm{<span\; class="notranslate">\; T</span>}}{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; t</span>}\mathrm{<span\; class="notranslate">\; r</span>}\mathrm{<span\; class="notranslate">\; a</span>}\mathrm{<span\; class="notranslate">\; no</span>}\mathrm{<span\; class="notranslate">\; the\; s</span>}}<span\; class="notranslate">\; \&Center\; Dot;</span>{\mathrm{<span\; class="notranslate">\; P</span>}}_{\mathrm{<span\; class="notranslate">\; r</span>}\mathrm{<span\; class="notranslate">\; a</span>}\mathrm{<span\; class="notranslate">\; no</span>}\mathrm{<span\; class="notranslate">\; the\; s</span>}}<span\; class="notranslate">\; )</span>$

When solving the second stage, the exchange capacity P _trans is the set value, and the energy storage capacity is the optimization variable. The two minimization models can be combined into one. The expression of the energy storage capacity optimization model in the second stage is:

$\underset{{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; E.</span>}\mathrm{<span\; class="notranslate">\; E.</span>}\mathrm{<span\; class="notranslate">\; C</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; h</span>}\mathrm{<span\; class="notranslate">\; E.</span>}\mathrm{<span\; class="notranslate">\; C</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; L</span>}\mathrm{<span\; class="notranslate">\; E.</span>}\mathrm{<span\; class="notranslate">\; C</span>}}{\mathrm{<span\; class="notranslate">\; m</span>}\mathrm{<span\; class="notranslate">\; i</span>}\mathrm{<span\; class="notranslate">\; no</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; e</span>}\mathrm{<span\; class="notranslate">\; e</span>}\mathrm{<span\; class="notranslate">\; c</span>}}<span\; class="notranslate">\; \&Center\; Dot;</span>\mathrm{<span\; class="notranslate">\; E.</span>}\mathrm{<span\; class="notranslate">\; E.</span>}\mathrm{<span\; class="notranslate">\; C</span>}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; h</span>}\mathrm{<span\; class="notranslate">\; e</span>}\mathrm{<span\; class="notranslate">\; c</span>}}<span\; class="notranslate">\; \&Center\; Dot;</span>\mathrm{<span\; class="notranslate">\; h</span>}\mathrm{<span\; class="notranslate">\; E.</span>}\mathrm{<span\; class="notranslate">\; C</span>}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; l</span>}\mathrm{<span\; class="notranslate">\; e</span>}\mathrm{<span\; class="notranslate">\; c</span>}}<span\; class="notranslate">\; \&Center\; Dot;</span>\mathrm{<span\; class="notranslate">\; L</span>}\mathrm{<span\; class="notranslate">\; E.</span>}\mathrm{<span\; class="notranslate">\; C</span>}<span\; class="notranslate">\; +</span>{{\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}}^{\mathrm{<span\; class="notranslate">\; T</span>}}{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; t</span>}\mathrm{<span\; class="notranslate">\; r</span>}\mathrm{<span\; class="notranslate">\; a</span>}\mathrm{<span\; class="notranslate">\; no</span>}\mathrm{<span\; class="notranslate">\; the\; s</span>}}<span\; class="notranslate">\; \&Center\; Dot;</span>{\mathrm{<span\; class="notranslate">\; P</span>}}_{\mathrm{<span\; class="notranslate">\; t</span>}\mathrm{<span\; class="notranslate">\; r</span>}\mathrm{<span\; class="notranslate">\; a</span>}\mathrm{<span\; class="notranslate">\; no</span>}\mathrm{<span\; class="notranslate">\; the\; s</span>}}<span\; class="notranslate">\; )</span>$

(4) Using an iterative method to solve the energy storage capacity optimization model decomposed into two stages in the above step (3), the process is as follows:

(4-1) Set the initial value of the cold, heat, and electricity energy storage capacity of the cold-heat-electricity multi-energy flow microgrid as S ₀ ;

(4-2) Substituting the above-mentioned energy storage capacity of cooling, heating and electricity into the energy storage capacity optimization model of the first stage above, since the addition of uncertainties and other factors may make the model non-linear, methods such as partitioning and delimitation can be used to solve the optimization operation of the microgrid Condition. Calculate the optimization results of the first stage, and obtain the exchange capacity between the cooling, heating, power and multi-energy flow micro-grid and the upper-level power grid from the optimization results of the first stage, and record the exchange capacity as P _max ;

(4-3) Substituting the cooling, heating and electric energy storage capacity of the above step (4-1) and the exchange capacity P _max of the step (4-2) into the cooling-heating-electricity multi-energy flow microgrid of the above step (1) The optimization model of the operation is calculated to obtain the optimization model of the operation of the cold-heat-electricity multi-energy flow microgrid and the overall benefit of the energy storage cost, and convert it to the day, and record the overall benefit of the operation and energy storage cost as Q _A ;

(4-4) Substitute the exchange capacity P _max of the above step (4-2) into the energy storage capacity optimization model of the second stage above, and also use partition demarcation and other methods to optimize the microgrid's annual operating efficiency and energy storage capacity , calculate the optimization result of the second stage, convert it to the day, record the overall benefit of operation and energy storage cost as Q _B , obtain the cold-heat-electric multi-energy flow energy storage capacity from the second-stage optimization result, and store The energy capacity is denoted as S;

(4-5) Compare the overall benefit Q _A of the operation and energy storage cost of the above step (4-3) with the overall benefit Q _B of the operation and energy storage cost of the above step (4-4), if |Q _A -Q _B |≤δ, the value range of δ is 10 ^-5 -10 ^-7 , then the iteration ends, and the energy storage capacity S and exchange capacity P _max of this iteration are operated as a cold-heat-electric multi-energy flow microgrid The optimal energy storage capacity and the exchange capacity of the cooling-heating-electricity multi-energy flow microgrid and the upper-level grid, the multi-energy flow microgrid operation and energy storage cost overall benefit Q _A or Q _B in this iteration is used as cooling-heating - The optimal benefit of the daily operation of the electric multi-energy flow microgrid; if |Q _A -Q _B |>δ, replace the original value with the energy storage capacity S obtained in this iteration, and return to step (4-2).

