View of REVIEW ON OPTIMAL ENERGY MANAGEMENT FOR VIRTUAL POWER PLANT WITH RENEWABLE

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Vol.04, Issue 02, February 2019 Available Online: www.ajeee.co.in/index.php/AJEEE

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REVIEW ON OPTIMAL ENERGY MANAGEMENT FOR VIRTUAL POWER PLANT WITH RENEWABLE

Abhishek Kumar, (Scholar) Namrata Sant

Asst. Prof., BITS Bhopal, MP, India

Abstract- This paper displays a thorough study on the new also intriguing idea of virtual control plant (VPP). The study blankets the virtual force plant definitions, components, Furthermore schema highlights those different strategies that might make utilized for VPP operation streamlining. Finally, An general structure to the operation and the streamlining of the virtual control plant is recommended examined.

Keywords: Distributed energy resources, Virtual power plant, VPP framework, and optimization.

I. INTRODUCTION

The idea about coordinating little generating units in the energy framework need pulled in great consideration in the most recent couple quite some time.

Moreover, disseminated era (DG) assumes a paramount part in reinforcing the principle generating energy plants will fulfill that developing force interest. Dg cam wood additionally make joined alternately disengaged undoubtedly from those organize Dissimilar to those fundamental energy plants, consequently giving work to higher adaptability.

Legitimately arranged and worked dg installations need a number profits for example, such that investment investment funds because of the decrement about force losses, higher reliability, also moved forward force caliber.

However, those expanded infiltration from claiming dg without agreement between those generating units might prompt increase of the grid force losses, undesirable voltage profiles, temperamental operation of the security devices, and unbalance the middle of the true utilization and the creation.

Therefore, will attain ideal prudent operation of the principle network, DER units ought further bolstering a chance to be noticeable of the framework driver.

The negative aspects of increased uncoordinated DG penetration are the basic motivation for the introduction of VPP concept. VPP is the aggregation of DG units, controllable loads and storage devices connected to a certain cluster in a single imaginative entity responsible for managing the electrical energy flow within the cluster and in exchange with the main network. The VPP concept was proposed early in [1] with its framework. Earlier,

DER was installed with a “fit and forget”

approach and they were not visible to the system operators. VPP aggregated all DERs into a single entity through which distributed energy resources (DERs) would have system visibility and controllability and market impacts as transmission-connected generators [2].

Different studies analyzed the VPP concept in three major directions:

 First direction concerned with classifying DGs inside the VPP structure according to their capacity and ownership. Two categories were reported; Domestic DG (DDG) and Public DG (PDG).

Another DG classification was presented according to their operational nature; either stochastic or dispatch able.

 Second direction focused on the VPP structure both technically and commercially; Technical VPP (TVPP) and Commercial VPP (CVPP), and their functionalities.

 Third direction slanted towards the optimization of the VPP operation.

Some of these studies focused on VPP structure optimization by selecting the optimal size and location of the VPP components. On the other hand, other studies highlighted the profit maximization of the VPP.

This paper presents a literature review of VPP definitions, components, and framework. Furthermore, it simplifies the relations/correlations between VPP structure entities and their responsibilities. Finally, a survey is presented of the different techniques that can be proposed to optimize the operation of the VPP.

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2 II. VPP DEFINITIONS

The mossy cup oak later VPP idea need Different definitions which constantly on concur upon the way that VPP may be a amassed of dg units about diverse advances so as with work Likewise An absolute force plant that need the capacity should control those total apples and oranges units will deal with those electrical vitality stream the middle of these units in place will get finer operation of the framework [2-6]. To [2], VPP is characterized Likewise “A adaptable representational of a portfolio from claiming disseminated vitality assets (DER) that could a chance to be used to aggravate contracts in the wholesale advertise Also with the table administrations of the framework operator”. On [3], VPP will be characterized Likewise “A data and correspondence framework for incorporated control in an amassed from claiming DGs, controllable loads and capacity devices”. On [4], VPP is characterized concerning illustration “An amassed from claiming DER including different DER technologies, receptive loads Also capacity gadgets which, the point when incorporated bring adaptability controllability comparable will expansive traditional control plants”.

