ARCHITECTING THE SMART GRID AS A HOLARCHY

Ebisa Negeri and Nico Baken

Delft University of Technology, Delft, The Netherlands

Keywords: Smart Grid, Architecture, Prosumer.

Abstract: The ever increasing concerns for energy security, energy efficiency, and sustainable energy is offering

various challenges for the power grid. With increasing penetration of the distributed generations, the

electricity power system is facing an era of prosumerization, whereby all stakeholders can autonomously

produce, consume, import and/or export power. The classical power grid with top-down organization and

control does not fit this dynamics, hence reorganizing the rather old architecture of the system is

indispensable. In this paper, we propose a generic architecture of the smart grid that fits the new scenario

based on the concepts of holons. The proposed architecture of the system is composed of autonomous

prosumers that are organized bottom-up in a recursive manner involving various aggregation layers,

forming a dynamically reconfigurable system. A corresponding control architecture that employs a holonic

approach to simultaneously capture the autonomy of the prosumers, the recursion and the dynamic

reconfiguration of the proposed system is also proposed. We extend our work by proposing a service

oriented architecture (SOA) framework to support our control architecture.

1 INTRODUCTION

With the increasing need of enhancing the share of

renewable energy, energy security and efficiency,

distributed sources are increasingly penetrating into

the electricity grid. Consequently, the lower end

points of the grid are “taking power into their own

hands” as they own distributed sources. For instance,

households are evolving from passive consumers to

active prosumers that can generate, store, import or

export power. According to the European

parliament, all new buildings to be built after 2019

will have to produce their own energy on site

(

European Parliament (2009)). The electric vehicles

and the future fuel cell vehicles could become

mobile power storage and generation elements of the

grid. These trends imply that the power system is

facing an era of prosumerization, whereby all

stakeholders can autonomously produce, consume,

import and/or export power on the grid. In this work,

prosumer is a general term that refers to a system

that autonomously manages its resources and is

capable of bidirectionally exchanging power with its

environment.

While prosumers autonomously manage their

own resources, they can join other prosumers whose

profile “complement” their own to exchange power

with them. Further, a group of such prosumers might

constitute a larger prosumer cluster to gain the

power of the collective and bargain with the rest of

the grid as a unit. Yet, a group of prosumer clusters

can form a bigger prosumer cluster to benefit the

power of the bigger collective. In this era of

prosumerization, it seems that the future power

system builds bottom-up. Thus, restructuring the

rather old centralized top-down organized power

system is crucial to accommodate the dynamics.

In this paper, we propose a generic architecture

of the smart grid and its corresponding control

architecture that can efficiently manage the era of

prosumerization. Our proposed architecture employs

holonic approach to organize the system bottom-up

by aggregating the prosumers at different

aggregation layers. The proposed architecture

incorporates dynamic reconfiguration capability

allowing the system to adapt to changes. We have

also proposed a control architecture that well suits

the envisioned system. Further, a service-oriented

architecture (SOA) bases framework that models the

control application of our proposed system is

presented.

The rest of this paper is organized as follows.

After we present the related background of the topic

in Section 2, we present our proposed architecture of

the system in Section 3. Our holonic control

Negeri E. and Baken N..

ARCHITECTING THE SMART GRID AS A HOLARCHY.

DOI: 10.5220/0003952500730078

In Proceedings of the 1st International Conference on Smart Grids and Green IT Systems (SMARTGREENS-2012), pages 73-78

ISBN: 978-989-8565-09-9

 2012 SCITEPRESS (Science and Technology Publications, Lda.)

architecture and its SOA based model are present in

Section 4. In Section 5, we describe the conditions

required to realize the proposed architecture. Finally,

we present the concluding remarks of the paper in

Section 6.

