This article was written by James Stirton, Senior Solutions Consultant, EMEA, Allegro Development.
The future has already arrived for utilities companies. But it’s not evenly distributed yet. Emerging technologies and changing consumer habits are forcing utilities to completely re-visit their century-old business models – and the systems that enable them.
The cost of solar continues to drop while consumer demand for renewables continues to rise. Highly responsive urban microgrids that optimize usage are gaining adoption. Tesla’s PowerWall product promises to make in-home energy storage a reality within this decade.
Those changes are pushing utilities towards a more distributed model of generation that all but guarantees even more disruption – along with reduced income from electricity sales as more and more people generate their own.
With all the embedded systems being installed in homes and businesses you’d think that technology would also make predicting and pricing consumption in this new environment easier.
The truth is that all that data being sent back to the IT mothership is too much for many legacy IT systems to analyse quickly. The business insights and improved visibility of risks that big data promises are needed now more than ever, particularly to inform the trading decisions utility companies make about their supply chains.
Because if changing market dynamics weren’t enough risk to manage, you now have to add the constant worry of extreme weather. The last few years have shown it to be a near constant that lands without precedent or warning, crashing generation capacity when a polar vortex or heatwave descends, or dampening demand during an extended El Nino winter.
How can utilities better understand the future impact of weather on both power demand and supply, manage a multiplicity of distributed generation sources, take the steps toward a distributed generation model with minimum pain and disruption, plan the availability of fuel, and deal with associated price swings?
It’s a big ask, but the answer may well lie in – yes – more technology. But this time in systems that can deal with torrents of data to manage unpredictability and risk.
Consumption drops yet demand goes up
Global demand for power is set to grow by about 85 percent between now and 2040 as living standards rise, economies grow and the electrification of society (see mobile devices, the internet of things, the rise of wearables) continues.
And yet - demand for fuel to produce that power is only projected to rise by 50 percent. For that blame more and more customer-owned generation and improved energy efficiency in generation and transmission. Flat or negative growth to utility revenues has been the result.
If utility companies are going to wring profits from a fast-evolving and shape-shifting marketplace, they have to find new ways to optimize their resources and reduce costs. One way to do that is to invest more in systems that provide intelligence for short-term planning issues like unit commitment and bidding.
It’s easy to say but harder to do. As an asset-intensive industry with major capital commitments, utility companies have always emphasised long-term planning - often conducted separately from short-term planning, and where both tend to be done in isolation from the trading desk. It’s a siloed approach that blurs awareness of the market risks that arise when planning for future portfolio enhancements or resource needs.
Significant cultural change may be needed alongside technological changes.
Regulation risks
Regulatory changes are another area of extreme risk for utilities. The complexity of reporting, markets, transactions, contracts and accounting rules generate special challenges in complying with the ambiguities of regimes such as Dodd-Frank, REMIT, EMIR, MiFID II and others.
Without accurate internal audits and proper governance, utility companies involved in energy trading can be exposed to significant risk. Forward-looking traders, meanwhile, are seeing that better visibility into the non-standard, structured deals in their portfolios could create new opportunities.
Further complicating matters for utilities are the ever-increasing pressures from global environmental agencies to curb and manage their carbon emissions. Proposals, such as the US Environmental Protection Agency’s comprehensive Clean Power Plan, are expected to affect carbon-fuelled generating plants around the world. Likewise, in Europe, the 7th Environment Action Programme outlines sustainability and biodiversity objectives based on low-carbon growth.
Not only will utility companies need to manage the physical aspects of these new regulations, they will need to facilitate the complex process of dealing with emissions credits and potential new cap-and-trade markets.
Change – and risk – management
With so many factors disrupting their business models, utility companies need to invest in technology that can mitigate the risks they face. Management needs better access to information and tools for decision making, not only for executives, but also for personnel engaged in planning and trading. Without a commodity management platform, they may not be able to accurately dispatch generation, manage contract terms or pass regulatory scrutiny over feedstock purchases.
