WO2019078419A1 - Power supply and demand operation scheduling apparatus and method, and computer program - Google Patents

Abstract

The present invention relates to a power supply and demand operation scheduling apparatus and method, and a computer program, and the scheduling apparatus for operating the power supply and demand of a microgrid (MG) comprises: a demand resource (DR); and power generation resources comprising a new renewable energy source, an energy storage system (ESS) and a distributed generator (DG), which respectively supply power to the DR, wherein operation scheduling result information, which includes successful bid information of each of the power generation resources in order to operate the power supply and demand of the MG, is calculated by applying, to operation scheduling input information including bidding information of each of the power generation resources, an operation scheduling algorithm for satisfying power supply and demand restriction of the MG and minimizing power generation costs of the power generation resources.

Description

Apparatus and method for power supply and demand operation scheduling, computer program

The present invention relates to an apparatus, a method and a computer program for a power supply and demand operation scheduling system, and more particularly, to a power supply and demand scheduling apparatus and method for operating a power supply and demand system through a power trading mechanism based on an economic point of view in a new power market including a grid- An operating scheduling apparatus and method, and a computer program.

Micro Grid (MG) is a kind of Smart Grid system, which means small electric power system that can self-supply electric energy in small area, Small power grid with a renewable energy source and energy storage, and a small power grid that allows it to operate independently or in conjunction with an external large power grid.

These microgrids are divided into grid-connected type and stand-alone type depending on whether they are grid-connected or not. Generally, stand-alone microgrid is limited to physically isolated areas such as island, mountain, and remote areas. The micro grid is attracting much attention as a decentralized system that is out of the existing centralized distribution system because it can receive more power from other networks or operate more flexible system through independent power generation.

Currently, it is expected that the growth of the market will continue due to the involvement of private companies in the field of micro grids. In order to support the creation of a private power-driven new power market, plans to open a small-scale power brokerage market by a small- The implementation of public policies for the spreading of new and renewable energy is accelerating.

However, there is no system for operating electricity supply and demand through a true bi-directional power supply that can directly generate and consume electricity in a micro grid environment based on the current economic viewpoint and sell the surplus power. In other words, it is easy to apply to the microgrid sector, and a system for new market structure and market operation based on economics is required so that the private sector can continue to grow.

The background art of the present invention is disclosed in Korean Patent Laid-Open Publication No. 10-2015-0136171 (published on Dec. 20, 2015).

The present invention relates to a power supply and demand operation scheduling apparatus and method for generating an optimal schedule for operating power supply and demand through a power trading mechanism based on an economic point of view in a new power market including a grid-connected micro grid and an external power market, A computer program is provided.

According to an aspect of the present invention, there is provided an apparatus for scheduling power supply and demand operations, comprising: a demand resource (DR); And a power generation resource including a renewable energy source for supplying power to the demanded resource, an energy storage system (ESS), and a distributed power generator (DG) The scheduling apparatus according to claim 1, further comprising: an operation scheduling algorithm for meeting the power supply and demand constraint of the micro grid and minimizing the generation cost of the power generation resources, in an operating scheduling input information including bidding information of each power generation resource, And calculates operational scheduling result information for operating the power supply and demand of the microgrid including the winning information of each power generation resource.

In the present invention, the operation scheduling algorithm includes an objective function for minimizing a power purchase cost required to operate the power supply and demand of the microgrid based on the operation scheduling input information, The scheduling result information is used to calculate the operational scheduling result information.

In the present invention, the operational scheduling input information includes information on renewable energy source bidding information including the bidding capacity and the bid price of the renewable energy source, and the energy storage device including the bidding charge quantity and the bid price of the energy storage device. And distributed power supply bidding information including bidding information, bidding capacity of the distributed power, and power generation cost function information.

In the present invention, the energy storage device bidding information further includes charge / discharge efficiency, maximum storage capacity, maximum allowable SoC (State Of Charge) and minimum allowable SoC information of the energy storage device, The maximum evaporation amount of the power source, the maximum amount of depression, the startup time information, and the stop time information.

In the present invention, the operational scheduling result information may include at least one of renewable energy source winning information including the internal usage amount of the renewable energy source and the external sales amount of electricity, the charge amount of the energy storage device, And the distributed power supply winning information including the energy storage device winning information including the total amount of the distributed power supply and the amount of the internal power used by the distributed power supply and the amount of the external sales power.

In the present invention, the energy storage device winning information may further include SoC information of the energy storage device, and the distributed power supply winning information may further include startup state information and activation / deactivation information of the distributed power supply .

In the present invention, the operation scheduling input information may further include power transaction information with an adjacent micro grid, power trading information between an external power purchase market and an external power sale market, and demand prediction information in the micro grid .

In the present invention, the operational scheduling result information may include at least one of adjacent microgrid power trading information including a purchased power amount from the adjacent microgrid and a sales power amount to the adjacent microgrid, a purchase power amount from the external power purchase market, And external power market power transaction information including a sales power amount to an external power market.

In the present invention, the operation scheduling algorithm may be configured to calculate, based on the operation scheduling input information, a cost of purchasing power from the renewable energy source, a cost of charging and discharging the energy storage device, The cost of power purchase required to operate the power supply and demand of the micro grid is minimized in consideration of the cost of power trading with the micro grid and the cost of each power trading between the external power purchase market and the external power sale market And the operation scheduling result information is calculated by using the objective function.

In the present invention, the operation scheduling algorithm may include: a renewable energy source constraint condition including an output constraint of the renewable energy source; an energy storage device constraint condition including an output constraint of the energy storage device; And an external power market constraint including a power trading constraint with the external power sales market, the power supply constraint being set to calculate the operational scheduling result information in a range that satisfies the power supply constraint condition .

