Process Framework

for

Smart Grid Implementation

Narayanan Rajagopal, Krishna V. PrasadTata Consultancy Services Limited

Bangalore, India narayanan.rajagopal@tcs.com; krishna.vp@tcs.com

Abstract— Transition to Smart Grid involves tracking the deployment in multiple functional areas of the utility. This is often carried out by periodic reviews of identified metrics for each functional area. The level of development and deployment that has been already realized needs to be assessed at the initial stage and at important milestones to progress along the roadmap. One of the primary requirements to achieve this is to have a comprehensive process framework and business tools to manage various aspects of Smart Grid implementation - the framework should be able to support the Smart Grid implementation from planning stages to final deployment and evaluation. Smart Grid Maturity Model [8] from SEI of CMU provides a comprehensive set of characteristics covering all the domains of Smart Grid deployment. The proposed process framework extends the SGMM by using other tools available to develop Characteristic Evidence Indicators (CEI) [15], [16] – this will improve the objectivity of the assessments resulting in more practical value and leading to deeper insights to drive and accelerate the transition to a Smart Grid. Index Terms—Smart Grid, Smart Grid Maturity Model, Characteristic Evidence Indicators

I. INTRODUCTION

The electric industry is going through a transformation from a centralized, producer-controlled network to one that is less centralized and more consumer-interactive.

The move to a smarter grid leads to changes in the industry’s entire business model and its relationship with all stakeholders, involving and affecting utilities, regulators, energy service providers, technology and automation vendors and customers. Transformation to a smarter grid aims at applying technologies, tools and techniques to make the

electricity grid work far more efficiently, reliably and securely. Managing utility wide Smart Grid deployment requires efficient business tools to assess current state and plan implementation activities to realize the Smart Grid characteristics mentioned above.

II. SMART GRID ENABLING PROCESS TOOLS

A. Overview of SGMM SGMM is a comprehensive model covering the requirements of all the functional domains of a utility involved in Smart Grid implementation. It is a business tool [8], [11] developed by a consortium of utilities for utilities. The model is currently managed by the Software Engineering Institute (SEI) at Carnegie Mellon University (CMU). The model provides a basis for understanding and evaluating the current state of smart grid deployment and capability within an electric utility. It provides a reference for establishing future strategies and work plans. SGMM includes the framework and associated tools that help utilities understand their position and support them through the Smart Grid transition. The model comprises of 6 levels of maturity defined across 8 domains [12], [11]. The domains are

1. Strategy, Management and Regulatory (SMR) 2. Organization Structure (OS) 3. Grid Operations (GO) 4. Work and Asset Management (WAM) 5. Technology (TECH) 6. Customer (CUST) 7. Value Chain Integration (VCI) 8. Societal and Environmental (SE)

The Smart Grid Levels are defined as:

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• Level 0: The default level pertains to utilities not specifically engaged in any of the Smart Grid functions in the particular domain.

• Level 1: There is a Smart Grid Vision in the organization but it is not accepted as a common vision yet or not integrated with the strategy at an enterprise level

• Level 2: Enterprise strategy includes Smart Grid and focused efforts have started

• Level 3: Significant infrastructure to realize Smart Grid have been put in place with some cross functional flow of data and control

• Level 4: Majority of the infrastructure to realize Smart Grid is in place. Integration of processes have been carried out to optimize the operation

• Level 5: Results of Levels 1 through 4, resulting in adaptive and learning environment

B. Other Process Tools

Figure 1: Process Models for Smart Grid

Apart from SGMM, there are a few other tools / models which have been developed with a focus specifically to address a specific phase or a functional area of Smart Grid. Figure 1 shows the models and tools used in arriving at process approach for Smart Grid. These tools are used to define the right set of metrics on specific areas of focus. Some such important tools that have played a role in Smart Grid projects: Smart Grid Score Card This scorecard [2] was developed to support deployment of the Smart Grid. EnerNex has prepared this scorecard as a checklist for GridWise Architecture Council and Smart Grid News. This can be used to assist in the evaluation of products and services for Smart Grid. This scorecard includes portions of EPRI IntelliGrid technology assessment methodology, EPRI IntelliGrid Architecture Application Guidelines, Southern California Edison’s Technology Capability Maturity Methodology, California Energy Commissions (CEC) Public