The assumption has always been that IT will provide access to the right insight. However, the industry has grown up with a dog’s breakfast of homegrown and off-the-shelf energy trading and Risk Management
Risk Management
One of the most common terms utilized by brokers, risk management refers to the practice of identifying potential risks in advance. Most commonly, this also involves the analysis of risk and the undertaking of precautionary steps to both mitigate and prevent for such risk.Such efforts are essential for brokers and venues in the finance industry, given the potential for fallout in the face of unforeseen events or crises. Given a more tightly regulated environment across nearly every asset class,
One of the most common terms utilized by brokers, risk management refers to the practice of identifying potential risks in advance. Most commonly, this also involves the analysis of risk and the undertaking of precautionary steps to both mitigate and prevent for such risk.Such efforts are essential for brokers and venues in the finance industry, given the potential for fallout in the face of unforeseen events or crises. Given a more tightly regulated environment across nearly every asset class,
Read this Term (ETRM) applications that may not be ready to meet the needs of today's power and utility markets. Spreadsheet-based applications, in particular, typically need a high level of expensive customization each time a new type of generation or fuel is added.
A utility commodity management system should at minimum feature robust Analytics
Analytics
Analytics may be defined as the detection, analysis, and relay of consequential patterns in data. Analytics also seeks to explain or accurately reflect the relationship between data and effective decision-making. In the trading space, analytics are applied in a predictive manner in an attempt to forecast the price more accurately. This predictive model of analytics generally involves the analysis of historical price patterns that are used in an attempt to determine certain price outcomes. Analy
Analytics may be defined as the detection, analysis, and relay of consequential patterns in data. Analytics also seeks to explain or accurately reflect the relationship between data and effective decision-making. In the trading space, analytics are applied in a predictive manner in an attempt to forecast the price more accurately. This predictive model of analytics generally involves the analysis of historical price patterns that are used in an attempt to determine certain price outcomes. Analy
Read this Term, such as forecasting, simulation and optimization; standardized models and forecasts to ensure consistency in analysis, with the ability to trace back model results and assess risk across power and gas portfolios; forecasting, simulation and optimization analytics integrated with energy trading and risk management applications; and simulation of market, outage and weather scenarios fast enough to handle trading requirements.
Conclusion
Before you begin evaluating solution providers, understand your company's strategy for hedging risk and complying with regulations in detail. Take an inventory of your most used resource analytics, but also consult traders, risk managers and planners to understand what they need to be successful.
The best approach to reduce the total cost of supporting legacy systems or spreadsheets is to invest in a suite of applications that integrate energy trading and risk management with analytics. This approach will also ensure consistency of information across the organization, which is essential if utilities are going to return to profitability and growth.
This article was written by James Stirton, Senior Solutions Consultant, EMEA, Allegro Development.
The future has already arrived for utilities companies. But it’s not evenly distributed yet. Emerging technologies and changing consumer habits are forcing utilities to completely re-visit their century-old business models – and the systems that enable them.
The cost of solar continues to drop while consumer demand for renewables continues to rise. Highly responsive urban microgrids that optimize usage are gaining adoption. Tesla’s PowerWall product promises to make in-home energy storage a reality within this decade.
Those changes are pushing utilities towards a more distributed model of generation that all but guarantees even more disruption – along with reduced income from electricity sales as more and more people generate their own.
With all the embedded systems being installed in homes and businesses you’d think that technology would also make predicting and pricing consumption in this new environment easier.
The truth is that all that data being sent back to the IT mothership is too much for many legacy IT systems to analyse quickly. The business insights and improved visibility of risks that big data promises are needed now more than ever, particularly to inform the trading decisions utility companies make about their supply chains.
Because if changing market dynamics weren’t enough risk to manage, you now have to add the constant worry of extreme weather. The last few years have shown it to be a near constant that lands without precedent or warning, crashing generation capacity when a polar vortex or heatwave descends, or dampening demand during an extended El Nino winter.
How can utilities better understand the future impact of weather on both power demand and supply, manage a multiplicity of distributed generation sources, take the steps toward a distributed generation model with minimum pain and disruption, plan the availability of fuel, and deal with associated price swings?
It’s a big ask, but the answer may well lie in – yes – more technology. But this time in systems that can deal with torrents of data to manage unpredictability and risk.
Consumption drops yet demand goes up
Global demand for power is set to grow by about 85 percent between now and 2040 as living standards rise, economies grow and the electrification of society (see mobile devices, the internet of things, the rise of wearables) continues.
And yet - demand for fuel to produce that power is only projected to rise by 50 percent. For that blame more and more customer-owned generation and improved energy efficiency in generation and transmission. Flat or negative growth to utility revenues has been the result.
If utility companies are going to wring profits from a fast-evolving and shape-shifting marketplace, they have to find new ways to optimize their resources and reduce costs. One way to do that is to invest more in systems that provide intelligence for short-term planning issues like unit commitment and bidding.