The energy storage capacity optimization method of the cooling, heating, power, multi-energy flow micro-grid considered in operation in the present invention has the characteristics and effects that the optimization of the energy storage capacity and the operation optimization of the multi-energy flow micro-grid are considered as a whole. On the one hand, it fully considers the economic benefits brought by cooling, heating and electric energy storage to the scheduling of cooling and heating electric energy flow in the multi-energy flow micro-grid and the effect of peak-shaving and valley-filling on the large power grid. By coordinating with the multi-energy flow micro-grid operation optimization, the different energy storage capacities of cooling, heating and power are optimized to achieve the optimization of the overall economic benefits of the system. This method can provide a reference for the microgrid operator to economically and reasonably select the type and capacity of energy storage and the exchange capacity with the upper-level grid, so as to achieve the optimal benefit of multi-energy flow microgrid operation.

detailed description

The method for optimizing the energy storage capacity of the cooling, heating, power and multi-energy flow microgrid proposed by the present invention includes the following steps:

(1) Establish an optimization model for the operation of the cold-heat-electric multi-energy flow microgrid, the process is as follows:

(1-1) Establish an optimization model for the operation of cooling-heating-power cogeneration equipment in the cold-heating-electricity multi-energy flow microgrid:

The model of the power supply equipment in the cooling-heat-power cogeneration equipment model is as follows:

P _{l min} ≤ P _l (i) ≤ P _{l max}

-RD _l ≤P _l (i+1)-P _l (i)≤RU _l

Among them: i is the number of the running period, P _l is the active power of the cooling-heat-power cogeneration equipment, P _{l min} and P _{l max} are the upper limit and lower limit of the active power of the cooling-heat-power cogeneration equipment, RD _l is the upward ramp rate of the active power of the combined cooling-heat-electricity equipment, RU _l is the downward ramp rate of the active power of the combined cooling-heat-electricity equipment, RD _l and RU _l are determined by the combined cooling-heat-electricity The product manual of the equipment is provided;

The model of the heating/cooling equipment in the cooling-heating-power cogeneration equipment model is as follows:

H _{l min} ≤ H _l (i) ≤ H _{l max}

-RD _hl ≤H _l (i+1)-H _l (i)≤RU _hl

H _l (i)≥H _lh (i)/η _hex +L _lc (i)/η _COP

Among them: H _l is the thermal output of the cooling-heat-electricity cogeneration equipment, H _{l min} and H _{l max} are the upper and lower limits of the thermal output of the cooling-heat-electricity cogeneration equipment, RD _hl is the cooling-heat-electricity The upward ramp rate of the heat output of the cogeneration equipment, RU _hl is the downward ramp rate of the heat output of the cooling-heat-power cogeneration equipment, RD _hl and RU _hl are obtained from the product manual of the cooling-heat-power cogeneration equipment, H _lh is the heating power of the cold-heat-electricity combined supply equipment, L _lc is the cooling power of the cold-heat-electricity combined supply equipment, η _hex is the heat supply conversion efficiency factor of the cold-heat-electricity combined supply equipment, η _cop is the cooling conversion efficiency factor of the cooling-heat-power cogeneration equipment, and η _hex and η _cop are obtained from the product manual of the cooling-heat-power cogeneration equipment;

The coupling relationship between electricity, heat and cold in the cooling-heat-electricity cogeneration equipment model is:

a _f P _l (i)+b _f H _l (i)=F _l (i)

H _l (i) = c ₁ P _l (i) + c ₂

Among them: F _l is the air consumption of cooling-heating-electricity cogeneration equipment, a _f and b _f are the air consumption efficiency factors of cooling-heating-electricity cogeneration equipment respectively, c ₁ and c ₂ are cooling-heating-electricity cogeneration equipment The electric-heat output coupling factors of the power supply equipment, a _f , b _f , c ₁ and c ₂ are respectively obtained from the product manual of the cooling-heat-power cogeneration equipment;

(1-2) Establish the optimization model for the operation of the heating boiler in the cold-heat-electric multi-energy flow microgrid as follows:

0≤H(i) _≤Hmax

-RD _h ≤H(i+1)-H(i)≤RU _h

H(i)=ηF(i)

Where: H is the thermal power of the heating boiler, H _max is the upper limit of the thermal power of the heating boiler, RD _h is the upward ramp rate of the heating boiler, RU _h is the downward ramp rate of the heating boiler, F is the Gas consumption of the heating boiler, η is the thermal efficiency factor of the heating boiler, H _max , RD _h , RU _h and η are obtained from the product nameplate of the heating boiler;

(1-3) Establish the optimization model for the operation of energy conversion equipment in the cold-heat-electric multi-energy flow microgrid as follows:

0≤P _EH (i)≤P _{EH max}

H _EH (i) = η _EH P _EH (i)

0≤P _EC (i)≤P _{EC max}

L _EC (i) = η _EC P _EC (i)

Where: P _EH is the electrothermal conversion electric power of the energy conversion equipment, P _{EH max} is the upper limit of the electrothermal conversion electric power of the energy conversion equipment, H _EH is the electrothermal conversion heat output power of the energy conversion equipment, η _EH is the electrothermal conversion efficiency factor of the energy conversion equipment, P _EC is the electrical cooling conversion electric power of the energy conversion equipment, P _{EC max} is the electrical cooling conversion electric power upper limit of the energy conversion equipment, L _EC is the electrical cooling conversion cold output power of the energy conversion equipment, η _EC is the electrical cooling conversion of the energy conversion equipment The efficiency factors, P _{EH max} , η _EH , P _{EC max} and η _EC are obtained from the product specification of the energy conversion equipment;

(1-4) Establish the optimization model for the operation of multi-energy flow energy storage equipment in the cold-heat-electricity multi-energy flow microgrid as follows:

The optimization model for the operation of electric energy storage equipment is as follows:

0≤P _{dis, char} (i)≤P _Emax

SoC(i)＝SoC(i-1)+η _c P _char (i)-P _dis (i)/η _d

SoC _min ≤ SoC(i) ≤ SoC _max

P _dis (i) · P _char (i) = 0

Among them: P _dis and P _char are the charging power and discharging power of the electric energy storage device respectively, P _{E max} is the maximum charging power and the maximum discharging power of the electric energy storage device, SoC is the electric energy storage current capacity of the electric energy storage device, SoC _min is the minimum electric energy storage capacity of the electric energy storage device, SoC _max is the maximum electric energy storage capacity of the electric energy storage device, η _c and η _d are the charging efficiency factor and discharge efficiency factor of the electric energy storage device, respectively, where, P _{E max} , SoC _min , SoC _max , η _c and η _d are obtained from the product specification of the electric energy storage device;

The optimization model for thermal energy storage equipment operation is as follows:

0≤H _TI,TO (i)≤H _TI,TO,max

HE _T (i)=η _H HE _T (i-1)+η _HI H _TI (i)-H _TO (i)/η _HO

HE _T,min ≤HE _T (i)≤HE _T,max

H _TO (i) · H _TI (i) = 0

Among them: H _TI and H _TO are the heat storage power and heat release power of the thermal energy storage device respectively, H _TI,TO,max are the maximum heat storage power and maximum heat release power of the thermal energy storage device, HE _T is the heat storage power The current thermal energy storage capacity of the equipment, HE _T,min is the minimum thermal energy storage capacity of the thermal energy storage device, HE _T,max is the maximum thermal energy storage capacity of the thermal energy storage device, η _HI and η _HO are the thermal energy storage The heat storage efficiency factor and heat release efficiency factor of the equipment, η _H is the thermal energy dissipation factor of the thermal energy storage equipment, where H _TI,TO,max , HE _T,min , HE _T,max , η _HI , η _HO and η _H Obtained from the product manual of the thermal energy storage device;

The optimization model for the operation of cold energy storage equipment is as follows:

0≤L _TI,TO (i)≤L _TI,TO,max

LE _T (i)=η _C LE _T (i-1)+η _CI L _TI (i)-L _TO (i)/η _CO

LE _T,min ≤LE _T (i)≤LE _T,max

L _TO (i) · L _TI (i) = 0

Among them: L _TI and L _TO are the cold storage power and cooling power of the cold energy storage equipment respectively, L _TI,TO,max are the maximum cold storage power and maximum cooling power of the cold energy storage equipment, LE _T is the cold energy storage The current cold storage capacity of the equipment, LE _T,min is the minimum cold storage capacity of the cold storage device, LE _T,max is the maximum cold storage capacity of the cold storage device, η _CI and η _CO are the cold storage capacity The cold storage efficiency factor and cooling efficiency factor of the equipment, η _C is the cooling energy dissipation factor of the cold energy storage equipment, where L _TI,TO,max , LE _T,min , LE _T,max , η _CI , η _CO and _ηC are obtained from the product specification of the cold energy storage device;

(1-5) Establish the energy exchange model between the cold-heat-electric multi-energy flow microgrid and the upper-level grid as follows:

0≤P _buy (i)≤P _{grid max}

0≤P _sell (i)≤P _{grid max}

P _buy (i) · P _sell (i) = 0

Among them: P _buy is the power purchased by the cold-heat-electricity multi-energy flow microgrid from the upper-level grid, P _sell is the power sold by the cold-heat-electricity multi-energy flow microgrid to the upper-level grid, and P _{grid max} is the cooling-heat- The maximum power of energy exchange between the electric multi-energy flow microgrid and the upper grid;

(1-6) Establish the energy balance model in the cold-heat-electric multi-energy flow microgrid as follows:

The power balance model is:

$\underset{\mathrm{<span\; class="notranslate">\; j</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{\mathrm{<span\; class="notranslate">\; m</span>}}{<span\; class="notranslate">\; \&Sigma;</span>}}{\mathrm{<span\; class="notranslate">\; P</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; P</span>}}_{\mathrm{<span\; class="notranslate">\; l</span>}}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; P</span>}}_{\mathrm{<span\; class="notranslate">\; b</span>}\mathrm{<span\; class="notranslate">\; u</span>}\mathrm{<span\; class="notranslate">\; the\; y</span>}}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; P</span>}}_{\mathrm{<span\; class="notranslate">\; d</span>}\mathrm{<span\; class="notranslate">\; i</span>}\mathrm{<span\; class="notranslate">\; the\; s</span>}}<span\; class="notranslate">\; =</span>{\mathrm{<span\; class="notranslate">\; E.</span>}}_{\mathrm{<span\; class="notranslate">\; l</span>}\mathrm{<span\; class="notranslate">\; o</span>}\mathrm{<span\; class="notranslate">\; a</span>}\mathrm{<span\; class="notranslate">\; d</span>}}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; P</span>}}_{\mathrm{<span\; class="notranslate">\; the\; s</span>}\mathrm{<span\; class="notranslate">\; e</span>}\mathrm{<span\; class="notranslate">\; l</span>}\mathrm{<span\; class="notranslate">\; l</span>}}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; P</span>}}_{\mathrm{<span\; class="notranslate">\; c</span>}\mathrm{<span\; class="notranslate">\; h</span>}\mathrm{<span\; class="notranslate">\; a</span>}\mathrm{<span\; class="notranslate">\; r</span>}}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; P</span>}}_{\mathrm{<span\; class="notranslate">\; E.</span>}\mathrm{<span\; class="notranslate">\; h</span>}}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; P</span>}}_{\mathrm{<span\; class="notranslate">\; E.</span>}\mathrm{<span\; class="notranslate">\; C</span>}}$

Among them: P _j is the active power of renewable energy in the cold-heat-electric multi-energy flow microgrid, m is the number of renewable energy units in the cold-heat-electric multi-energy flow microgrid, and E _load is the cold-heat-electricity multi-energy flow microgrid. The total electric energy load of the multi-energy flow microgrid, and the meanings of other symbols are the same as above;

The heat balance model is:

H _lh +H+H _EH +H _TO ≥H _load +H _TI

Among them: H _load is the total heat load of the cold-heat-electric multi-energy flow microgrid, and the meanings of other symbols are the same as above;

The cold energy balance model is:

L _lc +L _EC +L _TO ≥L _load +L _TI

Among them: L _load is the total cooling energy load of the cold-heat-electric multi-energy flow microgrid, and the meanings of other symbols are the same as above;

(1-7) Establish the optimization objective function for the operation of the cold-heat-electric multi-energy flow microgrid as follows:

Based on the operating economy and security of the microgrid operator, the optimization goal of the multi-energy flow microgrid can be described as minimizing the overall operating cost of the multi-energy flow microgrid, that is, maximizing the operating benefits. The optimization objective can be described as follows:

$\mathrm{<span\; class="notranslate">\; min</span>}\underset{\mathrm{<span\; class="notranslate">\; i</span>}}{<span\; class="notranslate">\; \&Sigma;</span>}\left(\begin{array}{c}{\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; P</span>}\mathrm{<span\; class="notranslate">\; b</span>}\mathrm{<span\; class="notranslate">\; u</span>}\mathrm{<span\; class="notranslate">\; the\; y</span>}}<span\; class="notranslate">\; \&Center\; Dot;</span>{\mathrm{<span\; class="notranslate">\; P</span>}}_{\mathrm{<span\; class="notranslate">\; b</span>}\mathrm{<span\; class="notranslate">\; u</span>}\mathrm{<span\; class="notranslate">\; the\; y</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; P</span>}\mathrm{<span\; class="notranslate">\; the\; s</span>}\mathrm{<span\; class="notranslate">\; e</span>}\mathrm{<span\; class="notranslate">\; l</span>}\mathrm{<span\; class="notranslate">\; l</span>}}<span\; class="notranslate">\; \&Center\; Dot;</span>{\mathrm{<span\; class="notranslate">\; P</span>}}_{\mathrm{<span\; class="notranslate">\; the\; s</span>}\mathrm{<span\; class="notranslate">\; e</span>}\mathrm{<span\; class="notranslate">\; l</span>}\mathrm{<span\; class="notranslate">\; l</span>}}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; g</span>}\mathrm{<span\; class="notranslate">\; a</span>}\mathrm{<span\; class="notranslate">\; the\; s</span>}}<span\; class="notranslate">\; \&Center\; Dot;</span>{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; l</span>}}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; g</span>}\mathrm{<span\; class="notranslate">\; a</span>}\mathrm{<span\; class="notranslate">\; the\; s</span>}}<span\; class="notranslate">\; \&Center\; Dot;</span>\mathrm{<span\; class="notranslate">\; f</span>}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; E.</span>}\mathrm{<span\; class="notranslate">\; c</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; P</span>}}_{\mathrm{<span\; class="notranslate">\; c</span>}\mathrm{<span\; class="notranslate">\; h</span>}\mathrm{<span\; class="notranslate">\; a</span>}\mathrm{<span\; class="notranslate">\; r</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; E.</span>}\mathrm{<span\; class="notranslate">\; d</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; P</span>}}_{\mathrm{<span\; class="notranslate">\; d</span>}\mathrm{<span\; class="notranslate">\; i</span>}\mathrm{<span\; class="notranslate">\; the\; s</span>}}<span\; class="notranslate">\; )</span>\\ <span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; h</span>}\mathrm{<span\; class="notranslate">\; c</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; T</span>}\mathrm{<span\; class="notranslate">\; I</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; h</span>}\mathrm{<span\; class="notranslate">\; d</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; T</span>}\mathrm{<span\; class="notranslate">\; o</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; L</span>}\mathrm{<span\; class="notranslate">\; c</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; L</span>}}_{\mathrm{<span\; class="notranslate">\; T</span>}\mathrm{<span\; class="notranslate">\; I</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; L</span>}\mathrm{<span\; class="notranslate">\; d</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; L</span>}}_{\mathrm{<span\; class="notranslate">\; T</span>}\mathrm{<span\; class="notranslate">\; o</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; a</span>}\mathrm{<span\; class="notranslate">\; l</span>}\mathrm{<span\; class="notranslate">\; l</span>}}<span\; class="notranslate">\; \&CenterDot;</span>{\mathrm{<span\; class="notranslate">\; P</span>}}_{\mathrm{<span\; class="notranslate">\; l</span>}}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; t</span>}\mathrm{<span\; class="notranslate">\; r</span>}\mathrm{<span\; class="notranslate">\; a</span>}\mathrm{<span\; class="notranslate">\; the\; s</span>}}{\mathrm{<span\; class="notranslate">\; P</span>}}_{\mathrm{<span\; class="notranslate">\; g</span>}\mathrm{<span\; class="notranslate">\; r</span>}\mathrm{<span\; class="notranslate">\; i</span>}\mathrm{<span\; class="notranslate">\; d</span>}\mathrm{<span\; class="notranslate">\; max</span>}}\end{array}\right)$