In the present invention, the energy storage device constraint condition is set based on the charge / discharge efficiency of the energy storage device, the maximum storage capacity, the minimum allowable SoC, and the maximum allowable SoC so that the energy storage device is operated in the allowable SoC range Wherein the distributed power constraint includes at least one of an output variation constraint set based on a maximum evaporation amount and a maximum fall amount of the distributed power source and an output variation constraint set based on the startup time information and the stop time information of the distributed power source And the start and stop hold time constraints set on the basis of the start and stop hold time constraints.

In the present invention, the external power market constraint condition may be a power constraint for limiting the surplus power among the power generated by the power generation resources included in the micro grid to the adjacent micro grid and the external power sales market And is a transaction constraint.

In the present invention, the operation scheduling result information may further include a MGGCP (MicroGrid Market Clearing Price), which is a market liquidation price in the micro grid, and the internal usage amount of the renewable energy source, And the internal power consumption of the distributed power source is settled through the MG MCP.

In the present invention, the amount of external sales electricity of the renewable energy source and the amount of sales electricity to the external electricity sales market are settled through SMP (System Marginal Price), which is a systematic marginal price, The MG MCP is calculated based on the retail price of the external power purchase market, and the MG MCP is calculated at a price equal to or higher than the SMP and equal to or less than the retail price.

According to an aspect of the present invention, there is provided a method of scheduling a power supply / demand operation, including: a DR (Demand Resource); And a power generation resource including a renewable energy source for supplying power to the demanded resource, an energy storage system (ESS), and a distributed power generator (DG) Wherein the scheduling apparatus for power supply and demand operation receives input of operational scheduling input information including bidding information of each of the generated resources, and the power supply and demand operation scheduling apparatus further comprises: An operation scheduling algorithm is applied to the scheduling input information to meet the power supply and demand constraint of the micro grid and to minimize the power generation cost of the power generation resources, thereby operating the power supply and demand of the micro grid including the winning information of each power generation resource And calculating operating scheduling result information .

A computer program in accordance with an aspect of the present invention is coupled to hardware to provide a system comprising: a Demand Resource (DR); And a power generation resource including a renewable energy source for supplying power to the demanded resource, an energy storage system (ESS), and a distributed power generator (DG) The method of claim 1, further comprising the steps of: receiving operating scheduling input information including bidding information of each of the power generation resources; and satisfying the power supply and demand constraint of the micro grid to the input operating scheduling input information And calculating operational scheduling result information for operating the power supply and demand of the microgrid including the winning information of each generating resource by applying an operating scheduling algorithm for minimizing the generation cost of the generating resources, .

According to the apparatus, method and computer program for power supply and demand operation scheduling according to the present invention, it is possible to flexibly respond to a power peak situation and perform more stable system operation, reduce transmission / distribution operation cost and loss cost, And the like can be expected.

FIG. 1 is an exemplary diagram illustrating a configuration of a micro grid in a power supply / demand operation scheduling apparatus according to an embodiment of the present invention. Referring to FIG.

FIG. 2 is a diagram illustrating a process of calculating an MG MCP in an apparatus for scheduling power supply / reception operations according to an exemplary embodiment of the present invention. Referring to FIG.

3 is an exemplary diagram illustrating a configuration of a new power market in the power supply / demand operation scheduling apparatus according to an embodiment of the present invention.

4 is an exemplary diagram illustrating an appropriate range of the MG MCP in the power supply / demand operation scheduling apparatus according to an embodiment of the present invention.

5 is a diagram illustrating an operation scheduling input information, an operation scheduling algorithm, and an operation scheduling result information in a power supply / demand operation scheduling apparatus according to an embodiment of the present invention.

6 is an exemplary diagram for explaining a process of calculating a renewable energy source in the power supply / demand operation scheduling apparatus according to an embodiment of the present invention.

FIG. 7 is an exemplary diagram illustrating a configuration of an energy storage device in a power supply / demand operation scheduling apparatus according to an embodiment of the present invention. Referring to FIG.

8 to 17 are diagrams illustrating an example of application of the power supply / demand operation scheduling apparatus according to an embodiment of the present invention.

18 is a flowchart illustrating a power supply / demand operation scheduling method according to an embodiment of the present invention.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Hereinafter, an apparatus, method and computer program for scheduling power supply and supply operations according to the present invention will be described with reference to the accompanying drawings. In this process, the thicknesses of the lines and the sizes of the components shown in the drawings may be exaggerated for clarity and convenience of explanation. In addition, the terms described below are defined in consideration of the functions of the present invention, which may vary depending on the intention or custom of the user, the operator. Therefore, definitions of these terms should be made based on the contents throughout this specification.

FIG. 1 is a diagram illustrating a configuration of a micro grid in an apparatus for scheduling power supply and demand operations according to an exemplary embodiment of the present invention. FIG. 2 is a diagram illustrating an MG MCP in an apparatus for scheduling power supply and demand operations according to an exemplary embodiment of the present invention. FIG. 3 is an exemplary view for explaining a configuration of a new power market in an apparatus for scheduling power supply and supply operations according to an embodiment of the present invention. FIG. 5 is a diagram for explaining an appropriate range of the MG MCP in the power supply / demand operation scheduling apparatus according to an embodiment of the present invention. FIG. 5 is a diagram illustrating an operation scheduling input information, an operation scheduling algorithm, FIG. 6 is a diagram illustrating an example of a power supply / demand operation scheduling apparatus according to an embodiment of the present invention. FIG. 7 is an exemplary diagram illustrating a configuration of an energy storage device in the power supply / demand operation scheduling apparatus according to an embodiment of the present invention. Referring to FIG.

First, the precondition of this embodiment is clearly defined.