2 BACKGROUND

2.1 Recent Concepts in Power System

Recently, various new concepts have been proposed

to manage the new trends in the power system. The

Flexible, Reliable, and Intelligent Electrical eNergy

Delivery System (FRIENDS) (Nara and Hasegawa,

1997) was proposed aiming to create a new

framework for power system that realizes flexible

reconfiguration of the system using switching

operation, multiple menu service to allow customers

to select the quality of power, and demand side

management. The concept of Virtual Power Plants

(VPP) was introduced as a cluster of distributed

power sources which are collectively managed

(Dielmann and van der Velden, 2003). The

Microgrid concept (Hatziargyriou et al., 2006) was

suggested as a low voltage (LV) distribution system

comprising of distributed sources, controlled loads

and storage systems that are coordinated to achieve a

controllable operation either as an island or

connected to the medium voltage (MV) grid.

Another concept is the autonomous network

(AN), which is a part of the system but its behavior

is more or less independent from the rest (Provoost

et al., 2004). AN differs from the microgrid because

AN is larger in size and complexity, as well as its

aim is primarily optimizing its normal operation. In

(van Overbeeke and Roberts, 2002), the active

networks concept is presented where the network is

subdivided into cells that are self managing, but not

necessarily self supplying. This concept involves

interconnection between the cells that provides more

than one power flow paths, and allows rerouting to

avoid congestion and to isolate faults. Further,

system services are traded along the connections

between the cells.

The smart grid concept represents the overall

picture of the future power network that is supported

by intelligent distributed devices and communication

technologies. In (Tsoukalas and Gao, 2008), the

smart grid is modeled as an energy internet

comprising of local area grids (LAGs), that are

demand-based autonomous entities consisting of a

convenient mixture of different customers. The

LAGs interact with the system using their intelligent

agents. The Future Renewable Electric Energy

Delivery and Management (FREEDM) (Huang et

al., 2011) have been proposed as a power

distribution system that interfaces with residential

customers and industry customers having distributed

renewable energy sources and distributed storage

devices. The key technology features of the system

are the plug-and-play interface, energy router, and

open-standard based operating system. The proposed

system relies on a flat and distributed management

architecture.

A market based control concept, named

PowerMatcher, is suggested for supply and demand

matching in electricity networks with large

penetration of distributed sources (Kok et al., 2005).

In the PowerMatcher, each device uses its agent to

buy or sell power in the electronic market that is

implemented in a distributed manner using a tree

structure. The device agents can also be clustered to

form intermediated aggregator agents. In (Grijalva

and Tariq, 2011), it is argued that each component of

the power system could be considered as a

prosumer, based on which they model the electricity

power system as a flat system composed of

prosumers of different scales. Correspondingly, they

propose a totally flat control architecture of the

system.

Although their scale, complexity and intelligence

varies, all the above concepts and technologies have

their own contributions in managing the distributed

sources. One concept could be more applicable in

some settings than the other, and vice versa.

Moreover, some of the concepts could be combined

since they complement each other. The smart grid

could be an umbrella to appropriately combine the

concepts, thereby achieve a heterogeneous and

intelligent power system that delivers its

expectations. For instance, the FRIENDS, VPP,

microgrid, AN, and active networks could form sub-

networks of the smart grid, while FREEDM

provides the power delivery infrastructure

supporting the sub-networks and PowerMatcher

delivers the transaction services.

In this work, we endeavor to propose a generic

architecture of the smart grid that tends to converge

the various proposed concepts. Our proposed

architecture appropriately accommodates the

heterogeneous composition of the smart grid as well

as provides flexibility, intelligence and autonomy at

all level of the grid as required.

2.2 Holons and Holarchy

The word holon was coined by (Koestler, 1990), and

SMARTGREENS2012-1stInternationalConferenceonSmartGridsandGreenITSystems

it refers to a logical entity that is both a whole and a

part. For example, a cell in your body is a holon

because it is a distinct living entity that has a distinct

cell wall defining its interface with the rest of the

world. However, a cell is composed of smaller

holons such as nucleus and chromosome that are

also separate entities. Yet, a group of cell holons

together form a higher aggregation layer tissue

holon, a group of tissue holons form an organ holon,

and so on.

