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Why forecasting around distributed generation can drive value for distribution utilities

The rise of distributed generation (DG) continues to change the game for utilities. In fact, thanks in part to DG, nearly half of utility industry executives surveyed by the Accenture Digitally Enabled Grid program feel that the traditional electricity distribution model is no longer fit-for-purpose.

As existing grid hosting capacity is used up, utilities need to invest substantially in grid infrastructure that meets new needs, but many utilities are struggling to figure out how to futureproof their grid and successfully integrate DG. Grid investments, long term by nature, aren’t always adaptable to changing regulatory and market needs and are often inflated.

One of the main reasons for overspending in this case is businesses’ lack of visibility into how much, when and where DG will come on to the grid. This can be tricky to predict since DG penetration doesn’t happen equally across any power grid, but instead is typically concentrated in small areas, as consumers install DG, often based on word of mouth about neighbors’ energy savings.

This results in a few substations with high DG penetration absorbing local hosting capacity and creating bottlenecks that increase the risk of poor power quality for the rest of the grid. Inaccurate DG forecasts make it harder to anticipate these bottlenecks, which fuels most businesses’ reinforcement needs. The result: overall investments become both inefficient and much too high.

The proliferation of distributed generation will only accelerate, so better DG forecasting is a crucial investment that ultimately helps distribution businesses save money – and it turns out the savings are appealing.  For example, research-based geo-modeling by Accenture – as part of our Digitally Enabled Grid (DEG) research program – has found that investing in DG deployment forecasting will more than pay for itself through lower capital expenditure.

The modeling assesses the potential savings in grid reinforcement spend through improved accuracy in distributed generation forecasts in five global markets. It is based on country and state-level data and academic papers; more than 9,000 sets of data from two to five leading distribution businesses in each market; and reviews with nine experts from local transmission and distribution teams;  plus an external grid sector analyst.

It also shows that forecasting accuracy is key to saving money for distribution businesses, and inaccuracies are detrimental to spend. DG deployment typically amplifies the impact on hosting capacity needs, as the few substations where the new DG is focused on the grid already have higher reinforcement needs. These substations become “hot clusters” that drive – or break – grid efficiency

In fact, a 10 percent forecast inaccuracy for DG deployment at the local level can drive forecast inaccuracy of over 20 percent for reinforcement spending. This is not only a challenge, but a huge opportunity for distribution businesses to save money – as a 10 percent improvement in forecast accuracy can result in savings between 12 and 28 percent of grid reinforcement spending for the distribution businesses in the five markets in our study.

Distribution businesses, as with any enterprise, need to achieve more accurate forecasting to take advantage of the prevailing DG trends in electricity distribution models. To be successful, Accenture recommends that distribution businesses focus on:

  • Improving analytics capabilities, local grid modeling and distributed energy resources management systems (DERMS) solutions.
  • Forming partnerships around data to gain insights from potential DG customers, historical trends and other markets.
  • Investing savings achieved in new solutions such as energy storage and demand response to reduce traditional spend.

Taking these steps towards accurate forecasting will help distribution businesses better anticipate bottlenecks on the grid, resolve quality issues before they begin, and ultimately save and invest money more wisely. But success won’t come easy, nor will it come quickly. Due to the rapid pace of the modern energy consumers’ changing needs and appetite for distributed energy resources, including solar, wind and energy storage, distribution businesses need to start upping their game in DG forecasting from here on out.

The author thanks Accenture Research colleague Lasse Kari for his contribution to this article and collaboration on the analysis.

The rise of distributed generation (DG) continues to change the game for utilities. In fact, thanks in part to DG, nearly half of utility industry executives surveyed by the Accenture Digitally Enabled Grid program feel that the traditional electricity distribution model is no longer fit-for-purpose.

As existing grid hosting capacity is used up, utilities need to invest substantially in grid infrastructure that meets new needs, but many utilities are struggling to figure out how to futureproof their grid and successfully integrate DG. Grid investments, long term by nature, aren’t always adaptable to changing regulatory and market needs and are often inflated.

One of the main reasons for overspending in this case is businesses’ lack of visibility into how much, when and where DG will come on to the grid. This can be tricky to predict since DG penetration doesn’t happen equally across any power grid, but instead is typically concentrated in small areas, as consumers install DG, often based on word of mouth about neighbors’ energy savings.

This results in a few substations with high DG penetration absorbing local hosting capacity and creating bottlenecks that increase the risk of poor power quality for the rest of the grid. Inaccurate DG forecasts make it harder to anticipate these bottlenecks, which fuels most businesses’ reinforcement needs. The result: overall investments become both inefficient and much too high.

The proliferation of distributed generation will only accelerate, so better DG forecasting is a crucial investment that ultimately helps distribution businesses save money – and it turns out the savings are appealing.  For example, research-based geo-modeling by Accenture – as part of our Digitally Enabled Grid (DEG) research program – has found that investing in DG deployment forecasting will more than pay for itself through lower capital expenditure.

The modeling assesses the potential savings in grid reinforcement spend through improved accuracy in distributed generation forecasts in five global markets. It is based on country and state-level data and academic papers; more than 9,000 sets of data from two to five leading distribution businesses in each market; and reviews with nine experts from local transmission and distribution teams;  plus an external grid sector analyst.

It also shows that forecasting accuracy is key to saving money for distribution businesses, and inaccuracies are detrimental to spend. DG deployment typically amplifies the impact on hosting capacity needs, as the few substations where the new DG is focused on the grid already have higher reinforcement needs. These substations become “hot clusters” that drive – or break – grid efficiency.

In fact, a 10 percent forecast inaccuracy for DG deployment at the local level can drive forecast inaccuracy of over 20 percent for reinforcement spending. This is not only a challenge, but a huge opportunity for distribution businesses to save money – as a 10 percent improvement in forecast accuracy can result in savings between 12 and 28 percent of grid reinforcement spending for the distribution businesses in the five markets in our study.

Distribution businesses, as with any enterprise, need to achieve more accurate forecasting to take advantage of the prevailing DG trends in electricity distribution models. To be successful, Accenture recommends that distribution businesses focus on:

  • Improving analytics capabilities, local grid modeling and distributed energy resources management systems (DERMS) solutions.
  • Forming partnerships around data to gain insights from potential DG customers, historical trends and other markets.
  • Investing savings achieved in new solutions such as energy storage and demand response to reduce traditional spend.

Taking these steps towards accurate forecasting will help distribution businesses better anticipate bottlenecks on the grid, resolve quality issues before they begin, and ultimately save and invest money more wisely. But success won’t come easy, nor will it come quickly. Due to the rapid pace of the modern energy consumers’ changing needs and appetite for distributed energy resources, including solar, wind and energy storage, distribution businesses need to start upping their game in DG forecasting from here on out.

The author thanks Accenture Research colleague Lasse Kari for his contribution to this article and collaboration on the analysis.

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