Among them: C _Pbuy is the electricity price purchased by the cold-heat-electricity multi-energy flow microgrid from the upper-level grid, C _Psell is the electricity price for the cold-heat-electricity multi-energy flow microgrid to sell electricity to the upper-level grid, and C _gas is the price of natural gas. C _Ec and C _Ed are the charging and discharging costs of electric energy storage equipment in the cold-heat-electric multi-energy flow microgrid, respectively, and _CHc and _CHd are the thermal energy storage in the cold-heat-electric multi-energy flow microgrid, respectively. The heat storage cost and heat release cost of the equipment, C _Lc and C _Ld are the cold storage cost and cooling cost of the cold energy storage equipment in the cold-heat-electricity multi-energy flow microgrid, respectively, C _all is the cold-heat-electricity multi- The operation subsidy for the cooling, heating and power cogeneration equipment in the energy flow microgrid, C _trans is the capacity fee for the energy exchange between the cooling-heating-electricity multi-energy flow microgrid and the upper-level grid;

(2) Establish an energy storage capacity optimization model considering the operation of cold-heat-electric multi-energy flow microgrid as follows:

min(S _eec EEC+S _hec HEC+S _lec LEC+min(C ₀ ^T x ₀ +S _trans P _trans ))

Among them: the internal minimization model min(C ₀ ^T x ₀ +S _trans P _trans ) is the optimization objective function of the cold-heat-electric multi-energy flow microgrid operation in the above step (1), where x ₀ represents -Other optimization variables other than the exchange capacity between the heat-electricity multi-energy flow micro-grid and the upper-level power grid, including: air consumption of combined cooling, heating and power, power generation of combined cooling, heating and power, heat production of combined cooling, heating and power, multi-energy flow micro The grid purchases electricity from the upper-level grid, sells electricity to the upper-level grid, the gas consumption of the heating boiler, the charging and discharging power of electric energy storage, the charging and discharging power of thermal energy storage, the charging and discharging power of cold energy storage, etc. EEC, HEC and LEC are cold- The capacity optimization variables of electric energy storage, thermal energy storage and cold energy storage of heat-electricity multi-energy flow microgrid, S _eec , S _hec , S _lec represent the electric energy storage, The cost per unit capacity of hot energy storage and cold energy storage (can be calculated in days);

(3) Solve the energy storage capacity optimization model in the above step (2), and decompose the energy storage capacity optimization model into two stages during the solution process:

In the first stage, EEC, HEC, and LEC are set as fixed values respectively, and the exchange capacity P _trans with the upper-level power grid is an optimization variable. The expression of the energy storage capacity optimization model in the first stage is:

$\underset{{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}<span\; class="notranslate">\; ,</span>{\mathrm{<span\; class="notranslate">\; P</span>}}_{\mathrm{<span\; class="notranslate">\; t</span>}\mathrm{<span\; class="notranslate">\; r</span>}\mathrm{<span\; class="notranslate">\; a</span>}\mathrm{<span\; class="notranslate">\; no</span>}\mathrm{<span\; class="notranslate">\; the\; s</span>}}}{\mathrm{<span\; class="notranslate">\; m</span>}\mathrm{<span\; class="notranslate">\; i</span>}\mathrm{<span\; class="notranslate">\; no</span>}}<span\; class="notranslate">\; (</span>{{\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}}^{\mathrm{<span\; class="notranslate">\; T</span>}}{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; t</span>}\mathrm{<span\; class="notranslate">\; r</span>}\mathrm{<span\; class="notranslate">\; a</span>}\mathrm{<span\; class="notranslate">\; no</span>}\mathrm{<span\; class="notranslate">\; the\; s</span>}}<span\; class="notranslate">\; \&CenterDot;</span>{\mathrm{<span\; class="notranslate">\; P</span>}}_{\mathrm{<span\; class="notranslate">\; r</span>}\mathrm{<span\; class="notranslate">\; a</span>}\mathrm{<span\; class="notranslate">\; no</span>}\mathrm{<span\; class="notranslate">\; the\; s</span>}}<span\; class="notranslate">\; )</span>$

When solving the second stage, the exchange capacity P _trans is the set value, and the energy storage capacity is the optimization variable. The two minimization models can be combined into one. The expression of the energy storage capacity optimization model in the second stage is:

$\underset{{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; E.</span>}\mathrm{<span\; class="notranslate">\; E.</span>}\mathrm{<span\; class="notranslate">\; C</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; h</span>}\mathrm{<span\; class="notranslate">\; E.</span>}\mathrm{<span\; class="notranslate">\; C</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; L</span>}\mathrm{<span\; class="notranslate">\; E.</span>}\mathrm{<span\; class="notranslate">\; C</span>}}{\mathrm{<span\; class="notranslate">\; m</span>}\mathrm{<span\; class="notranslate">\; i</span>}\mathrm{<span\; class="notranslate">\; no</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; e</span>}\mathrm{<span\; class="notranslate">\; e</span>}\mathrm{<span\; class="notranslate">\; c</span>}}<span\; class="notranslate">\; \&Center\; Dot;</span>\mathrm{<span\; class="notranslate">\; E.</span>}\mathrm{<span\; class="notranslate">\; E.</span>}\mathrm{<span\; class="notranslate">\; C</span>}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; h</span>}\mathrm{<span\; class="notranslate">\; e</span>}\mathrm{<span\; class="notranslate">\; c</span>}}<span\; class="notranslate">\; \&Center\; Dot;</span>\mathrm{<span\; class="notranslate">\; h</span>}\mathrm{<span\; class="notranslate">\; E.</span>}\mathrm{<span\; class="notranslate">\; C</span>}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; l</span>}\mathrm{<span\; class="notranslate">\; e</span>}\mathrm{<span\; class="notranslate">\; c</span>}}<span\; class="notranslate">\; \&Center\; Dot;</span>\mathrm{<span\; class="notranslate">\; L</span>}\mathrm{<span\; class="notranslate">\; E.</span>}\mathrm{<span\; class="notranslate">\; C</span>}<span\; class="notranslate">\; +</span>{{\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}}^{\mathrm{<span\; class="notranslate">\; T</span>}}{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; t</span>}\mathrm{<span\; class="notranslate">\; r</span>}\mathrm{<span\; class="notranslate">\; a</span>}\mathrm{<span\; class="notranslate">\; no</span>}\mathrm{<span\; class="notranslate">\; the\; s</span>}}<span\; class="notranslate">\; \&Center\; Dot;</span>{\mathrm{<span\; class="notranslate">\; P</span>}}_{\mathrm{<span\; class="notranslate">\; t</span>}\mathrm{<span\; class="notranslate">\; r</span>}\mathrm{<span\; class="notranslate">\; a</span>}\mathrm{<span\; class="notranslate">\; no</span>}\mathrm{<span\; class="notranslate">\; the\; s</span>}}<span\; class="notranslate">\; )</span>$