This embodiment can be applied to both cases of a linked operation state in which the micro grid is operated in conjunction with the upper system and an independent operation state in which the power is self-supplied in the micro grid. Hereinafter, As described above, it will be described based on the linked operation situation of the grid-linked micro grid.

1, the microgrid may include a demand resource (load) and a power generation resource for supplying power to the demand resource, and the power generation resource may include a renewable energy source, an energy storage device (ESS) Energy Storage System) and Distributed Generator (DG). Here, the renewable energy source is defined as a renewable power source, such as a solar generator or a wind turbine, which can not control its own power generation. The distributed power source is a power source capable of maintaining a desired output including a cogeneration generator, a diesel generator, .

The microgrid is a small power system, and there are constraints to maintain the power balance in the microgrid and to reserve power. Because the constraint characteristics are different for each generation resource included in the microgrid, There is a need to be expressed in a predetermined formula and reflected in the economic dispatch. In this embodiment, as described later, constraint conditions of power generation resources are mathematically modeled through power supply constraint conditions to perform power supply / demand operation scheduling.

In this embodiment, it is assumed that the power generation resources in the micro-grid trade electricity through bidding, and the costs and the settlement amounts of the demand and power generation amounts of demand and power generation resources in the micro grid are MG MCP MicroGrid Market Clearing Price. As shown in FIG. 2, it is possible to accumulate the bidding capacity from the generation resource having a low bid price and determine the bid price of the generation resource when the accumulated bid capacity equals the demand forecast value in the micro grid. At this time, although the bid price is basically lowered in the order of lower bid price, the order can be changed by the power supply and demand constraint to be described later. That is, the MG MCP can be determined not by the winning bid price but by the power generation resource having the highest bid price among the generated winning resources according to the operation scheduling algorithm to be described later.

In this embodiment, the new power market is defined as a concept covering the micro grid, the external power market, and the external power purchase market as shown in FIG. The microgrid performs power trading with the external power sales market and the external power purchase market based on the operation scheduling result information calculated through the operation scheduling algorithm to be described later. At this time, the power shortage in the micro grid is purchased from the external power purchase market on the basis of the retail price, and surplus power that is not won in the micro grid is sold based on the System Marginal Price (SMP) of the external power sales market.

As described above, based on the MG MCP, the settlement of power generation resources in the micro grid and the usage fee of demand resources are calculated. According to the MG MCP, participation and profit of the new power market participants including the micro grid are determined. There is a need to maintain a range of MG MCPs. Referring to FIG. 4, if the MG MCP is lower than the SMP, since the generation resources are more likely to exit the micro grid when the power is sold in the micro grid than in the external power sale market, the MG MCP is SMP And if the MG MCP is higher than the retail charge, the MG MCP should be below the retail rate, as demand resources are likely to deviate from the micro grid, as the cost of payment is reduced when purchasing power from the external power purchase market in the micro grid . SMP and retail rates vary by season and time, but basically the SMP tends to be lower than the retail rate, so the appropriate range of MG MCP is above SMP and below the retail rate.

The power supply / demand operation scheduling apparatus according to an embodiment of the present invention will be described in detail based on the preconditions of the present embodiment described above.

The apparatus for scheduling power supply and supply operations according to an embodiment of the present invention includes an operation scheduling algorithm for meeting the power supply and demand constraint of the micro grid and minimizing the generation cost of the power generation resources in the operation scheduling input information including the bidding information of each power generation resource, To calculate operating scheduling result information for operating the power supply and demand of the micro grid including the winning information of each generating resource. FIG. 5 shows an overall process of calculating the operational scheduling result information by using the operation scheduling input information and the operation scheduling algorithm by the power supply / demand operation scheduling apparatus.

Operational scheduling algorithms are based on mathematical optimization techniques as described below, and therefore there is a need to first mathematically model the components of the new power market.

To this end, the characteristics of distributed resources in the micro grid are summarized briefly. The new and renewable energy sources have characteristics that can not control power generation by themselves such as solar power generators and wind power generators. And the like. The energy storage device functions as an essential resource for constructing a new power market including the micro grid in terms of functions such as load leveling and output stabilization of renewable energy sources. Demand resources can include various loads such as industrial, commercial, and residential, depending on the resources of the participating customers.

Next, briefly summarizing the characteristics of the resources outside the micro grid, the external power purchasing market refers to a target market in which the power shortage in the micro grid is purchased. As an example, Korea can be described as Korea Electric Power Corporation, Of the demanded resources can purchase electricity according to the retail charge according to the subscription retailing plan. The external power sales market refers to the target market for surplus power that is not won in the micro grid, and it can be a small power brokerage market to be opened (or already established) in each country. You can sell your electricity.

Hereinafter, the operation scheduling algorithm of the power supply / demand operation scheduling apparatus will be described in detail with reference to an objective function and constraint conditions.

The operation scheduling algorithm of the present embodiment uses an objective function for minimizing the power purchase cost required to operate the power supply and demand of the micro grid and the power supply and demand constraint of the micro grid based on the operation scheduling input information, And may be set in the power supply / demand operation scheduling apparatus to calculate information.

Here, the operational scheduling input information includes renewable energy source bidding information including the bidding capacity (PR _{i, t} ) and the bid unit price (CR _{i, t} ) of the renewable energy source and the bidding charge amount PE _{j t} ) and the bid price (CE _{j, t} ), the bidding capacity (PG _{k, t} ) of the distributed power source and the generation cost function information (A _k , B _k , Lt; _{RTI ID = 0.0} > _Ck. &_Lt; / _RTI >

At this time, the energy storage device bidding information includes the charge / discharge efficiency (η _j ), the maximum storage capacity (Cap _{max, j} ), the minimum allowable SoC (State of Charge, SoC _{min, j} ) _{max, j)} the may further comprise, distributed generation bid information is distributed in the maximum amount of evaporation power (RU _k) and the maximum amount gambal (RD _k), start time information (MUT _k, LU _k ) and stop time information (MDT _K , LD _k ).

