Virtual power plants: aggregating distributed flexibility into tradable portfolios

What is a VPP?

Like a regular power plant, a virtual power plant (VPP) provides energy to the grid. Unlike a regular power plant, it connects smaller, decentralised elements, some of which may be customer-owned rather than a single central resource, such as coal. VPPs are connected via software, which also monitors network health and optimises it. This means there is no brick-and-mortar location for the plant to operate from, making it more flexible and cost-effective.

Aggregation of distributed assets

Aggregation of VPP refers to combining many smaller-scale resources into a single larger asset. The services it aggregates include wind turbines, rooftop solar, batteries, smart appliancesand electric vehicles. The aggregation of all of these services allow smaller outfits to meet minimum capacity requirements for the wholesale market.

Centralised control and optimisation

For VPPs to function well, they require real-time monitoring by software or central control systems. These operations are often managed in the cloud to enable remote health monitoring, which is important in wider regional networks that are not closely located to each other. Strategies to manage optimisation might include specific algorithms, for example, selling energy when prices are high and buying when they are low. Some VPPs might employ AI as part of an Energy Management System (EMS) to forecast optimal trading conditions.

How does aggregation creates value?

Aggregation creates power in numbers: it takes smaller assets and turns them into a larger portfolio that acts like a much larger power plant. It also opens the door for smaller outfits to operate in wholesale markets with higher entry requirements. Because of the component-like build of a VPP, these setups can revenue stack. This means benefiting from multiple streams of revenue from local capacity contracts, as well as from the day-ahead, intraday marketsand balancing services.

As mentioned before, AI can be a component of optimisation strategiesand in relation to value, it can help to mitigate some of the forecasting errors associated with the intermittency of renewable generation. Costs are also reduced through savings on the operational side: having a single set of operational costs rather than each asset having its own.

Scale and diversification

VPPs can create system-wide flexibility, uniting many types of renewable assets, including rooftop solar, EVsand small wind arrays across a large regional area, so assets are not competing with each other.

This creates grid stability because each element is stronger than the intermittency of a single asset.

Market participation strategies 

We know that VPPs can utilise technology advancements such as AI to help dispatch energy at the optimum time, while examining both long and short-term contracts, for example, weekly capacity or in real time. We can also utilise risk-constrained bidding to help mitigate some of the forecasting errors and price volatility associated with renewables.

Wholesale trading

While VVPs primarily act as energy sellers in the context of this article, in reality, they are also usually buyers of energy due to the intermittency of generation. They have to adjust their portfolios to account for unpredictable output to participate in renewable energy markets, such as intraday trading.

They can also act as a balancing service provider, providing ancillary services.

We can use VPPs to aggregate battery storage for frequency regulation: this high-value service requires an immediate response to demand.

Operational complexity

Because a VPP is composed of multiple components, a map of complex relationships can underlie the standard VPP. This requires sophisticated software to manage everything from relationships to energy trading markets.

Heterogeneous asset management is also crucial, as VPPs comprise a mix of intermittent assets, such as wind, solarand batteries, that need to be integrated into a reliable energy source. This requires a lot of data, so suitable infrastructure is needed to process and control it.

Forecasting distributed assets

Because renewable energy is an intermittent source, machine-learning-based forecasting may be required to accurately manage VPPs in real time and smooth associated volatility.

There are also unique challenges with Behind-the-Meter assets: forecasting consumption can be difficultand consumer behaviour isn't always known to the grid itself.

Positives are to be found in forecasting for VPPs, though: aggregating assets can actually reduce overall forecasting errors.

Coordinating multiple units

Grid constraint compliance, or situations when the grid controls how energy is distributed throughout the network, is a real consideration for VPPs and these must be balanced to avoid network disruptions. Ancillary services must also be balanced, so that services like load balancing can be reliably provided back to the grid. This is where a VPP acting as one flexible asset rather than disparate elements really comes into play.

Impact on market dynamics

Overall, we can see how VPPs' flexibility and adaptability position them as an attractive alternative to traditional plants, while achieving decarbonisation goals. They stabilise renewables as an option by easing pressure on a single source, making them more nimble and dynamic than their fossil-fuel competitors. This, coupled with their ability to help consumers and businesses achieve decarbonisation targets, will shape the marketplace, positioning them ahead of fossil fuel plants and offering a real chance of delivering stable energy compared to singular renewable options.