(4) Using an iterative method to solve the energy storage capacity optimization model decomposed into two stages in the above step (3), the process is as follows:

(4-1) Set the initial value of the cold, heat, and electricity energy storage capacity of the cold-heat-electricity multi-energy flow microgrid as S ₀ ;

(4-2) Substituting the above-mentioned energy storage capacity of cooling, heating and electricity into the energy storage capacity optimization model of the first stage above, since the addition of uncertainties and other factors may make the model non-linear, methods such as partitioning and delimitation can be used to solve the optimization operation of the microgrid Condition. Calculate the optimization results of the first stage, and obtain the exchange capacity between the cooling, heating, power and multi-energy flow micro-grid and the upper-level power grid from the optimization results of the first stage, and record the exchange capacity as P _max ;

(4-3) Substituting the cooling, heating and electric energy storage capacity of the above step (4-1) and the exchange capacity P _max of the step (4-2) into the cooling-heating-electricity multi-energy flow microgrid of the above step (1) The optimization model of the operation is calculated to obtain the optimization model of the operation of the cold-heat-electricity multi-energy flow microgrid and the overall benefit of the energy storage cost, and convert it to the day, and record the overall benefit of the operation and energy storage cost as Q _A ;

(4-4) Substitute the exchange capacity P _max of the above step (4-2) into the energy storage capacity optimization model of the second stage above, and also use partition demarcation and other methods to optimize the microgrid's annual operating efficiency and energy storage capacity , calculate the optimization result of the second stage, convert it to the day, record the overall benefit of operation and energy storage cost as Q _B , obtain the cold-heat-electric multi-energy flow energy storage capacity from the second-stage optimization result, and store The energy capacity is denoted as S;

(4-5) Compare the overall benefit Q _A of the operation and energy storage cost of the above step (4-3) with the overall benefit Q _B of the operation and energy storage cost of the above step (4-4), if |Q _A -Q _B |≤δ, the value range of δ is 10 ^-5 -10 ^-7 , then the iteration ends, and the energy storage capacity S and exchange capacity P _max of this iteration are operated as a cold-heat-electric multi-energy flow microgrid The optimal energy storage capacity and the exchange capacity of the cooling-heating-electricity multi-energy flow microgrid and the upper-level grid, the multi-energy flow microgrid operation and energy storage cost overall benefit Q _A or Q _B in this iteration is used as cooling-heating - The optimal benefit of the daily operation of the electric multi-energy flow microgrid; if |Q _A -Q _B |>δ, replace the original value with the energy storage capacity S obtained in this iteration, and return to step (4-2).

Claims (1)