First, the renewable energy source bidding information will be described. The power receiving and operating scheduling apparatus receives mathematically modeled renewable energy source bidding information as shown in Table 1 below.

Item	unit	Explanation
PR i, t	kW	Bidding capacity at time t of renewable energy source i
CR i, t	Yuan / kWh	Bidding unit at time t of renewable energy source i

As shown in FIG. 6, the electric power generated by the renewable energy source can be divided into a quantity used in the micro grid and a quantity sold to the outside, and the amount of winning bid for the renewable energy source is used in the micro grid And are settled in accordance with the MG MCP, and those not sold are sold under the SMP to the external power sales market.

Next, the energy storage device bidding information will be described. The power supply / demand operation scheduling device can receive energy storage device bidding information modeled mathematically as shown in Table 2 below.

Item	unit	Explanation
PE j, t	kW	The amount of bidding charge at time t of energy storage j
CE j, t	Yuan / kWh	The bid unit at time t of energy storage j
η j	%	Charge / discharge efficiency at time t of energy storage device j
Cap max, j	kWh	The maximum storage capacity at time t of energy storage j
SoC min, j	%	The minimum allowable SOC at time t of energy storage j
SoC max, j	%	The maximum allowable SOC at time t of energy storage j

As shown in FIG. 7, the energy storage device is composed of a battery for storing energy and a PCS (Power Conditioning System) for powering in and out.

In this embodiment, the charging and discharging state is indicated by using a sign (PE _{j, t} > 0, and PE _j, when discharging) _t <0). Also, in the case of energy storage devices, only the price for the discharge is bidded, and the charging charge is calculated based on the retail charge of the external power purchase market. In the case of an energy storage device, it is treated as a load during charging and added to the demand term of the power supply and demand constraint as described later, and is treated as a generation resource during the discharge and added to the supply term of the power supply constraint. Also, when considering the sales outside the grid, the amount of energy storage device discharge can be divided into internal consumption amount and external sales volume as well as the amount of renewable energy generation. Furthermore, the energy remaining in the battery of the energy storage device is represented by SoC (State of Charge), and a model that linearly increases with respect to the charging amount can be used. Since the charging / discharging efficiency of the PCS is considered, The discharge quantity should be modeled with each other variable rather than a single variable, and for safe operation of the energy storage device, the energy storage device should be operated within the allowable SoC range. Table 2 shows the result of mathematically modeling the above-mentioned contents.

Next, the bidding information of the distributed power supply will be described. The power supply / demand operation scheduling device can receive the energy storage device bidding information modeled mathematically as shown in Table 3 below.

Item	unit	Explanation
PG k, t	kW	Bid capacity at time t of distributed power k
A k	KRW / kW 2	The quadratic coefficient of the power cost function of the distributed power source k
B k	Won / kW	First order coefficient of power cost function of distributed power source k
C k	won	The constant cost of the power cost function of the distributed power k
RU k	kW / min	Maximum evaporation amount of dispersed power source k
RD k	kW / min	The maximum amount of decay of distributed power k
MUT K	hour	Minimum startup time of distributed power k
MDT K	hour	Minimum stop time of distributed power k
LU k	hour	The time the distributed power source k last lasted
LD k	hour	The time the distributed power source k was last stopped

In the case of distributed power generation, unlike other power generation sources that apply a fixed unit price regardless of power generation amount, a second generation power generation cost function is used. Accordingly, the marginal cost is changed according to the power generation amount. The function can be changed to a linear function or a constant function.

In addition, a general model is used in the case of a distributed power source, so that the increase / decrease restriction (output fluctuation constraint), the minimum start time and the minimum stop time constraint (start and stop hold time constraints) .

Here, the amount of evaporation represents the amount by which the output of the generator is increased by one minute, and the maximum evaporation amount represents the maximum value of this value. The amount of decay represents the amount by which the output of the generator decreases by one minute, and the maximum decay amount represents the maximum value of this value. The minimum stop time is the minimum time that the generator must be kept in a stopped state before restarting when the generator is stopped, and the minimum startup time must be maintained until the generator is stopped and then stopped again It means minimum time. In order to determine whether to start the engine, the time (LU _k ) and the time (LD _k ) during which the engine was last operated are stored, and the values of LU _k and LD _k are 0 or more The other value must be a value of zero. In addition, when considering off-grid sales, the amount of power generated by the distributed power supply can be divided into internal consumption and external sales volume, as well as the amount of power generated by renewable energy sources. Table 3 above shows the result of mathematically modeling the above-mentioned contents.

On the other hand, the operation scheduling input information includes power transaction information CBMG _{l, t} , PBMG _{1, t} , CSMG _{1, t} , PSMG _{l, t} ), the power trading information (RtlP _t , SMP _t ), and demand forecast information (Load _t ) in the microgrid. Accordingly, the power supply / demand operation scheduling apparatus can receive mathematically modeled input information as shown in Table 4 below.

Item	unit	Explanation
CBMG 1, t	Yuan / kWh	Hourly electricity purchase price of adjacent micro grid l
PBMG 1, t	kW	Hourly power purchase threshold of adjacent micro grid l
CSMG 1, t	Yuan / kWh	Hourly electricity sales unit price of adjacent micro grid l
PSMG l, t	kW	Hourly electricity sales limit of adjacent micro grid l
SMP t	Yuan / kWh	SMP predicted value at time t
RtlP t	Yuan / kWh	Retail rates at time t
Load t	kW	Demand forecast at time t

Based on the operation scheduling input information described above, the power supply / demand operation scheduling apparatus can calculate operating scheduling result information for operating power supply and demand of the micro grid.