Interest Energy Research (PIER) program AMI system capability checklist, and GridWise Architecture Council’s Interoperability Framework. The score card is used to select key measures that are particularly relevant to each deployment being reviewed. Smart Grid Project Evaluation Metrics These metrics [3] were prepared by the GridWise Alliance in response to requests from the Department of Energy for suggestions and recommendations for the process of selecting Smart Grid Project. This covers • Key metrics the DOE should use to assess Smart Grid proposals and projects under the Recovery Act. • A process for achieving stakeholder buy-in to the metrics and the weights to be used for each metric in a Balanced Scorecard approach (BSC) to proposal evaluation. • Recommendations on a process to monitor and report on effective use of funding Smart Grid Deployment Plan Evaluation Framework Environmental Defense Fund and Herter Energy Research Solutions have defined this framework [4]. This framework gives guidelines for evaluating the plan for each of Smart Grid program goals and scores them on sections for Vision, Strategy, Roadmap, Metrics, Baseline and Roadmap. Electricity Subsector Cybersecurity Capability Maturity Model - ES-C2M2 The model [5] has been developed by SEI to support the Electricity Subsector Cybersecurity Risk Management Maturity Initiative, a White House initiative led by the Department of Energy (DOE) in partnership with the Department of Homeland Security (DHS) and in collaboration with representatives of asset owners and operators within the electricity subsector. The model was developed to provide descriptive guidance to help organizations develop and improve their cybersecurity capabilities. The model practices have been defined at a high level of abstraction so that they can be interpreted for utilities of various structures, functions, and sizes. The present version of the model does not directly recommend any metrics for cybersecurity, but defines generic and specific practices for the following domains

1. Risk management 2. Asset and Configuration management 3. Identity and Access Management 4. Threat and Vulnerability management 5. Situation Awareness 6. Information Sharing and Communications 7. Event, Incident Response and Continuity of

operation 8. Supply Chain and External Dependencies

management 9. Workforce Management 10. Cybersecurity Program Management

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Other Generic and Specific Models There are other models which have been developed to address some of the common domains across different industries. These models can be used to arrive at some relevant metrics for the Smart Grid program. One such example is the Resilience Maturity Model from CMU [6] which provides some practices relevant to the utility industry. There are certain other models defined with limited scope to address a specific area and phase of Smart Grid implementation. ORMM, Outage Restoration Maturity Model defined by Avineon, Inc. with support from utilities such as Central Hudson Gas & Electric and Cleco Power LLC. North American Electric Reliability Corporation, NERC Standards on Critical Infrastructure Protection provides a cyber security framework for the identification and protection of Critical Cyber Assets to ensure reliable operation of the electricity grid. This provides a good reference of established practices which are useful in arriving at CEIs for security related Smart Grid characteristics.

III. NEED FOR A SMART GRID PROCESS APPROACH

Most models and tools covered in II address either a specific phase or functional area of Smart Grid. One tool / model does not cover all aspects of Smart Grid such as Technical, Operational, Organizational, Infrastructural, & Customer Services aspects. SGMM covers most aspects, but designed as a maturity profiling tool to support Smart Grid strategy & roadmap definition.

Utilities use SGMM to understand where they are in their Smart Grid journey, conduct a gap analysis with respect to their aspired maturity levels and define roadmap. Most utilities also repeat SGMM based evaluation after completion of a phase of their Smart Grid program to refine their strategy and roadmap. Otherwise the Smart Grid program is managed as different projects and work packages, each one addressing a certain area such as AMI, Distribution Automation, and Customer Programs etc. What is normally missing is a unified framework that will serve as a management tool to address all important characteristics needed for overall Smart Grid migration. This framework should provide key metrics that will be collected from individual work packages to monitor the overall progress of the Smart Grid deployment across the utility organization.