1. A method for optimizing the energy storage capacity of a cold, hot, electric and multi-energy flow micro-grid considering operation, characterized in that the method comprises the following steps: (1) Establish an optimization model for the operation of the cold-heat-electric multi-energy flow microgrid, the process is as follows: (1-1) Establish an optimization model for the operation of cooling-heating-power cogeneration equipment in the cold-heating-electricity multi-energy flow microgrid: The model of the power supply equipment in the cooling-heat-power cogeneration equipment model is as follows: P _lmin ≤ P _l (i) ≤ P _lmax -RD _l ≤P _l (i+1)-P _l (i)≤RU _l Among them: i is the number of the running period, P _l is the active power of the cooling-heat-power cogeneration equipment, P _lmin and P _lmax are the upper limit and lower limit of the active power of the cooling-heat-power cogeneration equipment, RD _l is the cooling -The upward ramp rate of the active power of the heat-power cogeneration equipment, RU _l is the downward ramp rate of the active power of the cooling-heat-power cogeneration equipment, RD _l and RU _l are determined by the cooling-heat-power cogeneration equipment Provide product brochures; The model of the heating/cooling equipment in the cooling-heating-power cogeneration equipment model is as follows: H _lmin ≤ H _l (i) ≤ H _lmax -RD _hl ≤H _l (i+1)-H _l (i)≤RU _hl H _l (i)≥H _lh (i)/η _hex +L _lc (i)/η _COP Among them: H _l is the thermal output of cooling-heat-electricity cogeneration equipment, H _lmin and H _lmax are the upper limit and lower limit of the thermal output of cooling-heat-electricity cogeneration equipment, RD _hl is cooling-heat-electricity cogeneration The upward climbing rate of the heat output of the equipment, RU _hl is the downward climbing rate of the heat output of the cooling-heat-power cogeneration equipment, RD _hl and RU _hl are obtained from the product manual of the cooling-heat-power cogeneration equipment, H _lh is the heating power of the cooling-heat-power cogeneration equipment, L _lc is the cooling power of the cooling-heat-power cogeneration equipment, η _hex is the heat supply conversion efficiency factor of the cooling-heat-power cogeneration equipment, η _cop is the cooling conversion efficiency factor of the cooling-heating-power cogeneration equipment, η _hex and η _cop are obtained from the product specification of the cooling-heat-power cogeneration equipment; The coupling relationship between electricity, heat and cold in the cooling-heat-electricity cogeneration equipment model is: a _f P _l (i)+b _f H _l (i)=F _l (i) H _l (i) = c ₁ P _l (i) + c ₂ Among them: F _l is the air consumption of cooling-heating-electricity cogeneration equipment, a _f and b _f are the air consumption efficiency factors of cooling-heating-electricity cogeneration equipment respectively, c ₁ and c ₂ are cooling-heating-electricity cogeneration equipment The electric-heat output coupling factors of the power supply equipment, a _f , b _f , c ₁ and c ₂ are respectively obtained from the product manual of the cooling-heat-power cogeneration equipment; (1-2) Establish the optimization model for the operation of the heating boiler in the cold-heat-electric multi-energy flow microgrid as follows: 0≤H(i) _≤Hmax -RD _h ≤H(i+1)-H(i)≤RU _h H(i)=ηF(i) Where: H is the thermal power of the heating boiler, H _max is the upper limit of the thermal power of the heating boiler, RD _h is the upward ramp rate of the heating boiler, RU _h is the downward ramp rate of the heating boiler, F is the Gas consumption of the heating boiler, η is the thermal efficiency factor of the heating boiler, H _max , RD _h , RU _h and η are obtained from the product nameplate of the heating boiler; (1-3) Establish the optimization model for the operation of energy conversion equipment in the cold-heat-electric multi-energy flow microgrid as follows: 0≤P _EH (i) _{≤P EHmax} H _EH (i) = η _EH P _EH (i) 0≤P _EC (i) _{≤P ECmax} L _EC (i) = η _EC P _EC (i) Among them: P _EH is the electrothermal conversion electric power of the energy conversion equipment, P _EHmax is the upper limit of the electrothermal conversion electric power of the energy conversion equipment, H _EH is the electrothermal conversion heat output power of the energy conversion equipment, η _EH is the electrothermal conversion efficiency factor of the energy conversion equipment, P _EC is the electrical cooling conversion electric power of the energy conversion equipment, P _ECmax is the upper limit of the electrical cooling conversion electrical power of the energy conversion equipment, L _EC is the electrical cooling conversion cooling output power of the energy conversion equipment, and η _EC is the electrical cooling conversion efficiency factor of the energy conversion equipment , P _EHmax , η _EH , P _ECmax and η _EC are obtained from the product manual of the energy conversion device; (1-4) Establish the optimization model for the operation of multi-energy flow energy storage equipment in the cold-heat-electricity multi-energy flow microgrid as follows: The optimization model for the operation of electric energy storage equipment is as follows: 0≤P _{dis, char} (i)≤P _Emax SoC(i)＝SoC(i-1)+η _c P _char (i)-P _dis (i)/η _d SoC _min ≤ SoC(i) ≤ SoC _max P _dis (i) · P _char (i) = 0 Among them: P _dis and P _char are the charging power and discharging power of the electric energy storage device respectively, P _Emax is the maximum charging power and the maximum discharging power of the electric energy storage device, SoC is the current electric energy storage capacity of the electric energy storage device, SoC _min is the minimum electric energy storage capacity of the electric energy storage device, SoC _max is the maximum electric energy storage capacity of the electric energy storage device, η _c and η _d are the charging efficiency factor and discharge efficiency factor of the electric energy storage device, respectively, where, P _Emax , SoC _min , SoC _max , η _c and η _d are obtained from the product specification of the electric energy storage device; The optimization model for thermal energy storage equipment operation is as follows: 0≤H _TI,TO (i)≤H _TI,TO,max HE _T (i)=η _H HE _T (i-1)+η _HI H _TI (i)-H _TO (i)/η _HO HE _T,min ≤HE _T (i)≤HE _T,max H _TO (i) · H _TI (i) = 0 Among them: H _TI and H _TO are the heat storage power and heat release power of the thermal energy storage device respectively, H _TI,TO,max are the maximum heat storage power and maximum heat release power of the thermal energy storage device, HE _T is the heat storage power The current thermal energy storage capacity of the equipment, HE _T,min is the minimum thermal energy storage capacity of the thermal energy storage device, HE _T,max is the maximum thermal energy storage capacity of the thermal energy storage device, η _HI and η _HO are the thermal energy storage The heat storage efficiency factor and heat release efficiency factor of the equipment, η _H is the thermal energy dissipation factor of the thermal energy storage equipment, where, H _TI,TO,max , HE _T,min , HE _T,max , η _HI , η _HO and η _H Obtained from the product manual of the thermal energy storage device; The optimization model for the operation of cold energy storage equipment is as follows: 0≤L _TI,TO (i)≤L _TI,TO,max LE _T (i)=η _C LE _T (i-1)+η _CI L _TI (i)-L _TO (i)/η _CO LE _T,min ≤LE _T (i)≤LE _T,max L _TO (i) · L _TI (i) = 0 Among them: L _TI and L _TO are the cold storage power and cooling power of the cold energy storage equipment respectively, L _TI,TO,max are the maximum cold storage power and maximum cooling power of the cold energy storage equipment, LE _T is the cold energy storage The current cold storage capacity of the equipment, LE _T,min is the minimum cold storage capacity of the cold storage device, LE _T,max is the maximum cold storage capacity of the cold storage device, η _CI and η _CO are the cold storage capacity The cold storage efficiency factor and cooling efficiency factor of the equipment, η _C is the cooling energy dissipation factor of the cold energy storage equipment, where L _TI,TO,max , LE _T,min , LE _T,max , η _CI , η _CO and _ηC are obtained from the product specification of the cold energy storage device; (1-5) Establish the energy exchange model between the cold-heat-electric multi-energy flow microgrid and the upper-level grid as follows: 0≤P _buy (i) _{≤P gridmax} 0≤P _sell (i) _{≤P gridmax} P _buy (i) · P _sell (i) = 0 Among them: P _buy is the power purchased by the cold-heat-electricity multi-energy flow microgrid from the upper-level grid, P _sell is the power sold by the cold-heat-electricity multi-energy flow microgrid to the upper-level grid, and P _gridmax is the cold-heat-electricity The maximum power of energy exchange between the multi-energy flow microgrid and the upper grid; (1-6) Establish the energy balance model in the cold-heat-electric multi-energy flow microgrid as follows: The power balance model is: $\underset{\mathrm{<span\; class="notranslate">\; j</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{\mathrm{<span\; class="notranslate">\; m</span>}}{<span\; class="notranslate">\; \&Sigma;</span>}}{\mathrm{<span\; class="notranslate">\; P</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; P</span>}}_{\mathrm{<span\; class="notranslate">\; l</span>}}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; P</span>}}_{\mathrm{<span\; class="notranslate">\; b</span>}\mathrm{<span\; class="notranslate">\; u</span>}\mathrm{<span\; class="notranslate">\; the\; y</span>}}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; P</span>}}_{\mathrm{<span\; class="notranslate">\; d</span>}\mathrm{<span\; class="notranslate">\; i</span>}\mathrm{<span\; class="notranslate">\; the\; s</span>}}<span\; class="notranslate">\; =</span>{\mathrm{<span\; class="notranslate">\; E.