More specifically with respect to the operation scheduling result information, operation scheduling result information is renewable internal use energy of the energy source (P_RI _{i, t)} and external sales amount of power (P_RE _{i, t)} for new and renewable energy source, bid information including a and a charge amount of the energy storage device (P_EC _{j, t),} internal use discharge amount (P_EDI _{j, t)} and external sales discharge amount (P_EDE _{j, t)} an energy storage device bid information, and internal use of distributed generation that contains the The distributed power supply winning bid information including the amount of power P_GI _{k, t} and the amount of external sales power P_GE _{k, t} .

Here, the energy storage device winning information includes the SoC information (SoC _{j, t} ) of the energy storage device, and the distributed power supply winning bid information includes the starting state information (u _{k, t} ) _{k, t} , ud _{k, t} ).

In addition, operating scheduling result information, adjacent purchase power from the micro-grid (P_buyMG _{l, t)} and the adjacent micro-grid power exchange information, the external power purchase market adjacent a selling power (P_sellMG _{l, t)} of a microgrid (P_buyR _t ) from the external power market and the sales power amount (P_sellW _t ) to the external power market.

The operational scheduling result information is mathematically modeled and summarized in Table 5 below.

Item	unit	Explanation
P_RI i, t	kW	The amount of internal power used by renewable energy source i over time
P_RE i, t	kW	The amount of renewable energy i sold over time
P_EC j, t	kW	The charge amount of the energy storage device j over time
P_EDI j, t	kW	Of the discharge amount of energy storage device j,
P_EDE j, t	kW	Of the discharge amount of the energy storage device j,
SoC j, t	%	Time-dependent SoC of energy storage device j
P_GI k, t	kW	The internal power consumption of the distributed power source k over time
P_GE k, t	kW	The amount of external sales power of distributed power source k over time
u k, t		Time-based start-up state of distributed power supply k
du k, t		Whether or not the distributed power source k is operated by time (1 only when the generator is stopped at time t)
ud k, t		Whether the distributed power supply k is stopped by time (1 only when the generator is stopped at time t)
P_buyR t	kW	The amount of electricity purchased from external electricity purchasing market by hour
P_sellW t	kW	The amount of electricity sold to the external power sales market by hour
P_buyMG l , t	kW	The amount of electricity purchased per hour from the adjacent micro grid l
P_sellMG l , t	kW	Sales power to adjacent micro grid l

The power supply operation scheduling apparatus can calculate the operation scheduling result information as shown in Table 5 by applying the operation scheduling algorithm to the operation scheduling input information. At this time, as described above, a mathematical optimization technique can be applied to the operation scheduling algorithm, and the operation scheduling algorithm aims at scheduling an hourly schedule for the next 24 hours.

First, the objective function of the operation scheduling algorithm will be described in detail.

The operation scheduling algorithm is based on the operation scheduling input information, and it is based on the information of the power purchase cost from the renewable energy source, the cost due to charging and discharging of the energy storage device, the power generation cost of the distributed power source, And to minimize the cost of purchasing power required to operate the power supply and demand of the micro grid in consideration of the cost of each power trading between the external power purchase market and the external power sale market (that is, The scheduling result information can be set to be calculated using the objective function (for minimization). The objective function can be expressed by the following equation (1).

In Equation (1), a term relating to the power purchase cost from the renewable energy source

), The cost of purchasing power from renewable energy sources is calculated by multiplying the bid price of new and renewable energy sources by the amount of internal power used by renewable energy sources. In the case of external sales power, It is not reflected in the objective function because it is supposed to be sold directly to the electricity sales market.

Next, in Equation (1), a term relating to the charge and discharge of the energy storage device

In the case of charging the energy storage device, since it corresponds to the case where the energy storage device purchases power in the new power market as a load, it takes an (-) sign to reduce the total power purchase cost, The cost of purchasing electricity from the MicroGrid operator is calculated by multiplying the bid price of the energy storage unit by the discharge amount. At this time, the amount of discharge of the energy storage device is divided into the internal use discharge amount and the external sales discharge amount. However, unlike the case of the renewable energy source, since the microgrid assumes the method in which the operator purchases and sells it to the outside, The sales discharge amount is reflected.

Next, in Equation (1), the term &quot;

), The f _k function at the term of the generation cost of the distributed power source is expressed by the following equation (2).

Next, the terms related to the cost of power trading with the adjacent microgrid in Equation (1) will be described. When the power is purchased from the adjacent microgrid, the cost of purchasing power increases. When the power is sold to the adjacent microgrid, Since the income is generated, the corresponding income is deducted from the total objective function.

Next, in Equation (1), a term relating to the cost of each power transaction between the external power purchase market and the external power sale market

), Electric power is purchased according to the retail price in case of purchasing power from the external power purchase market, and electric power is sold in accordance with SMP in case of power sale to the external power sale market.

The power supply and demand constraints of the operation scheduling algorithm are explained in detail.

The operating scheduling algorithms can be classified as follows: Renewable energy source constraints including output constraints of renewable energy sources, energy storage device constraints including output constraints of energy storage devices, distributed power constraints including output constraints of distributed power sources, And an external power market constraint including a power trading restriction with an external power sales market.

First, the constraint on the renewable energy source will be described. The output constraint of the renewable energy source can be expressed by the following equation (3).

Specifically, since the new renewable energy source is bid with a constant bid price per hour, it is expected that the entire amount of the bid amount will be used inside the micro grid or the entire amount will be sold to the outside. In this embodiment, And the sum of the sales power is equal to the bidding capacity of the renewable energy source.