To [5], VPP may be characterized likewise

“A bunch about scattered generator units, controllable loads storages systems, total

apples and oranges so as will work similarly as a exceptional energy plant.

Those generators could utilization both fossil renewable vitality wellsprings (RES).

The heart of a VPP will be an vitality administration framework (EMS) which coordinates the force streams advancing from those generators, controllable loads storages”. In [6], VPP will be characterized Likewise “An amassed from claiming diverse sorts from claiming disseminated assets which might be scattered in distinctive focuses about medium voltage appropriation networks”.

From the presented definitions a comprehensive definition is proposed. VPP can be defined as “A concourse of dispatch able and non dispatch able DGs, energy storage elements and controllable loads accompanied by information and communication technologies to form a single imaginary power plant that plans, monitors the operation, and coordinates the power flows between its component to minimize the generation costs, minimize the production of green house gases, maximize the profits, and enhance the trade inside the electricity market”.

III. VPP COMPONENTS AND MODEL VPP consists of three main components, distributed energy resources, energy storage systems and information and communication technologies as shown in Fig. (1).

Fig. 1 VPP simplified model

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3 A. Distributed energy resources (DER) DER can be either distributed generators or controllable loads connected to the network. From the authors’ point of view, DGs within the VPP premises can be classified according to:

1) Type of the primary energy source:

According to the primary energy source type, DGs can be classified into two categories;

 Generators utilizing RES (such as wind-based generators, photovoltaic arrays, solar-thermal systems, and small hydro-plants).

 Generators utilizing non-RES (such as Combined Heat and Power (CHP), biomass, biogas, diesel generators, gas turbines, and fuel cells (FC)).

2) Capacity of DG units:

According to DG units’ capacities, DGs can be classified into two categories;

 Small-scale capacity DGs that must be connected to the VPP in order to gain access to the electricity market; or they could be connected together with controllable loads to form micro grids that may or may not participate in the VPP based on their capacities.

 Medium- and large-scale capacity DGs that can individually participate in the electricity market but they may choose to be connected to VPP to gain optimal steady revenue.

3) Ownership of DG units:

DGs within the VPP premises may be;

 Residential-, Commercial-, and Industrial-owned DGs used to supply part/all of its load in its own premises. They can be referred to as Domestic DGs (DDG) [3].

 Utility-owned DGs that are used to support the main grid supply shortage. They may be called Public DGs (PDG).

 Commercial company-owned DGs that aim to gain profits from selling power production to the grid. They can be named Independent Power Producers DGs (IPPDG).

4) DGs operational nature [7]:

DGs operational nature can be classified into two cases:

 Stochastic nature: In case of wind- based and photovoltaic DG units, the output power is not controllable as it depends on a variable input resource. To overcome this nature, this type of DG must be equipped with battery storage in order to be able to control the output power.

 Other DG technologies such as FCs and micro-turbines have an operational dispatch able nature.

They are capable of varying their operation quickly. Therefore, in general, VPP should include controllable loads, Energy Storage Elements (ESE) and dispatch able DGs in order to compensate the vulnerability of the stochastic nature-DG type.

B. Energy Storage systems (ESS)

ESS and its components assume a critical part for bridging the hole between those era demand, particularly in the vicinity for secondary infiltration of stochastic era.

Vitality capacity components (ESEs) might store vitality throughout off-top periods Furthermore encourage it throughout the crest periods. It likewise might ideally redistribute the yield force of wind turbines photovoltaic arrays All around those day. ESS cam wood be arranged as stated by their applications; i.