</span>}}_{\mathrm{<span\; class="notranslate">\; l</span>}\mathrm{<span\; class="notranslate">\; o</span>}\mathrm{<span\; class="notranslate">\; a</span>}\mathrm{<span\; class="notranslate">\; d</span>}}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; P</span>}}_{\mathrm{<span\; class="notranslate">\; the\; s</span>}\mathrm{<span\; class="notranslate">\; e</span>}\mathrm{<span\; class="notranslate">\; l</span>}\mathrm{<span\; class="notranslate">\; l</span>}}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; P</span>}}_{\mathrm{<span\; class="notranslate">\; c</span>}\mathrm{<span\; class="notranslate">\; h</span>}\mathrm{<span\; class="notranslate">\; a</span>}\mathrm{<span\; class="notranslate">\; r</span>}}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; P</span>}}_{\mathrm{<span\; class="notranslate">\; E.</span>}\mathrm{<span\; class="notranslate">\; h</span>}}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; P</span>}}_{\mathrm{<span\; class="notranslate">\; E.</span>}\mathrm{<span\; class="notranslate">\; C</span>}}$ Among them: P _j is the active power of renewable energy in the cold-heat-electric multi-energy flow microgrid, m is the number of renewable energy units in the cold-heat-electric multi-energy flow microgrid, and E _load is the cold-heat-electricity multi-energy flow microgrid. The total electric energy load of the multi-energy flow microgrid, and the meanings of other symbols are the same as above; The heat balance model is: H _lh +H+H _EH +H _TO ≥H _load +H _TI Among them: H _load is the total heat load of the cold-heat-electric multi-energy flow microgrid, and the meanings of other symbols are the same as above; The cold energy balance model is: L _lc +L _EC +L _TO ≥L _load +L _TI Among them: L _load is the total cooling energy load of the cold-heat-electric multi-energy flow microgrid, and the meanings of other symbols are the same as above; (1-7) Establish the optimization objective function for the operation of the cold-heat-electric multi-energy flow microgrid as follows: $\mathrm{<span\; class="notranslate">\; min</span>}\underset{\mathrm{<span\; class="notranslate">\; i</span>}}{<span\; class="notranslate">\; \&Sigma;</span>}\left(\begin{array}{c}{\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; P</span>}\mathrm{<span\; class="notranslate">\; b</span>}\mathrm{<span\; class="notranslate">\; u</span>}\mathrm{<span\; class="notranslate">\; the\; y</span>}}<span\; class="notranslate">\; \&Center\; Dot;</span>{\mathrm{<span\; class="notranslate">\; P</span>}}_{\mathrm{<span\; class="notranslate">\; b</span>}\mathrm{<span\; class="notranslate">\; u</span>}\mathrm{<span\; class="notranslate">\; the\; y</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; P</span>}\mathrm{<span\; class="notranslate">\; the\; s</span>}\mathrm{<span\; class="notranslate">\; e</span>}\mathrm{<span\; class="notranslate">\; l</span>}\mathrm{<span\; class="notranslate">\; l</span>}}<span\; class="notranslate">\; \&Center\; Dot;</span>{\mathrm{<span\; class="notranslate">\; P</span>}}_{\mathrm{<span\; class="notranslate">\; the\; s</span>}\mathrm{<span\; class="notranslate">\; e</span>}\mathrm{<span\; class="notranslate">\; l</span>}\mathrm{<span\; class="notranslate">\; l</span>}}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; g</span>}\mathrm{<span\; class="notranslate">\; a</span>}\mathrm{<span\; class="notranslate">\; the\; s</span>}}<span\; class="notranslate">\; \&Center\; Dot;</span>{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; l</span>}}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; g</span>}\mathrm{<span\; class="notranslate">\; a</span>}\mathrm{<span\; class="notranslate">\; the\; s</span>}}<span\; class="notranslate">\; \&Center\; Dot;</span>\mathrm{<span\; class="notranslate">\; f</span>}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; E.</span>}\mathrm{<span\; class="notranslate">\; c</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; P</span>}}_{\mathrm{<span\; class="notranslate">\; c</span>}\mathrm{<span\; class="notranslate">\; h</span>}\mathrm{<span\; class="notranslate">\; a</span>}\mathrm{<span\; class="notranslate">\; r</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; E.</span>}\mathrm{<span\; class="notranslate">\; d</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; P</span>}}_{\mathrm{<span\; class="notranslate">\; d</span>}\mathrm{<span\; class="notranslate">\; i</span>}\mathrm{<span\; class="notranslate">\; the\; s</span>}}<span\; class="notranslate">\; )</span>\\ <span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; h</span>}\mathrm{<span\; class="notranslate">\; c</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; T</span>}\mathrm{<span\; class="notranslate">\; I</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; h</span>}\mathrm{<span\; class="notranslate">\; d</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; T</span>}\mathrm{<span\; class="notranslate">\; o</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; L</span>}\mathrm{<span\; class="notranslate">\; c</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; L</span>}}_{\mathrm{<span\; class="notranslate">\; T</span>}\mathrm{<span\; class="notranslate">\; I</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; L</span>}\mathrm{<span\; class="notranslate">\; d</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; L</span>}}_{\mathrm{<span\; class="notranslate">\; T</span>}\mathrm{<span\; class="notranslate">\; o</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; a</span>}\mathrm{<span\; class="notranslate">\; l</span>}\mathrm{<span\; class="notranslate">\; l</span>}}<span\; class="notranslate">\; \&Center\; Dot;</span>{\mathrm{<span\; class="notranslate">\; P</span>}}_{\mathrm{<span\; class="notranslate">\; l</span>}}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; t</span>}\mathrm{<span\; class="notranslate">\; r</span>}\mathrm{<span\; class="notranslate">\; a</span>}\mathrm{<span\; class="notranslate">\; the\; s</span>}}{\mathrm{<span\; class="notranslate">\; P</span>}}_{\mathrm{<span\; class="notranslate">\; g</span>}\mathrm{<span\; class="notranslate">\; r</span>}\mathrm{<span\; class="notranslate">\; i</span>}\mathrm{<span\; class="notranslate">\; d</span>}\mathrm{<span\; class="notranslate">\; max</span>}}\end{array}\right)$ Among them: C _Pbuy is the electricity price purchased by the cold-heat-electricity multi-energy flow microgrid from the upper-level grid, C _Psell is the electricity price for the cold-heat-electricity multi-energy flow microgrid to sell electricity to the upper-level grid, and C _gas is the price of natural gas. C _Ec and C _Ed are the charging and discharging costs of electric energy storage equipment in the cold-heat-electric multi-energy flow microgrid, respectively, and _CHc and _CHd are the thermal energy storage in the cold-heat-electric multi-energy flow microgrid, respectively. The heat storage cost and heat release cost of the equipment, C _Lc and C _Ld are the cold storage cost and cooling cost of the cold energy storage equipment in the cold-heat-electricity multi-energy flow microgrid, respectively, C _all is the cold-heat-electricity multi- The operation subsidy for the cooling, heating and power cogeneration equipment in the energy flow microgrid, C _trans is the capacity fee for the energy exchange between the cooling-heating-electricity multi-energy flow microgrid and the