Next, the energy storage device constraint condition is expressed by Equation (4) and Equation (5).

Specifically, when PE _{j, t} <0, the energy storage device bids the charging schedule and Equation (4) is applied. If PE _{j, t} > 0, the energy storage device bids the discharge schedule Apply equation (5). That is, Equations (4) and (5) are complementarily applied according to the signs of PE _{j, t} . Equations 4 and 5 mean that the charging and discharging amount of the energy storage device should be determined within the bidded schedule, and the bidding charge amount of the energy storage device is assumed to be within the limit of the energy storage device do.

On the other hand, according to the energy supply state in the micro grid, only a part of the schedules bidded by the energy storage device may be charged or discharged. In this case, there may arise a problem that the SoC of the energy storage device can not be guaranteed to be within the allowable SoC range , The energy storage device constraint in this embodiment is set based on the charge / discharge efficiency of the energy storage device, the maximum storage capacity, the minimum allowable SoC, and the maximum allowable SoC, And may further include range operating constraints. The allowable SoC range operation constraint can be expressed by the following equations (6) to (9).

Equation (6) defines the relationship between the charge amount of the energy storage device and SoC. That is, the SoC is calculated according to the SoC of the previous time and the charge amount of the corresponding time (the SoC should be calculated as the product of the input power and the time, but in the present embodiment, the time term is not considered ). Equations 7 and 8 show that SoC _{j, t} according to Equation 6 is kept within the minimum allowed SoC and maximum allowed SoC range provided at the time of bid. Equation (9) represents a constraint condition that the SoC of the scheduling end time is maintained at the minimum SoC, and it is possible to prevent the energy storage device from being used only from the energy storage device according to Equation (9).

Describing the distributed power constraint, the output constraint of the distributed power is expressed by the following equation (10).

The amount of power generated by the distributed power supply is divided into the internal power consumption and the external sales power, and the sum should be smaller than the bid capacity. In addition, when the distributed power source is in operation, u _{k, t} of the right side must be 1 in order to generate the power greater than 0, which can indicate the starting state of the generator.

On the other hand, in the suspended state of the distributed power source,

, And u _{k, t} in the equation can be any value between 0 and 1. Therefore, in order to prevent such a situation, the following constraint condition may be added.

When the power generation amount is generated by the distributed power source according to Equation (11), u _{k, t} must be 1, and for this, epsilon of Equation (11) has a small value that does not affect the determination of the starting state of the distributed power source Can be set to a constant.

On the other hand, the distributed power constraint condition further includes an output fluctuation constraint set on the basis of the maximum evaporation amount and maximum evaporation amount of the distributed power source, and the start and stop hold time constraints set based on the start time information and the stop time information of the distributed power source .

Specifically, there is a limitation in the fluctuation range of the output per unit power of the distributed power source, the maximum evaporation amount means the limit of the power generation amount per minute, and the maximum amount of discharge means the limit of the power generation amount per minute. Based on this, the output fluctuation constraint can be expressed by the following equations (12) and (13).

Equation (12) means that the difference between the generation amount of the current time and the generation amount of the previous time should be equal to or less than the maximum evaporation amount, and the equation (13) means that the difference between the generation amount of the previous time and the generation amount of the present time should be less than the maximum amount of evaporation.

In addition, if the state of the divided power source changes from the stop state to the start state, the start state can not be stopped again for a predetermined time, and the minimum start time means the minimum time for the start state to be maintained. Expression (14) is expressed as Equation (14).

The left side of Equation (14) is a sum of variables representing the starting state of the distributed power source for the minimum startup time just before the time when the distributed power source is stopped. If this sum is not less than the minimum start time, ud _{k, t} can be 1, which means that the distributed power can only be stopped if the start state is maintained from 1 hour before to 1 hour before the minimum start time.

Likewise, when the state of the divided power source changes from the start state to the stop state, it can not be restarted for a predetermined time and the stop state must be maintained, and the minimum stop time means the minimum time during which the stop state must be maintained. The stop hold time constraint can be expressed by Equation (15).

The left side of Equation (15) is a sum of (1 - variable indicating the starting state of the distributed power source) for the minimum stop time from immediately before the time when the distributed power source is started, and is equal to the sum of the times when stopped before starting. If this sum is greater than the minimum stop time, then du _{k, t} can be 1, which means that the distributed power source can only be started if the stop time is maintained from 1 hour to 1 hour before the minimum stop time.

Meanwhile, in the present embodiment, the external power market restriction condition included in the power supply and demand constraint is that only the surplus power generated by the power generation resources included in the micro grid is sold to the adjacent micro grid and the external power sales market This means that the power trading restriction is allowed.

Concretely, if the general electricity supply and demand constraints used in the problem of economic dispatch and generator stoppage plan are used, there may arise a problem that the electricity purchased in the external power purchase market is sold again to the external power sale market. For example, retail pricing in the external power purchasing market may cause problems because the retail price is lower than the SMP at the time of the upper light load. If the amount of electricity purchased from the external power purchasing market and the amount of power sold to the external power market are not limited , There may arise a problem that the operation scheduling of the new power market of the present embodiment can not be normally performed.

Therefore, the present embodiment employs a configuration that prevents the above-described problems by adding the power trading restriction to the power supply limiting constraint. Specifically, the amount of internal power used in the micro grid is the amount of power supplied to the demand resource in the micro grid, and the sum of the internal power consumed and the external purchased power must be equal to the sum of the demanded power in the micro grid. Here, the amount of externally purchased power means the sum of the amount of purchased electricity from the external power purchase market and the amount of purchased electricity from the adjacent micro grid. The above description can be expressed by the following equation (16).