E. Supplying force alternately vitality [8], as takes after:.

 Energy supply class includes:

o Hydraulic Pumped Energy Storage (HPES)

o Compressed Air Energy Storage (CAES)

 Power supply class includes:

o Flywheel Energy Storage (FWES)

o Super Conductor Magnetic Energy Storage (SMES)

o Super Capacitors

C. Information and Communication systems

The energy management system (EMS) represents the heart of the information and communication system. It manages the operation of other VPP components through communication technologies in bidirectional ways, as shown in Fig. (1).

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4 The EMS has the following responsibilities [9]:

 Receiving information about the status of each element inside the VPP.

 Forecasting RES primary sources and output power.

 Forecasting and management of loads.

 Coordinating the power flow between the VPP elements

 Controlling the operation of DGs, storage elements, and controllable loads.

The EMS’s aim is to achieve one of the following targets:

 Minimization of generation cost.

 Minimization of energy losses.

 Minimization of greenhouse gases.

 Maximization of profit.

 Improvement of voltage profile.

 Enhancement of power quality.

IV. VPP FRAMEWORK

VPP is an extensive substance that includes an immense number of DGs, controllable loads, Also stockpiling components under An layer about data Furthermore correspondence innovations (ICT). VPP is answerable for regulating the supply and manages the electrical vitality stream not best inside its group as well as in return with the principle grid. In addition, VPP could also offer people of old and energy caliber administrations.

Should attain these functions, VPP must identity or those accompanying instruments [3]:

 ICT infrastructure.

 Monitoring and control applications.

 Smart metering and control devices installed at the customer sites.

 Software applications to forecast the power generation of the VPP.

For the sake of specialization, VPP is subdivided into two entities; Technical Virtual Power Plant (TVPP) and Commercial Virtual Power Plant (CVPP).

These two entities operate together in order to achieve the VPP functions. TVPP and CVPP functionalities and responsibilities are as follows:

A. Technical virtual power plant (TVPP) TVPP is responsible for the correct operation of the DER and the ESSs in order to manage the energy flow inside the VPP cluster, and execution of ancillary services. TVPP receives information from the CVPP about the contractual DGs and the controllable loads, this information must include:

 The maximum capacity and commitment of each DG unit.

 The production and consumption forecast.

 The location of DG units and loads.

 The capacity and the locations of the energy storage systems.

 The available control strategy of the controllable loads at all times during the day according to the contractual obligations between the VPP and the loads.

Based on the information received from the CVPP in addition to the detailed information about the distribution network topology, TVPP ensures that the power system is operated in an optimized and secure way taking physical constraints and potential services offered by VPP into account. The following functions are provided by the TVPP [10]

and [11]:

 Managing the local system for distribution system operators (DSO)

 Providing balancing, management of the network and execution of ancillary services.

 Providing visibility of the DERs in the distribution network to the transmission system operator (TSO) allowing DG and demand to contribute to the transmission system management activities.

 Taking care of the DER operation according to requirements obtained from CVPP and system status information.

 Monitoring continuously the condition for the retrieval of equipment historical loadings.

 Asset management- supported by statistical data.

 Self-identification of system components

 Determining of fault location.

 Facilitating maintenance.

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 Optimizing of project portfolio and statistical analysis.

B. Commercial Virtual power plant (CVPP)

CVPP recognizes DERs Similarly as business substances advertising that value measure from claiming vitality that it might deliver, upgrading prudent use from claiming VPP portfolio for the power business [11]. CVPP performs reciprocal contracts for both the dg units and the clients. These contracts’ majority of the data will be sent of the TVPP so as on detract the measure of the contracted control under attention throughout the execution about specialized foul investigations. Little-scale dg units are not capable to take part in the power showcase separately. Therefore, CVPP makes these units unmistakable of the power business. The CVPP functionalities need aid summarized concerning illustration takes after [4] and [11]:

 Scheduling of production based on predicted needs of consumers.

 Trading in the wholesale electricity market

 Balancing and/or trading portfolios

 Providing of services to the system operator

 Submitting of DERs’

characteristics and costs and maintenance

 Production and consumption forecasting based on weather forecasting and demand profiles.