It’s easy to say but harder to do. As an asset-intensive industry with major capital commitments, utility companies have always emphasised long-term planning - often conducted separately from short-term planning, and where both tend to be done in isolation from the trading desk. It’s a siloed approach that blurs awareness of the market risks that arise when planning for future portfolio enhancements or resource needs.
Significant cultural change may be needed alongside technological changes.
Regulation risks
Regulatory changes are another area of extreme risk for utilities. The complexity of reporting, markets, transactions, contracts and accounting rules generate special challenges in complying with the ambiguities of regimes such as Dodd-Frank, REMIT, EMIR, MiFID II and others.
Without accurate internal audits and proper governance, utility companies involved in energy trading can be exposed to significant risk. Forward-looking traders, meanwhile, are seeing that better visibility into the non-standard, structured deals in their portfolios could create new opportunities.
Further complicating matters for utilities are the ever-increasing pressures from global environmental agencies to curb and manage their carbon emissions. Proposals, such as the US Environmental Protection Agency’s comprehensive Clean Power Plan, are expected to affect carbon-fuelled generating plants around the world. Likewise, in Europe, the 7th Environment Action Programme outlines sustainability and biodiversity objectives based on low-carbon growth.
Not only will utility companies need to manage the physical aspects of these new regulations, they will need to facilitate the complex process of dealing with emissions credits and potential new cap-and-trade markets.
Change – and risk – management
With so many factors disrupting their business models, utility companies need to invest in technology that can mitigate the risks they face. Management needs better access to information and tools for decision making, not only for executives, but also for personnel engaged in planning and trading. Without a commodity management platform, they may not be able to accurately dispatch generation, manage contract terms or pass regulatory scrutiny over feedstock purchases.
The assumption has always been that IT will provide access to the right insight. However, the industry has grown up with a dog’s breakfast of homegrown and off-the-shelf energy trading and Risk Management
Risk Management
One of the most common terms utilized by brokers, risk management refers to the practice of identifying potential risks in advance. Most commonly, this also involves the analysis of risk and the undertaking of precautionary steps to both mitigate and prevent for such risk.Such efforts are essential for brokers and venues in the finance industry, given the potential for fallout in the face of unforeseen events or crises. Given a more tightly regulated environment across nearly every asset class,
One of the most common terms utilized by brokers, risk management refers to the practice of identifying potential risks in advance. Most commonly, this also involves the analysis of risk and the undertaking of precautionary steps to both mitigate and prevent for such risk.Such efforts are essential for brokers and venues in the finance industry, given the potential for fallout in the face of unforeseen events or crises. Given a more tightly regulated environment across nearly every asset class,
Read this Term (ETRM) applications that may not be ready to meet the needs of today's power and utility markets. Spreadsheet-based applications, in particular, typically need a high level of expensive customization each time a new type of generation or fuel is added.
A utility commodity management system should at minimum feature robust Analytics
Analytics
Analytics may be defined as the detection, analysis, and relay of consequential patterns in data. Analytics also seeks to explain or accurately reflect the relationship between data and effective decision-making. In the trading space, analytics are applied in a predictive manner in an attempt to forecast the price more accurately. This predictive model of analytics generally involves the analysis of historical price patterns that are used in an attempt to determine certain price outcomes. Analy
Analytics may be defined as the detection, analysis, and relay of consequential patterns in data. Analytics also seeks to explain or accurately reflect the relationship between data and effective decision-making. In the trading space, analytics are applied in a predictive manner in an attempt to forecast the price more accurately. This predictive model of analytics generally involves the analysis of historical price patterns that are used in an attempt to determine certain price outcomes. Analy
Read this Term, such as forecasting, simulation and optimization; standardized models and forecasts to ensure consistency in analysis, with the ability to trace back model results and assess risk across power and gas portfolios; forecasting, simulation and optimization analytics integrated with energy trading and risk management applications; and simulation of market, outage and weather scenarios fast enough to handle trading requirements.
Conclusion
Before you begin evaluating solution providers, understand your company's strategy for hedging risk and complying with regulations in detail. Take an inventory of your most used resource analytics, but also consult traders, risk managers and planners to understand what they need to be successful.
The best approach to reduce the total cost of supporting legacy systems or spreadsheets is to invest in a suite of applications that integrate energy trading and risk management with analytics. This approach will also ensure consistency of information across the organization, which is essential if utilities are going to return to profitability and growth.
