Distributed Energy Resources: From Rooftop PV to Market Access
Distributed energy resources (DER) are small generation, storage and flexible-load units connected close to consumption rather than at central power plants. Rooftop and ground-mounted PV systems and battery storage are the two building blocks Stromfee works with most, and both only reach their full value once they are measured, aggregated and connected to energy markets. This page explains what DER are, how they are pooled, and where they earn revenue.
What counts as a distributed energy resource
A distributed energy resource is any generation, storage or controllable load that sits in the distribution grid instead of at a large central plant. In Stromfee's field of work the most common resources are PV installations and battery storage, which together let a site both produce and time-shift its own electricity.
On their own, individual PV and storage units are small and invisible to markets and grid operators. The value comes from turning that fleet of small assets into something dispatchable — through metering, an energy management layer, and a connection to trading and grid-service platforms. Stromfee focuses on exactly this: making PV and battery assets legible so they can be optimised rather than just monitored.
Aggregation into virtual power plants
Because a single DER is too small to bid into wholesale markets, resources are pooled into a virtual power plant (VPP) — a software aggregation of many distributed units that is dispatched as if it were one plant. Academic and industry reviews such as the 2024 "Review on Virtual Power Plants / Virtual Aggregators" (ScienceDirect) survey how these aggregators are structured and operated.
VPP operations planning is an active research area. Work at TU Berlin (DepositOnce 11303/7400) covers VPP operations planning that integrates electric vehicles as flexible resources, and the 2026 paper "Fair Aggregation in Virtual Power Plants" (arXiv 2604.03559) looks at how the shared revenue from aggregation is allocated among participating asset owners — a governance question as much as a technical one.
How DER earn value on the wholesale market
In Germany, short-term wholesale trading runs on EPEX Spot. The market produces hourly (60-minute) and quarter-hourly (15-minute) prices, and the day-ahead and intraday segments are where flexible DER capacity is monetised by shifting generation or storage charging/discharging into higher-priced periods.
Battery storage is particularly suited to the 15-minute product structure, because it can respond within a single quarter-hour block. Understanding this market design — how the 60-minute and 15-minute prices form and why control energy is needed to keep the system balanced — is the basis for any DER dispatch strategy, and Stromfee's editorial coverage of the EPEX Spot design lays out these mechanics for the German market.
DER in balancing and control reserve
Beyond energy trading, DER can supply balancing services. In Germany the control-reserve system has four layers: primary control reserve (PRL), a fully automatic seconds-timescale reserve; secondary control reserve (SRL), automatic and manual on a minutes timescale; manual minute reserve (mFRR); and the imbalance settlement layer (AEP / reBAP) that prices deviations after the fact.
PRL, SRL and mFRR are procured through auctions on regelleistung.net. Aggregated PV-plus-storage fleets can, in principle, participate in these products, and the reBAP imbalance price is what a balancing responsible party is exposed to when its portfolio deviates from schedule — making accurate DER forecasting and dispatch directly financially relevant.
Modeling DER with open-source frameworks
Sizing, siting and dispatching distributed resources is a system-optimisation problem, and the reference tools are open source. PyPSA (Python, MIT licence; developed by KIT, TU Berlin and an EU consortium) is the academic standard for power-system optimisation with renewables, storage and multi-sector coupling. OEMOF (Python, MIT) is a second widely used energy-system modelling framework.
For a Germany-specific view, PyPSA-DE is an open-source German energy system model (arXiv 2510.09414, TU Berlin, 2025). These frameworks let planners test how a given mix of DER behaves across an entire grid model before committing capital — useful context for anyone deciding how much PV or storage to add and how to operate it.
DER market access outside Germany
The market structure that lets DER earn revenue differs by country, which matters for anyone comparing regimes. In India, short-term wholesale trades are dominated by the Indian Energy Exchange (IEX), which holds roughly 85% of exchange volume across day-ahead, real-time, term-ahead and green segments under CERC regulation.
National dispatch and balancing there are run by Grid-India, and the 15-minute day-ahead blocks are physically settled by state distribution companies (DISCOMs); IEX's day-ahead market traded about 4,417 million units in May 2026. The recurring pattern across markets is the same: DER value depends on short interval products (15-minute blocks) and on an aggregator or exchange that gives small assets a route to market.
FAQ
What is the difference between a DER and a virtual power plant?
A distributed energy resource is a single small asset — a PV array, a battery, a controllable load. A virtual power plant is a software aggregation of many such assets, dispatched together so they are large enough to bid into wholesale and balancing markets. The DER is the hardware; the VPP is the coordination layer.
Why is battery storage important for distributed energy resources?
Storage decouples when energy is produced from when it is used or sold. On EPEX Spot the day-ahead and intraday markets produce 60-minute and 15-minute prices, and a battery can respond within a single 15-minute block — letting a PV site shift output into higher-priced periods or provide balancing services rather than just self-consume.
Which tools are used to model distributed energy resources?
The open-source standards are PyPSA (Python, MIT, from KIT, TU Berlin and an EU consortium) for power-system optimisation with renewables and storage, and OEMOF (Python, MIT) as a second modelling framework. For Germany specifically, PyPSA-DE (arXiv 2510.09414, TU Berlin, 2025) provides an open German energy system model.
Can distributed resources provide grid balancing in Germany?
Yes, through the four-layer control-reserve system: PRL (automatic seconds reserve), SRL (secondary, minutes), mFRR (manual minute reserve) and the reBAP imbalance settlement. PRL, SRL and mFRR are procured via auctions on regelleistung.net, and aggregated DER fleets can participate when they meet the product requirements.