 Outage demand management

 Constructing DER bids and submitting them to the electricity market.

 Scheduling of generation and daily optimization

 Selling DER power in the electricity market.

In order to achieve the above mentioned targets, CVPP interacts with the following entities [11]:

 DER: Its main function is to bridge the gap between demand and production. Its production must be planned, forecasted, and transferred that information to the TVPP.

 Balance Responsible Party (BRP):

It is an energy trading entity with

a property to make its own production/consumption plan available to be used by TVPP.

 Transmission System Operator (TSO): It has a main role in maintaining the instantaneous supply and demand balance in the network.

 TVPP: It receives information from CVPP and takes it into consideration in optimizing the operation of the VPP and its interaction with the main grid.

V. VPP VERSUS MICROGRID

Concerning the control framework deregulation, another era from claiming appropriation networks will be created named animated conveyance networks (ADN). ADN may be characterized concerning illustration An circulation system whose driver camwood remotely and naturally control those DER units Furthermore system topology should effectively deal with and ideally use the system advantages [12]. The ADN mind will be the vital control framework that is skilled about settling on control movements send control signs of the DER units. Those focal control framework plans should improve those DER controllability and the specialized foul and prudent profits attained by both the DER owners and the host grid [13]

Furthermore [14].

Those ADN particular idea radically progressions those accepted conveyance framework under another conveyance standard. Thus, dissemination frameworks could be decayed under smaller, autonomously- operated systems, known as micro grid that need An focal framework controller facilitating the operation for DER units controllable loads. Utilizing that Virtual energy Plant (VPP) concept, each little autonomously worked framework might be exhibited as total apples and oranges controllable assembly. This gathering is accessible to use previously, framework oversaw economy works In higher system voltage levels [14].

VI. VPP OPTIMIZATION

The optimal VPP operation aims at enhancing its operation and minimizing the cost of its produced energy. This section surveys the publications in this field. VPP future optimization studies can

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6 be divided into two main categories from the authors’ point of view.

A. Selecting VPP structure by optimizing its components.

B. Optimizing the VPP operation.

These two categories are explained as follows:

A. Optimization of the VPP structure VPP as an independent entity that has the ability to perform two sets of contracts:

 Bilateral contracts with DG units.

These contracts include the maximum DG units’ capacities and the obligations of these units towards the VPP.

 Contracts with customers that include the category of the load and the possibility of controlling or even interrupting it. The corresponding

controlling/interruption duration and initiation times.

VPP streamlining technique relies on the force framework under study;

whichever though it is new or existing. To A newly-established control system, VPP need the capacity to decide the ability Furthermore area of the dg units Furthermore ESEs, and the areas of the loads with make regulated and the proper control methodologies Also schedules. On the great holders kept all for existing force systems, these choices need aid constrained similarly as those area and size of the dg units and ESEs, and the areas of the controllable loads need aid pre-determined.

The following ideas are proposed for VPP structure optimization:

1) DG units’ optimal sizing and siting:

Researchers investigated various optimization techniques to determine the optimal location and size of DG in order to reduce power loss and improve the voltage profile of the power system. Similarly, VPP optimization can be carried out through optimal placing of stochastic DG units (wind and photovoltaic). Other studies can be performed to select the optimal capacity of a conventional power plant used in collaboration with DG units as well as purchasing energy from the electricity market to supply the required VPP energy.

2) ESEs optimal sizing and siting:

Optimal sizing and sitting of ESEs helps in reducing power loss, improving voltage profiles, and in optimizing the generation of stochastic DGs.

3) Optimal load control scheduling:

The VPP has the authority to control or even interrupt the loads according to their importance in order to optimize its operation. The loads can be divided into three categories:

 Critical loads (Class-A): These loads are the most important loads. They are not interruptible or even controllable. The price of energy supplied to these loads must be the most expensive one but on the other hand a big penalty should be paid by the VPP operator in case of interruption.