A holon is basically autonomous, cooperative

and recursive. Holons exhibit self-similar recursive

structure and are organized in various aggregation

layers to form a complete holarchy as shown in

Figure 1. In a holarchy, each holon can function

autonomously thereby enabling formation of a

distributed system. While functioning

autonomously, a holon can cooperate with other

holons in the holarchy to achieve mutual goals. In a

dynamic environment, holons can also be

dynamically reorganized thereby making the

holarchy more robust to changes adapting itself to its

environment. Recently, there is a growing interest in

the holonic approach in the development of various

systems (e.g. (Moghadam and Mozayani, 2011) and

(Lai and Qin, 2010)).

Figure 1: A Holarchy: organization of holons.

3 THE ENVISIONED SMART

GRID

We model the smart grid as a system formed from

interconnection of prosumers of different types and

complexities. A prosumer could be as simple as a

household that autonomously manages its resources

(appliances, distributed sources, and/or storage

systems). Other systems such as VPP, microgrid,

AN, etc. can also be regarded as prosumers. A

prosumer can have a sub-part that is also a prosumer

in itself. Our proposed architecture reflects a

paradigm shift from a centralized top-down system

to a decentralized bottom-up one where prosumers

recursively join in different aggregation layers to

form the whole power system. The new scenario

entails self-similarity because the prosumers exhibit

the autonomy to produce, consume, import, and/or

export power, irrespective of their aggregation level.

The autonomy, aggregation into layers,

recursiveness (self-similarity), and dynamic

adaptation of a holonic system make it well suited to

model the envisioned smart grid. We model each

prosumer as a holon and the entire power system as

a holarchy. The new power system holarchy has the

following major features.

3.1 Autonomy/Self-Management

The prosumer holons autonomously manage their

own resources and optimize their utilization.

Further, a prosumer holon can choose to be part of a

bigger prosumer holon and exchange power with its

surrounding, or operate as a self-supplying islanded

unit. The autonomy of the prosumer holons aids a

distributed control capability of the system that

would be otherwise very difficult to control

centrally. Autonomy might also increase the

consciousness of the prosumer holon, making it

more cautious about its consumption, which could

increase energy efficiency.

3.2 Bottom-up Organization

The prosumer holons (such as households) at a

lower aggregation level may be self-organized to

constitute a bigger prosumer holon (such as a

neighbourhood energy community) to locally

exchange power with each other and to gain a

collective bargaining power with the rest of the grid.

For the same reasons, the newly formed prosumer

holon can still be connected to its peers in a network

in the next higher aggregation layer to form yet a

bigger prosumer holon. Further bottom-up grouping

of such holons in networks-of-networks continues

recursively in higher aggregation levels and

eventually constitutes the overall holarchy of the

smart grid as shown in Figure 2. Simon (Simon,

1962) has shown that this recursive clustering at

different aggregation layers is inherent behaviour of

all complex systems. The smaller holons that form a

bigger holon are referred to as sub-holons of the

bigger holon on the next aggregation layer, whereas,

the bigger holon on the next aggregation layer that

contains a holon is referred to as its super-holon.

The bottom-up organization at different aggregation

layers provides efficient structure that abstracts and

simplifies the coordination of the system. Moreover,

the aggregation of prosumer holons into super-

holons might increase the reliability of the collective

as the profiles of the individual holons might

complement each other. Further, the local power

ARCHITECTINGTHESMARTGRIDASAHOLARCHY

exchanges between the prosumer holons reduces

both the transportation losses and the costly

investment costs to upgrade the transmission

capacity to meet the ever increasing demands.

Figure 2: Bottom-up organization of prosumer holons to

form the power holarchy.

