Examples of these trends are the electrification of energy consumption and the increasing volume of distributed generation being connected to the distribution grid.

The relationship between transmission system operators (TSO) and distribution network operators (DSO) is changing. Examples of these trends are the electrification of energy consumption and the increasing volume of distributed generation being connected to the distribution grid. In Europe this subject is highly relevant as pointed out by ENSTO-E (European Network of Transmission System Operators for Electricity) in their paper, Towards smarter grids: Developing TSO and DSO roles and interactions for the benefit of consumers published in March 2015, and ACER (Agency for the Cooperation of Energy Regulators) in their conclusions paper, Energy Regulation: A Bridge to 2025 published in September 2014. ENTSO-E is an association which represents 41 European TSOs and has an objective to promote closer cooperation across Europe’s TSOs to support the implementation of EU energy policy objectives of affordability, sustainability and security of supply. ACER is an agency of the European Union with the overall mission to complement and coordinate the work of national energy regulators at EU level, and to work towards the completion of the single EU energy market for electricity and natural gas. The expected increased interaction between TSOs and DSOs will result in both technical and non-technical challenges.

IEA ISGAN Annex 6 has published a discussion paper in which the current and future cooperation between TSOs and DSOs has been investigated. Six critical grid operation challenges have been identified:
1. Congestion of the transmission-distribution interface
2. Congestion of transmission lines and distribution lines
3. Voltage support (TSO↔DSO)
4. Balancing challenge
5. (Anti-)Islanding, re-synchronization, and black-start
6. Coordinated protection

For each case, country experts provided first-hand information about the status and expected development of TSO-DSO interaction in their respective countries. This resulted in an overview, by country, of the interaction between grid operators and provided input for the discussion about how this interaction could evolve in years to come. Technical aspects, as well as policy aspects, have been taken into account.
The technical solutions required for a closer interaction between TSOs and DSOs are very similar for most of the identified cases, except for the case of islanding & black-start. From a high level viewpoint, grid monitoring has to be implemented, communication between TSO and DSO has to be established and means of communication between the DSO and its flexible customers have to be available. DSOs should also be able to perform (quasi) real time network simulations with input from measurements on the grid.
Such technical requirements should not be underestimated regarding implementation and operational cost, complexity and skills required. These could be a challenge, especially for smaller distribution network operators. Nonetheless, only the distribution grid operator has information about the actual grid configuration and grid loading. This means that even when other entities take up certain roles, for example the role of aggregator, the distribution network operator will always be responsible for monitoring the grid and will need to implement communication solutions to one entity or another.
With the current status of technology, technical requirements for an evolved interaction between TSOs and DSOs can be met. However, several non-technical issues, or points of discussion, have been identified which are closely related to the regulated environment grid operators are working in.

• Maintaining a balance between infrastructure investments and use of flexibility

Flexible demand and generation can be used to support grid operation and avoid infrastructure investments. A minimum use of flexibility will be necessary to avoid over investing, but the impact on the processes and business cases of flexible customers has to be limited. The flexibility available by curtailing renewable energy sources needs to be limited to avoid a high loss of renewable energy.

• The role of markets
Which grid operation challenges should be met by introducing markets and which should be managed only by technical means and appropriate bilateral contracts? It is proposed to use market mechanisms only for the balancing challenge, which is applied today in various countries. Coping with local grid operation challenges such as critical transformer loading, line loading and voltages, is proposed to be managed by the network operators, optimally interacting with each other and using flexible customers when necessary. Because of the local nature of the mentioned grid operation challenges, markets would not work efficiently. Instead, a regulatory framework is required for bilateral contracts between flexible customers and network operators, facilitating the use of flexible generation and demand for grid operation purposes.

• Setting a level playing field for flexibility
When the combined flexibility of customers on the distribution and transmission grid is used, favoring one set of customers at the cost of the other should be avoided. For example, when facing critical line loading on the transmission grid, the use of flexibility of only distribution connected customers would be undesirable. Some mechanism, probably in discussion with the regulator, should be implemented to cope with this.

• The role of regulation
Closely related to the previous statement is the discussion point on how grid operation should evolve:
more regulated, with clearer and stricter roles, or more open, with guaranteed interaction between grid operators and new market players? There is no one size fits all solution but in any case, a clear definition of the roles and responsibilities of all participants in future grid operation will be necessary and will serve as a good start.
A clear policy framework will, in every case, push forward investments in Smart Grid solutions to deal with the discussed challenges that grid operators are facing.
The article is based on a discussion paper published by IEA ISGAN Annex 6.

Smart grid technologies offer new options for integrating variable RE, yet technology is not the only important area of focus—innovative policy, regulation, and business models are needed to incentivize and implement next-generation grid architectures.

This discussion paper explores the intersection of smart grid technology, policy, and regulation from a non-technical point of view, focusing on some specific questions relevant for decision makers:

• What are the challenges of integrating variable RE into power grids?
• What types of smart grid solutions are emerging to integrate variable RE?
• What are good examples from around the world of smart grids aiding in the integration of variable RE?
• What types of policy and regulatory approaches are emerging to support smart grid solutions in relation to RE?

Based on emerging case studies from around the world, this discussion paper concludes that smart grids offer solutions to various challenges associated with variable RE, including
providing additional flexibility, unlocking demand side participation, and deferring more costly grid upgrades.

The case book Spotlight on Smart and Strong Power T&D Infrastructure spotlights a number of projects sharing best practice in how to meet the challenge to develop the electricity network to become stronger and smarter using different approaches.