The key requirements of the approach are

A strong customized framework to support every stage of the Smart Grid life cycle starting from planning to deployment

Leverage all current strengths in organizational processes for successful Smart Grid deployment

Incorporate best practices from proven process models. These models could be specific to Smart Grid or generic models which have a subset applicable to Smart Grid.

IV. DEVELOPMENT AND CUSTOMIZATION OF THE SMART

GRID PROCESS FRAMEWORK

A. Gap analysis and arriving at key characteristics to be monitored

SGMM defines 175 characteristics across the domains and levels of maturity to carry out the evaluation. The characteristics are evaluated based on the answers to the survey questionnaire. The steps involved in the assessment are

1. Survey completion involving SMEs from utilities and owners of important organizational functions

2. Scoring and benchmarking

3. Analysis of the results

4. Aspirations setting and Gap analysis

The gap analysis step identifies certain key characteristics that are important to be achieved or maintained to meet the aspirations.

The process approach is customized based for a particular utility based on these key characteristics

B. Metrics for the framework – Characteristic Evidence Indicators

In certifications like CMMI [14], the characteristics are linked to a certain part of an organization’s process assets such as a detailed process definition and artifacts serving as their implementation evidence. These are called as Practice Implementation Indicators (PII). The fundamental idea of PIIs is broadly applicable to any practice or activity. It is based on the fact that the execution of an activity or the implementation of a practice will result in “footprints”- evidence that the practice was implemented [14]. A similar approach can be implemented in a utility as part of the process approach. Once an organization has an understanding of how its Smart Grid processes relate to the SGMM characteristics, the stage is set for capturing the objective evidence of implementation. Similar to PIIs used in the CMMI assessments, we can define Characteristic Evidence Indicators, CEIs for the key characteristics defined in the Smart Grid Maturity model. One or more Characteristics can be mapped to a CEI.

CEIs will have two components or dimensions:

• Objective evidence component • Implementation evidence type component.

The objective evidence component refers to an evidence of the characteristic’s existence. The characteristic implementation evidence type component deals with the significance of the objective evidence in relation to the implementation. The example below illustrates the CEI definition: An overall process definition for the utility covering all its areas of operations is generally available in documented

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form. We can map a reference in the utility’s operational process description as an Objective Evidence of a Smart Grid Characteristic. Utilities can have established artifacts generated as part of most processes. These can serve as Implementation Evidence. If we choose Level 2, Grid Operations Domain, “Implementing advanced outage restoration schemes” is one of the characteristics. The Objective Evidence for this could be the functional description of Outage Restoration. This merely shows that Outage Restoration is defined in the process. The Implementation Evidence for this could be metrics extracted from System generated reports, outage reports showing effectiveness of outage restoration listing the

number of consumers affected and restored during major outages.

C. Defining the right CEIs An important step in development of the framework is to identify the right CEIs for the key characteristics that are to be monitored regularly. The progress in each area can be tracked by the improvement in the CEIs collected at periodic intervals through monthly reports, on line updates etc. This approach uses other industry proven process models also to identify the right CEIs for a characteristic. Table 1 Example CEIs shows some of the SGMM characteristics with corresponding CEIs derived from ES-C2M2.

Table 1 Example CEIs

Characteristic Objective Evidence Implementation Evidence

Changes to Enterprise Architecture enabling Smart Grid – (TECH, Level 2)

C2M2, Asset domain, Change and Configuration management Practices

OT, IT landscape mapping to business functions; Change control records

Performance, trend analysis, and event audit data for cyber and physical systems. (WAM, Level 3)

Physical asset operation and condition monitoring, Monitoring threat and vulnerability management practices, C2M2

WAM reports Access violation records

Safety and security (physical and cyber) requirements are considered in all grid operations initiatives. ( GO, Level -1)