3.3 Dynamic Reconfiguration

Over an interval of time, a prosumer holon may be

in the state of either self sufficiency, surplus

production, or excess demands. Thus, the prosumer

holons in our envisioned system can leave one

super-holon to join another one over a period of time

to look for a set of holons that complement their

profiles, thereby optimizing their resource

utilization. It has been shown in (Erol-kantarci et al.,

2011) that a set of microgrids could be dynamically

reorganized during a day into clusters according to

their profiles to optimize the utilization of their

renewable resources. Moreover, prosumer holons

can join a super-holon for some time intervals

during a day and operate in island mode at other

intervals, for example in response to potential faults.

Such flexibilities lead to a dynamic reconfiguration

of the smart grid holarchy over a period of time.

3.4 Intelligence and Communication

A prosumer holon needs to coordinate its

components, as well as coordinate itself with its

surrounding to optimize utilization of resources and

to ensure system stability. This coordination

involves large information flows and require

intelligent information processing units that

constitute the “nerve system” of the “organic” power

system. Accordingly, each prosumer holon requires

communication capabilities and an intelligent device

that makes decisions based on the gathered

information.

4 CONTROL ARCHITECTURE

OF THE ENVISIONED SMART

GRID

Given the nature of the envisioned power system, its

control architecture needs to exhibit the following

properties: 1) sufficient autonomy of each prosumer

holon to manage its own resources; 2) recursive

structure where a prosumer is composed of smaller

prosumers at the lower aggregation layer, and at the

same time be part of a larger prosumer holon at a

higher aggregation layer; 3) layered structure to

facilitate coordination between different aggregation

layers; 4) dynamic reconfiguration to runtime

topology change. The holonic architecture, as

explained before, nicely fits the envisioned system

because it combines distributed control and a layered

coordination structure. It also provides dynamic

reconfiguration and recursive structure that best

model the system.

4.1 Holonic Control Architecture

Our holonic control architecture maintains the

proposed structure in the envisioned power system.

In the control domain, a control-holon represents the

control system of a prosumer holon. Thus, holonic

control units will be recursively organized in a

bottom-up structure to form a complete control-

holarchy of the smart grid. When the prosumer

holon has prosumer sub-holons, its control-holon is

also composed of the corresponding control-sub-

holons (i.e. control systems of sub-holons). The

control-sub-holons can interact with each other, as

well as with their control-holon.

Figure 3 depicts the holonic control architecture.

As shown in the figure, the control-holon could

represent its members in the next aggregation layer

as a member of a control-super-holon. The control

mechanism involves mutual negotiations between

the control-holon and the control-sub-holons. As

part of the negotiations, a control-sub-holon might

agree to submit part of its autonomy to the control-

holon. Once agreements are reached, the control-

holon is responsible to enforce the terms and

conditions. The power transactions and provision of

system services are based on mutual negotiations,

and the control-holon can play a coordinating role to

maintain the desired overall state of the system.

Coordination could be achieved in various ways

such as by providing incentives or through local

electronic markets within the holon.

SMARTGREENS2012-1stInternationalConferenceonSmartGridsandGreenITSystems

Figure 3: Control architecture of a prosumer holon.

While the prosumer holons are organized in a

holarchy as in Figure 2, the control-holon

investigates the situations in the external

environment and presents the opportunities and

threats to its control-sub-holons, and corresponding

decisions are made through negotiations. The

control-sub-holons also need to translate the

negotiations to their corresponding control-sub-

holons (if any), and the process continues

recursively in the holarchy. In this manner, the

control-holons at various aggregation layers will be

conscious about the dynamics in the system and

make corresponding optimal decisions through

negotiations.

In the holonic control architecture, the

aggregation level of a control-holon does not

indicate its level of influence. The level of influence

of control-holons are decided through contracts that

involve negotiations. Accordingly, up on joining a

super-holon a control-sub-holon might choose to

retain its full autonomy, or submit its autonomy to

the control-holon of its super-holon partly or fully.