 Emergency loads (Class-B): These loads are less important than the critical loads. They are also not interruptible but they are controllable. As mentioned before, the control procedures should be well defined and stated in the contract.

 Normal loads (Class-C): These loads are the least important loads. They are interruptible and controllable. The price of energy supplied to these loads is the least one as a tribute to the possibility of interruption. These normal loads may be further divided into sub-categories based on the allowable duration of interruption and control and the corresponding time (within the peak period or off- peak period). Undoubtedly, as the

allowable period of

interruption/control increases the price of energy decreases.

B. Optimal operation of the VPP

For an existing power system with pre- determined capacities and locations of DG units and ESEs and with certain allowable schedules of load control, the optimal operation could be obtained by optimally determining the generation of DG units, the charge and discharge rate of the ESEs and the amount of energy to be purchased from the electricity market.

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7 C. Optimization of the VPP components

Although rare studies were performed to optimize the structure and operation of the VPP as a one unit (i.e. optimizing all the VPP components and operation simultaneously), several studies were done to optimize each of the VPP components of the VPP individually. The following subsections surveyed the work done to optimize the VPP component (i.e.

DGs, ESEs and controllable loads).

C.1 Optimal sizing and placement of DGs Distributed generators (DGs) are connected to the distribution network for different purposes: improving the voltage

profile, reducing the power loss, enhancing of system reliability and security, improving of power quality (supply continuity), relieving transmission and distribution congestion, reducing health care costs due to improved environment, reducing the system cost, and deferral of new investments.

Optimal location and capacity of DGs plays a pivotal role in gaining the maximum benefits from them. On the other side non-optimal placement or sizing of DGs may cause undesirable effects. Optimal DG sizing and siting problem can be classified according different aspects as presented in Fig. (2).

Fig. (2) Different classifications of DG optimization studies C.1.1 DG optimization according to

methodology

The search space of optimal location and capacity of DGs is roomy; Different optimization methods are used in this field for the sake of power loss minimization, cost reduction, profit maximization and environmental emission reduction. The optimization methods could be analytical [18-23], numerical [24-31] and heuristic [32-46].

A) Analytical methods

Those explanatory technique known as those “2/3 rule” might have been recommended to [18] to ideal establishment of a dg about 2/3 ability of the approaching era in 2/3 of the period of the offering. However, this strategy might not make powerful to no uniformly conveyed loads. Two explanatory techniques for ideal area of a absolute dg to spiral Also coincided energy frameworks were acquainted done [19].

Those To begin with system will be

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8 pertinent on spiral and the second one on coincided force frameworks In view of transport induction matrix, era majority of the data and load appropriation of the framework. To [20] An non iterative explanatory technique In light of those accurate passing equation on minimize control misfortunes those ideal placement for dg Previously, spiral Also coincided frameworks might have been introduced.

Previously, [21], the ideal span and area about dg were characterized Along these lines Likewise with minimize aggregate control misfortunes dependent upon the proportional current infusion method Also without the utilization of impedance or Jacobian matrices to spiral frameworks.

Explanatory expressions to discovering ideal extent Furthermore energy variable for distinctive sorts about DGs were proposed previously, [22]. An enhanced explanatory strategy might have been depicted for [23] for allocating four sorts of various dg units to reduction diminishment done elementary dissemination networks. Moreover, a approach for ideally selecting those ideal dg force variable is Additionally exhibited.

B) Numerical methods

The most common used numerical methods can be summarized as follows.

1) Linear Programming (LP): It was used to solve optimal DG power optimization problem in [24] and [25] for achieving maximum DG penetration and maximum DG energy harvesting, respectively.

2) Nonlinear Programming (NLP): It was presented in [26] for capturing the time variations of multiple renewable sites and demands as well as the effect of innovative control schemes

3) Gradient Search: Gradient search for the optimal sizing of DGs in meshed networks considering fault level constraints was proposed in [27].