upper-level grid; (2) Establish an energy storage capacity optimization model considering the operation of cold-heat-electric multi-energy flow microgrid as follows: min(S _eec EEC+S _hec HEC+S _lec LEC+min(C ₀ ^T x ₀ +S _trans P _trans )) Among them: the internal minimization model min(C ₀ ^T x ₀ +S _trans P _trans ) is the optimization objective function of the cold-heat-electric multi-energy flow microgrid operation in the above step (1), where x ₀ represents -Other optimization variables other than the exchange capacity between the heat-electricity multi-energy flow micro-grid and the upper-level power grid, including: air consumption of combined cooling, heating and power, power generation of combined cooling, heating and power, heat production of combined cooling, heating and power, multi-energy flow micro-grid The grid purchases electricity from the upper-level grid, sells electricity to the upper-level grid, the gas consumption of the heating boiler, the charging and discharging power of electric energy storage, the charging and discharging power of thermal energy storage, the charging and discharging power of cold energy storage, etc. EEC, HEC and LEC are cold- The capacity optimization variables of electric energy storage, thermal energy storage and cold energy storage of heat-electricity multi-energy flow microgrid, S _eec , S _hec , S _lec represent the electric energy storage, The cost per unit capacity of thermal energy storage and cold energy storage; (3) Solve the energy storage capacity optimization model in the above step (2), and decompose the energy storage capacity optimization model into two stages during the solution process: In the first stage, EEC, HEC, and LEC are set as fixed values respectively, and the exchange capacity P _trans with the upper-level power grid is an optimization variable. The expression of the energy storage capacity optimization model in the first stage is: $\underset{{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}<span\; class="notranslate">\; ,</span>{\mathrm{<span\; class="notranslate">\; P</span>}}_{\mathrm{<span\; class="notranslate">\; t</span>}\mathrm{<span\; class="notranslate">\; r</span>}\mathrm{<span\; class="notranslate">\; a</span>}\mathrm{<span\; class="notranslate">\; no</span>}\mathrm{<span\; class="notranslate">\; the\; s</span>}}}{\mathrm{<span\; class="notranslate">\; m</span>}\mathrm{<span\; class="notranslate">\; i</span>}\mathrm{<span\; class="notranslate">\; no</span>}}<span\; class="notranslate">\; (</span>{{\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}}^{\mathrm{<span\; class="notranslate">\; T</span>}}{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; t</span>}\mathrm{<span\; class="notranslate">\; r</span>}\mathrm{<span\; class="notranslate">\; a</span>}\mathrm{<span\; class="notranslate">\; no</span>}\mathrm{<span\; class="notranslate">\; the\; s</span>}}<span\; class="notranslate">\; \&Center\; Dot;</span>{\mathrm{<span\; class="notranslate">\; P</span>}}_{\mathrm{<span\; class="notranslate">\; t</span>}\mathrm{<span\; class="notranslate">\; r</span>}\mathrm{<span\; class="notranslate">\; a</span>}\mathrm{<span\; class="notranslate">\; no</span>}\mathrm{<span\; class="notranslate">\; the\; s</span>}}<span\; class="notranslate">\; )</span>$ When solving the second stage, the exchange capacity P _trans is the set value, and the energy storage capacity is the optimization variable. The expression of the energy storage capacity optimization model in the second stage is: $\underset{{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; E.</span>}\mathrm{<span\; class="notranslate">\; E.</span>}\mathrm{<span\; class="notranslate">\; C</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; h</span>}\mathrm{<span\; class="notranslate">\; E.</span>}\mathrm{<span\; class="notranslate">\; C</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; L</span>}\mathrm{<span\; class="notranslate">\; E.</span>}\mathrm{<span\; class="notranslate">\; C</span>}}{\mathrm{<span\; class="notranslate">\; m</span>}\mathrm{<span\; class="notranslate">\; i</span>}\mathrm{<span\; class="notranslate">\; no</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; e</span>}\mathrm{<span\; class="notranslate">\; e</span>}\mathrm{<span\; class="notranslate">\; c</span>}}<span\; class="notranslate">\; \&Center\; Dot;</span>\mathrm{<span\; class="notranslate">\; E.</span>}\mathrm{<span\; class="notranslate">\; E.</span>}\mathrm{<span\; class="notranslate">\; C</span>}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; h</span>}\mathrm{<span\; class="notranslate">\; e</span>}\mathrm{<span\; class="notranslate">\; c</span>}}<span\; class="notranslate">\; \&Center\; Dot;</span>\mathrm{<span\; class="notranslate">\; h</span>}\mathrm{<span\; class="notranslate">\; E.</span>}\mathrm{<span\; class="notranslate">\; C</span>}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; l</span>}\mathrm{<span\; class="notranslate">\; e</span>}\mathrm{<span\; class="notranslate">\; c</span>}}<span\; class="notranslate">\; \&Center\; Dot;</span>\mathrm{<span\; class="notranslate">\; L</span>}\mathrm{<span\; class="notranslate">\; E.</span>}\mathrm{<span\; class="notranslate">\; C</span>}<span\; class="notranslate">\; +</span>{{\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}}^{\mathrm{<span\; class="notranslate">\; T</span>}}{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; t</span>}\mathrm{<span\; class="notranslate">\; r</span>}\mathrm{<span\; class="notranslate">\; a</span>}\mathrm{<span\; class="notranslate">\; no</span>}\mathrm{<span\; class="notranslate">\; the\; s</span>}}<span\; class="notranslate">\; \&Center\; Dot;</span>{\mathrm{<span\; class="notranslate">\; P</span>}}_{\mathrm{<span\; class="notranslate">\; t</span>}\mathrm{<span\; class="notranslate">\; r</span>}\mathrm{<span\; class="notranslate">\; a</span>}\mathrm{<span\; class="notranslate">\; no</span>}\mathrm{<span\; class="notranslate">\; the\; s</span>}}<span\; class="notranslate">\; )</span>$ (4) Using an iterative method to solve the energy storage capacity optimization model decomposed into two stages in the above step (3), the process is as follows: (4-1) Set the initial value of the cold, heat, and electricity energy storage capacity of the cold-heat-electricity multi-energy flow microgrid as S ₀ ; (4-2) Substituting the above-mentioned energy storage capacity of cooling, heating, and electricity into the optimization model of the energy storage capacity of the first stage above, the calculation results of the first-stage optimization are obtained, and from the optimization results of the first stage, the micro-grid and the upper-level The switching capacity of the grid, which is recorded as P _max ; (4-3) Substituting the cooling, heating and electric energy storage capacity of the above step (4-1) and the exchange capacity P _max of the step (4-2) into the cooling-heating-electricity multi-energy flow microgrid of the above step (1) The optimization model of operation is calculated to obtain the optimization model of cold-heat-electric multi-energy flow microgrid operation and the overall benefit of energy storage cost, and the overall benefit of operation and energy storage cost is recorded as Q _A ; (4-4) Substitute the exchange capacity P _max of the above step (4-2) into the above-mentioned second-stage energy storage capacity optimization model, calculate and obtain the second-stage optimization results, convert to days, and record the overall benefits of operation and energy storage costs is Q _B , the energy storage capacity of cold-heat-electric multi-energy flow is obtained from the optimization results of the second stage, and the energy storage capacity is denoted as S; (4-5) Compare the overall benefit Q _A of the operation and energy storage cost of the above step (4-3) with the overall benefit Q _B of the operation and energy storage cost of the above step (4-4), if |Q _A -Q _B |≤δ, the value range of δ is 10 ^-5 -10 ^-7 , then the iteration ends, and the energy storage capacity S and exchange capacity P _max of this iteration are operated as a cold-heat-electric multi-energy flow microgrid The optimal energy storage capacity and the exchange capacity of the cooling-heating-electricity multi-energy flow microgrid and the upper-level grid, the multi-energy flow microgrid operation and energy storage cost overall benefit Q _A or Q _B in this iteration is used as cooling-heating - The optimal benefit of the daily operation of the electric multi-energy flow microgrid; if |Q _A -Q _B |>δ, replace the original value with the energy storage capacity S obtained in this iteration, and return to step (4-2).