That is, Equation (16) represents the power supply condition in the micro grid.

In addition, the sales amount of electricity to the external power sales market and the adjacent micro grid must be equal to the sum of the external sales amount among the total generation amount in the micro grid, and it can be expressed by the following equation (17).

That is, Equation (17) implies a constraint on external power sales volume.

On the other hand, the amount of power generated by the unbundled renewable energy source is not reflected in the equation (17) since it is assumed that the generation of the new and renewable energy source is directly sold to the external power sale market without mediating the micro grid operator.

The operation scheduling input information, the operation scheduling result information, the objective function, and the power supply constraint conditions are summarized as follows.

1. Operation scheduling input information and operation scheduling result information

Item	Operational scheduling input information	Operational scheduling result information
Renewable energy source	PR i, t , CR i, t	P_RI i, t , P_RE i, t
Energy storage device	PE j, t , CE j, t , η j , Cap max, j , SoC min, j , SoC max, j	P_EC j, t , P_EDI j, t , P_EDE j, t , SoC j, t
Distributed power	PG k, t , A k , B k , C k , RU k , RD k , MUT K , MDT K , LU k , LD k	P_GI k, t , P_GE k, t , u k, t , du k, t , ud k, t
External component	CBMG 1, t , PBMG 1, t , CSMG 1, t , PSMG 1, t , SMP t , RtlP t , Load t	P_buyR t , P_sellW t , P_buyMG l , t , P_sellMG l , t

2. Objective function

3. Power supply constraints

① New and renewable energy constraints (renewable energy source output constraint)

② Energy storage device constraint

a. Energy Storage Output Constraints

b. Allow SoC scope operating constraints

③ Distributed power constraint

a. Distributed power output constraint

b. Output fluctuation constraint

c. Start and stop hold time constraints

④ External power market constraint

a. Power supply condition in micro grid

b. External power sales constraints

8 to 17 illustrate an example of performing scheduling for operating the power supply and demand of the new power market by applying the power supply and demand operation scheduling apparatus according to the present embodiment. The conditions applied to the example shown in Figs. 8 to 17 will be described below.

It is assumed that the power generation resources in the micro grid consist of one renewable energy source generator, one energy storage device, and one distributed resource generator. The renewable energy source generator is assumed to have a generating capacity of 12.5MW maximum by borrowing the pattern of the photovoltaic generator, and the energy storage device is assumed to have a capacity of 5MW / 10MWh. The distributed power generators are assumed to be a kind of cogeneration generators, and it is assumed that the minimum startup time and the minimum stopping time are less than one hour, considering that they are small resources. MUT and MDT, LU _k and LD _k are all set to 0, and the increase / decrease amount is set to a very large number assuming that the increase / decrease speed is sufficient and the maximum output can be reached within one hour.

FIG. 8 shows an example of renewable energy source bidding information, FIG. 9 shows an example of energy storage device bidding information (CE _t is assumed to be 100 won / kWh) FIG. 11 shows the electric power transaction information with respect to the external electric power purchase market (for example, the retail price of KEPCO, the high-voltage B-selection II charge for industrial use (applied to the spring and autumn charge plan)), (I.e., SMP) with the electricity sales market, and FIG. 13 shows demand forecast information in the micro grid. FIGS. 14 and 15 show the results of the comparison between the total amount of demand and total bidding for each hour, the retail price and the SMP based on the operational scheduling bidding information shown in FIGS. 8 to 13. FIG. 16 and FIG. 17 show the results of summarizing the operational scheduling input information and the operational scheduling result information in the above-described examples, respectively.

Meanwhile, in the present embodiment, the power supply / demand operation scheduling apparatus includes an FPGA (Field Programmable Gate Array) or an ASIC (Application Specific Integrated Circuit) that performs an operation scheduling algorithm on operation scheduling input information to calculate operation scheduling result information, And may be implemented as a computer device containing the same hardware.

18 is a flowchart illustrating a power supply / demand operation scheduling method according to an embodiment of the present invention.

Referring to FIG. 18, a power supply / demand operation scheduling method according to an embodiment of the present invention receives operating scheduling input information including bidding information of each power generation resource (S10).

Next, the power supply / demand operation scheduling apparatus applies an operation scheduling algorithm to meet the power supply and demand constraint of the micro grid and minimize the power generation cost of the power generation resource, to the operation scheduling input information received in operation S10, And calculates operating scheduling result information for operating power supply and demand of the micro grid (S20).

Meanwhile, the power supply / demand operation scheduling method according to the present embodiment may be prepared as a computer program for executing steps S10 and S20 in combination with hardware, and may be stored in a computer-readable recording medium to operate the computer program And can be implemented in a general-purpose digital computer. Examples of the computer readable recording medium include a ROM, a RAM, a CD-ROM, a magnetic tape, a floppy disk and an optical data storage device, and a carrier wave (for example, transmission via the Internet) . The computer readable recording medium may also be distributed over a networked computer system so that computer readable code is stored and executed in a distributed manner.

As described above, the present embodiment can flexibly cope with the power peak situation, enabling more stable system operation, reducing transmission / distribution operation cost and loss cost, reducing carbon emission, and improving energy efficiency.

While the present invention has been particularly shown and described with reference to exemplary embodiments thereof, it is clearly understood that the same is by way of illustration and example only and is not to be taken by way of limitation, I will understand. Accordingly, the true scope of the present invention should be determined by the following claims.