Information sharing practices, C2M2 – Information and Communications domain

Test records Detailing security requirements in RFP documents

In a similar manner, CEIs can be defined for each key

SGMM characteristic that requires monitoring at regular intervals. Smart Grid process approach and the reference models used to arrive at the overall framework are shown in Figure 2. The CEIs defined can be used at various stages of the Smart Grid life cycle ensuring implementation and alignment to the defined roadmap. The steps involved in the process are

1. Use of SGMM as the basis for maturity profiling and setting aspiration levels (using benchmarked SGMM results)

2. Gap analysis and identifying key differentiating characteristics that require continuous monitoring

3. Definition of Characteristic Evidence Indicators (CEIs) for key SGMM Characteristics – based on

Figure 2: Smart Grid Process Framework

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4. recommended metrics from RMM, C2M2, SG Score card, and other models / practices

5. Using CEIs to track / monitor Smart Grid program’s progress

D. Smart Grid Process Framework Benefits The CEI based framework benefits the utility in

Serving as a tool to achieve Smart Grid Vision aligned to business strategies and customers

Enabling objective evaluation of – Technologies – Solutions – Organization

Helping to arrive at a roadmap addressing – PoCs and Pilots and their adaptation to

different operational regions – Interoperability – Scalability

Providing a path to converge discrete Smart Grid initiatives in different domains (Customer, Grid operation etc.) with a unified framework and facilitate effective deployment

Providing metrics for tracking and progress benchmarking

V. SUMMARY

Process tools available for managing transformation to a smarter grid have been studied. A unified approach to manage the complete life cycle of Smart Grid implementation has been proposed. A framework leveraging proven process tools in the industry and best practices has been described. The approach will support effective implementation of Smart Grid with a focus to measure and improve the program metrics on efficiency, reliability and security. The framework can be customized for each utility with their own set of CEIs defining the metrics for each of the domains. The paper describes the steps involved in customization.

While SGMM surveys are good means of starting the journey, the CEI based approach will be needed for a well articulated journey through the maturity levels. These will help institutionalization of the Smart Grid activities to ensure that in each domain, the processes followed are effective, repeatable and lasting.

REFERENCES

Technical Reports: [1] “Interim Smart Grid Road Map”, April 2009, EPRI [2] “Smart Grid Score Card”, Jan 2008, www.smartgridnews.com [3] “Smart Grid Project Evaluation Metrics”, February 2009, KEMA [4] “Evaluation Framework for Smart Grid Deployment Plans”, June,2011,

Environmental Defense Fund [5] “Electricity Subsector Cybersecurity Capability Maturity Model”, May

2012, Software Engineering Institute, Carnegie Mellon University [6] Richard A. Caralli, Julia H. Allen, David W. White “The CERT

resilience management model : a maturity model for managing operational resilience” 2011, Addison Wesley

[7] “The Age of the Smart Grid is Here”, SEI, IBM, World Energy Council, March 30, 2009

[8] “Smart Grid Maturity Model”, Software Engineering Institute, Carnegie Mellon University, www.sei.cmu.edu/smartgrid

[9] “The Smart Grid: An Introduction” , U.S D.O.E [10] “SGMM Overview”, v 1.2, Software Engineering Institute, Carnegie

Mellon University [11] David White, SEI, “Empower your Smart Grid Transformation”, SEI

Webinar, March, 2011 [12] “SGMM Document Definition”, Software Engineering Institute,

Carnegie Mellon University [13] “SGMM Assessment Survey”, 1.2, Software Engineering Institute,

Carnegie Mellon University [14] “Standard CMMI Appraisal Method for Process Improvement”

(SCAMPI) A, Ver 1.2, Method Definition Document

Papers from Conference Proceedings (Published): [15] Narayanan R and Krishna VP, "Extending SGMM Based Approach for

Smart Grid Implementation," in Proc. 2011 International Conference on Roadmap for Smart Grid

[16] Mehul Shah, Ranjeet Vaishnav, Narayanan Rajagopal, Krishna V. Prasad, “Delivering Power system decision support tools over the web”, in Proc.2010 IEEE-PES General Meeting.

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