For example how:

• Existing and new AC power transmission lines can carry more power by the use of smart technologies such as WAMS and Synchrophasors.
• HVDC lines with Voltage Source Converters can be used for interconnectors that also support the existing grid e.g. by avoiding voltage collapse.
•  The use of smart voltage control concepts can increase the hosting capacity for distributed energy resources

Questions relevant for decision makers:

• What are the challenges of integrating variable RE into power grids?
• What types of smart grid solutions are emerging to integrate variable RE?
• What are good examples from around the world of smart grids aiding in the integration of variable RE?
• What types of policy and regulatory approaches are emerging to support smart grid solutions in relation to RE?
• Based on emerging case studies from around the world, this discussion paper concludes that smart grids offer solutions to various challenges associated with variable RE, including providing additional flexibility, unlocking demand side participation, and deferring more costly grid upgrades.

This report is an update of a 2012 ISGAN Annex 4 report entitled “Smart Grid Contributions to Variable Renewable Resource Integration.”

To meet the required objective of this Annex, a program of work is designed and it includes the following three tasks:

• Task 1: Assess Current Network Maturity Model and Update data
• Subtask 1.1: Trial application of two network maturity analysis tools and results discussion
• Subtask 1.2: Development of the questionnaire for the assessment of the level of smartness of transmission and distribution networks

• Task 2: Analyze Current Benefit-Cost Analytical Methodologies and Tools
  • Subtask 2.1: Analyzing benchmark benefit-cost frameworks and tools
  • Subtask 2.2: Model research to overcome limit of current BCA frameworks and tools
• Task 3: Develop Toolkits to Evaluate Benefit-Costs
  • Subtask 3.1: Development of Simplified cost-benefits analysis tool
  • Subtask 3.2: Technical Analysis of current BCA took-kit and Modification of Simplified tool-kit

For Task I, the report goes through several maturity frameworks available, especially those of Software Engineering Institute (SEI) and Katholieke Universiteit Leuven (KUL). The SEI has developed a management tool that can be used to measure the current state of a smart grid project, aiming to help utilities to identify the target and build proper strategies to reach it. The tool, Smart Grid Maturity
Model (SGMM), utilizes a set of surveys called Smart Grid Compass. The drawback of this tool is the undocumented scoring method of the surveys once a result is obtained. Full assistance of an SGMM Navigator is required for the utility to understand and analyze the SGMM output. Meanwhile, the KUL introduce the characteristics, categories and key performance indicators of a smart electricity grid. The previous report also includes own survey methods developed by Annex III, although there has not much of progress after that.

For Task II, an extensive update of the BCA survey has been provided in the previous report. It started with various frameworks related to BCA, which include Frontier Economics and the Smart Grid Forum (SGF) in UK, Smart Grid Investment Model (SGIM) of SGRC, I
MPLAN Model, McKinsey Tool, and general overviews of EPRI’s methodology to BCA and its subsequent developments by DOE and JRC. After that, several BCA applications to country-specific or states cases are summarized. Some of the surveyed countries are Czech Republic, Netherland, Lithuania, Denmark, and USA states. For the comparison purpose, the summary for each case is carried out following some key points: background of the smart grid project, the methodology or toolkits used, the scope of the project (location, period, technologies), the list and definition of benefits and costs, and deliverables (results, recommendations, policy andregulations). The 1st year’s work of Task II can be compared with the previous year’s work in the sense that how EPRI guideline has any impact on the work development of JRC and DOE frameworks, especially for the Smart Grid Computational Tool (SGCT), a BCA toolkit that is developed by US DOE. This report summarizes the findings from the previous works with the focus of selecting the benchmark smart grid tool kit for the development of own ISGAN tool kit for member countries.

For Task III, a simplified cost-benefit analysis tool is being developed taking SGCT of DOE as a benchmark tool kit, based on the previous year report on the development plan of ISGAN member countries’ toolkit. A standalone program based on Object Oriented Programming (OOP) is now being developed replicating, revising and upgrading the currently available excel-based SGCT. As will be discussed, this tool kit has various advantages over other tools: First, this tool is open to public and anyone can take a look inside of the model deep enough to examine the visual basic application modules. JRCEU, McKinsey models were once discussed in Annex III before for any potential utilization for ISGAN member countries’ tool kit. However, members acknowledge the fact that JRC works on excel based format and there seems to be not much difference between JRC’s work and DOE. The difference lies in the fact that JRC never opened up the details of the functionalities and sample calculation of BC in their whole work process. McKinsey software was discussed but it is not open to public. Rather it is a commercial package with no specific advantage over to SGCT of DOE. Detailed engine is not fully explained and the scope of the analysis the tool kit provides does not seem to be very useful (Nigris 2012, Kim 2013). The new tool kit being developed is named for the time being as ‘Replicated Tool Kit’ for convenience. Through the replication process, a lot of details have been identified, which, otherwise, would not have been known to us. Many of the parameters utilized in the process of benefitcalculation may be required to be collected from outside, reflecting the region specific characteristics. Some of the default values provided by SGCT, although they are from USA case (refer to Appendix), may also be useful until those detailed information becomes available for ISGAN member countries even when they don’t have them.

In addition, there a at least 12 smart grid projects currently being conducted in USA (refer to III.2.24), and those projects are starting to produce some detailed information which might be potentially utilized by current SGCT. Not only those advantages, there are many interesting researches being conducted around the world and the work results could be very useful sources of updating this replication effort in the future, once this replication process allows us to identify the pros and cons of the current model. The last chapter of the Expansion of Smart Grid Computational Tool is the wild idea of what could be accomplished in this whole process of simplified own ISGAN tool kit for member countries. Some of the ideas for the tool kit development become clearer as the process of the replication progresses. By the time of the completion of this year’s work, we hope to have a very concrete idea on how to proceed to further develop this current work in the future for the benefit of every member country in ISGAN.