4.2 Service Framework of the Holonic

Control

The proposed control paradigm involves a large

number of autonomous actors that interact with each

other and exchange power. Such a scenario poses

various challenges relater to interoperability,

scalability, discovery, real-time decision making and

others that are best addressed by the Service

Oriented Architecture (SOA) (Pagani and Aiello,

2011). SOA is an architecture that models an

application as a set of loosely coupled, flexible,

reusable and adaptable functional units called

services, whereby the services are interrelated

through well-defined interfaces and contracts. The

main advantages of SOA include platform-

independence of the interfaces that aids

interoperability, the flexibility and reusability of the

services, and its easy adaptation to evolutionary

changes in the application. While SOA can be

implemented using different technologies, the web

services is the most popular one because of the wide

acceptance of its standards. Web service technology

exposes web services, which are sets of operations,

on the web; thereby allowing high degree of

integration among them.

Our proposed service framework of the holonic

control is composed of four major services.

1. Database service - srvDatabase: This web

service takes care of storing, accessing,

updating and maintaining the relevant data of

the prosumer holon. The data could include

topology information, parameter

specifications of the grid and the components,

history of production, demand and storage

profiles, etc.

2. State Evaluation Service -

srvStateEvaluation: This web service takes

care of getting information about the real-

time state of the holon and its environment,

forecasting the profiles over the next

interval(s) of time, and setting appropriate

goals depending on the current state and the

forecast.

3. Optimization Service - srvOptimization: This

service ensures optimal utilization of

resources. This could involve devising a

coordination mechanism to be proposed to

sub-holons to achieve a desirable profile, and

finding optimal scheduling of the resources,

such as power sources, storage systems, and

appliances.

4. Transaction Service - srvTransaction: This

service contains operations that support

power transactions between prosumer holons.

For instance, a prosumer holon that wants to

import power can publish its demand, while it

can notify others about its interest to export

its surplus production. Through such

operations the prosumer holons can negotiate

and exchange electric power with each other.

5. Stability Service - srvStability: This service is

a set of operations that guard the stability of

the prosumer holon. It must make sure that

the active and reactive power are balanced,

the power quality is maintained, and faults

are safely recovered.

5 CONCLUSIONS AND

DISCUSSIONS

The electricity power system is facing an era of

ARCHITECTINGTHESMARTGRIDASAHOLARCHY

prosumerization, whereby any stakeholder can

autonomously produce, consume, import and/or

export power. Since the classical centralized and

top-down organized power system cannot efficiently

and sustainably handle the new scenario, a new

optimal way of structuring the system is essential.

We have presented an optimal alternative

architecture using the concepts of holons and

holarchy. Our architecture organizes the system

bottom-up from autonomous prosumers that are

recursively clustered at various aggregation layers

allowing dynamic reconfiguration. The proposed

architecture is generic allowing it to accommodate

the heterogeneous composition of the power grid. A

corresponding control architecture is also presented

together with a service oriented architecture (SOA)

based framework that models the holonic control

architecture. Currently, we are working on

formulating the details of the proposed holonic

control architecture, aiming at defining the relevant

control functions and designing the appropriate

protocols for their interaction with each other as well

as with their environment.

The proposed architecture is in line with the

trends in prosumerization of the power system.

Moreover, it is generic and is capable of

accommodating the potentially heterogeneous types

of networks in the smart grid. Its implementation

poses several requirements though. The physical

infrastructures need to be enhanced to accommodate

the required level of flexibility. Intelligent solutions

are required to enable bidirectional power flows, to

easily connect and island prosumers, and to maintain

system stability under these circumstances. Further,

the prosumer holons need intelligent units that can

exchange information across communication

infrastructures, process information and make

decisions.

Further, modelling the behaviours of the

autonomous prosumers is essential to propose

coordination mechanisms for optimal system-wide

behaviour. On the other hand, an in-depth

investigation of the relevant legal issues is essential

to design relevant regulations that accommodate the

envisioned system.

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SMARTGREENS2012-1stInternationalConferenceonSmartGridsandGreenITSystems