4) Sequential Quadratic Programming (SQP): It was applied in [28] to determine the optimal locations and sizes of single and multiple DGs with specified and unspecified power factor.

5) Dynamic Programming (DP): DP was applied to maximize the profit of the DNO by optimal selection of DGs locations while considering light,

medium, and peak load conditions [29].

6) Exhaustive Search: An exhaustive search was proposed for determination of optimal DG size and locations in unbalanced distribution networks considering the changes in the loading conditions due to contingencies in [30] and for heavily over loaded networks [31].

C) Heuristic methods

The most common heuristic methods used can be summarized as follows

1. Genetic Algorithm (GA): It was applied to solve an optimal multiple DGs sizing and siting problem with reliability constraints in [32] where the optimization process is solved by the combination of genetic algorithms (GA) techniques with methods to evaluate DG impacts in system reliability, losses and voltage profile. Authors in [33] proposed a GAbased method for optimal sizing and siting of DGs in radial as well as networked systems for the sake of power loss minimization. A GA was utilized in [34] to solve the optimization problem that maximizes the profit of the system based on nodal pricing for optimally allocating distributed generation for profit, loss reduction, and voltage improvement including voltage rise phenomenon. A GA methodology was implemented to optimally allocate renewable DG units in distribution network to maximize the worth of the connection to the local distribution company as well as the customers connected to the system [35]. A value-based approach, taking into account the benefits and costs of DGs, was developed and solved by a GA that computes the optimal number, type, location, and size of DGs [36].

2. Tabu Search (TS): It was used to obtain the optimal sizing and siting of DG units simultaneously with the optimal placement of reactive power sources in [37]. A stochastic multiple DGs optimal sizes and locations were determined for cost minimization by a combined TS and scatter search [38].

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9 3. Particle Swarm Optimization (PSO):

It was utilized for optimal selection of types, locations and sizes in order to maximize the DG penetration considering standard harmonic limits and protection coordination constraints [39]. A PSO based algorithm was implemented for cost minimization through the optimal sizing and placement of multiple DG units in [40].

4. Ant Colony Optimization: A multiobjective ant colony system algorithm was proposed to derive the optimal recloser and DG placement scheme for radial distribution networks in [41]. A composite reliability index was used as the objective function in the optimization procedure.

5. Artificial Bee Colony (ABC): DG-unit placement and sizing process was performed with ABC algorithm in [42].

6. Harmony Search (HS): The optimal DG location is based on loss sensitivity factors and the optimal DG size is obtained by HS algorithm [43].

7. Cat Swarm Optimization: The authors in [44] presented a cat swarm optimization method for optimal placement and sizing of multiple DGs to achieve higher system reliability in large scale primary distribution networks.

8. Big Bang Big Crunch (BB-BC): A supervised Big Bang Big Crunch optimization method was proposed in [45] and [46] for the optimal sizing and siting of voltage controlled distributed generators for the sake of power loss as well as energy losses minimization.

9. Firefly algorithm (FA): Authors in [47] proposed a firefly based optimization algorithm for the optimal sizing and siting of dispatchable distributed generators for power loss reduction.

VII. CONCLUSION

VPP will be an generally new Also yet an engaging particular idea that necessities careful investigate on encourage its execution. This paper displays a thorough expositive expression survey for the diverse VPP definitions, components, and the connection between these parts.

Moreover, that VPP schema will be demonstrated and the functionalities of the TVPP Also CVPP would stated for exceptional understanding of the VPP particular idea. A overview of the diverse streamlining systems plans with streamline Possibly those VPP structure or those VPP operation examined. The streamlining of the VPP structure included those ideal measuring siting of dg units and the ESEs, the ideal load control, and the ideal estimation gadgets area. The obliged objective functions, Also upgrading calculations to the purpose of VPP ideal operation need aid highlighted.

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