Claims (16)

1. Demand Resource (DR); And a power generation resource including a renewable energy source for supplying power to the demanded resource, an energy storage system (ESS), and a distributed power generator (DG) A scheduling device for operating power supply /

   An operating scheduling algorithm for meeting the power supply and demand constraint of the micro grid and minimizing the generation cost of the power generation resources is applied to the operating scheduling input information including the bidding information of each power generation resource, And calculates operating scheduling result information for operating the power supply and demand of the micro grid.
2. The method according to claim 1,

   Wherein the operating scheduling algorithm comprises: an objective function for minimizing the power purchase cost required to operate the power supply and demand of the microgrid based on the operational scheduling input information, Wherein the scheduling information is configured to calculate operational scheduling result information.
3. 3. The method of claim 2,

   Wherein the operation scheduling input information includes at least one of renewable energy source bidding information including a bidding capacity and a bid price of the renewable energy source, energy storage device bidding information including a bidding charge quantity and a bid price of the energy storage device, And b) distributed power supply bidding information including bidding capacity and power generation cost function information of the distributed power supply.
4. The method of claim 3,

   The energy storage device bidding information may further include charge / discharge efficiency, maximum storage capacity, maximum allowable SoC (State Of Charge), and minimum allowable SoC information of the energy storage device, and the distributed power supply bidding information may include a maximum evaporation amount , A maximum amount of deceleration, start time information, and stop time information.
5. 5. The method of claim 4,

   Wherein the operational scheduling result information includes new and renewable energy source winning information including an internal usage amount of the renewable energy source and an external sales amount of electricity and a charging amount of the energy storage device, And a distributed power supply awarding information including an energy storage device winning information, an internal power consumption of the distributed power supply, and an external sales power amount.
6. 6. The method of claim 5,

   Wherein the energy storage device winning information further includes SoC information of the energy storage device, and the distributed power supply winning bid information further includes startup state information and activation / deactivation information of the distributed power supply. Device.
7. The method according to claim 6,

   The operating scheduling input information may further include power trading information with adjacent micro grids, power trading information between an external power purchase market and an external power sale market, and demand forecast information in the micro grid. Power supply and demand operation scheduling device.
8. 8. The method of claim 7,

   The operational scheduling result information includes at least one of adjacent microgrid power trading information including a purchased power amount from the adjacent microgrid and a sales power amount to the adjacent microgrid, a purchase power amount from the external power purchase market, And an external power market power transaction information including a sales power amount of the external power market.
9. 9. The method of claim 8,

   Wherein the operating scheduling algorithm is further operable to calculate an operating scheduling algorithm based on the operating scheduling input information such as a cost of purchasing power from the renewable energy source, a cost of charging and discharging the energy storage device, An objective function for minimizing the power purchase cost required to operate the power supply and demand of the microgrid in consideration of the cost due to the power transaction and the cost due to each power transaction between the external power purchase market and the external power sale market, Wherein the operation scheduling result information is configured to calculate the operation scheduling result information using the scheduling result information.
10. 10. The method of claim 9,

    Wherein the operation scheduling algorithm includes: a renewable energy source constraint condition including an output constraint of the renewable energy source; an energy storage device constraint condition including an output constraint of the energy storage device; Power constraints, and external power market constraints including power trading constraints with the external power sales market. The power management system of claim 1, Supply and demand operation scheduling device.
11. 11. The method of claim 10,

    Wherein the energy storage device constraint is set based on charge / discharge efficiency, maximum storage capacity, minimum allowable SoC, and maximum allowable SoC of the energy storage device, the allowable SoC range Including operational constraints,

    Wherein the distributed power constraint condition includes an output fluctuation constraint set based on a maximum evaporation amount and a maximum evaporation amount of the distributed power supply and an output fluctuation constraint set on the basis of the startup time information and the stop time information of the distributed power supply Wherein the scheduling apparatus further comprises:
12. 11. The method of claim 10,

    The external power market constraint is a power trading restriction for permitting sales to the adjacent micro grid and the external power sales market only for surplus power among the power generated by the power generation resources included in the micro grid The power supply and demand operation scheduling device.
13. 13. The method of claim 12,

    The operational scheduling result information further includes a MGGCP (MicroGrid Market Clearing Price), which is a market clearing price in the micro grid,

    Wherein the internal power consumption of the renewable energy source, the internal usage discharge amount of the energy storage device, and the internal usage power amount of the distributed power supply are settled through the MG MCP.
14. 14. The method of claim 13,

    The amount of the external sales power of the renewable energy source and the amount of sales electricity to the external power sales market are settled through System Marginal Price (SMP)

    The amount of purchased electricity from the external power purchase market is settled through the retail charge of the external power purchase market,

    Wherein the MG MCP is calculated at a price equal to or higher than the SMP and equal to or less than the retail price.
15. Demand Resource (DR); And a power generation resource including a renewable energy source for supplying power to the demanded resource, an energy storage system (ESS), and a distributed power generator (DG) The method comprising the steps of:

    Receiving the operation scheduling input information including the bidding information of each of the power generation resources; And

    Wherein the power supply and demand operation scheduling apparatus applies an operation scheduling algorithm to satisfy the power supply and demand constraint of the micro grid and to minimize the power generation cost of the power generation resources in the inputted operation scheduling input information, Calculating operating scheduling result information for operating the power supply and demand of the micro grid including information;

    Wherein the scheduling method comprises:
16. Combined with hardware, it can be called a Demand Resource (DR); And a power generation resource including a renewable energy source for supplying power to the demanded resource, an energy storage system (ESS), and a distributed power generator (DG) A computer program for operating power supply /

    Receiving operational scheduling input information including bidding information of each power generation resource; And

    And an operation scheduling algorithm for meeting the power supply and demand constraint of the micro grid and minimizing the power generation cost of the power generation resources is applied to the received operating scheduling input information, Calculating operational scheduling result information for operating power supply and demand;

    Lt; RTI ID = 0.0 &gt; medium. &Lt; / RTI &gt;

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