Advanced Hosting Capacity Analysis
NREL's advanced hosting capacity analysis can help utilities, policymakers, and solar developers better understand the impact of adding new distributed photovoltaic (DPV) systems to the electrical distribution system.
Advanced hosting capacity analysis considers the thresholds at which new DPV systems will trigger upgrades or changes to the electrical distribution system and evaluates the cost of different options for expanding the hosting capacity.
It is one part of NREL's work to help stakeholders better understand the distribution system costs associated with integrating new DPV systems at different penetration levels.
NREL's analysis uses a bottom-up methodology that involves simulating distribution systems. The analysis considers sequential increases in hosting capacity and corresponding upgrade costs from a baseline scenario with no DPV up to penetration levels greater than 100% of peak load.
What Is Hosting Capacity?
Hosting capacity is the amount of DPV that can be added to distribution system before control changes or system upgrades are required to safely and reliably integrate additional DPV. Hosting capacity does not represent a hard limit on the amount of DPV that can be added to the distribution system. As upgrades are implemented, the hosting capacity of the system increases. The analysis of these sequential increases in hosting capacity and their related costs are at the core of NREL's approach.
Hosting capacity is highly relational, dependent on a number of factors, including:
- The characteristics of the DPV system, such as whether advanced inverter settings are utilized, the system size, and where it is located on the circuit
- The location and time-varying behavior of all distributed energy resources on the circuit, such as distributed storage
- The existing equipment on a circuit at any given time, which will evolve over time depending on investments made by utilities and DPV owners or developers
- The distribution planning practices used by the utility—especially how they determine when upgrades or other mitigations are required.
Three Approaches to Hosting Capacity Analysis
Snapshot Hosting Capacity
- Traditional firm interconnection approach
- Fit and forget
- Analysis uses worst-case static snapshots
- Conservative limits on the changes in device operations by using proxies for solar variability
Example: Hosting capacity maps, such as those used in California
Uncoordinated Dynamic Hosting Capacity
- Interconnection using autonomous advanced inverter functionalities without communication to the utility
- Time-series analysis and probabilistic screens
- May or may not involve curtailment risk, depending on the inverter settings and size
Example: Volt-var control functionality for PV inverters
Coordinated Dynamic Hosting Capacity
- Flexible interconnection, where curtailment risk is accepted by the PV developer as an alternative to paying for traditional distribution upgrades
- Inverters have communications capabilities
- Uses time-series analysis and probabilistic screens
Example: New York Flexible Interconnect Capacity Solution
Snapshot Hosting Capacity
Snapshot (or static) hosting capacity is the traditional concept of hosting capacity, that:
- Is based on a few snapshots in time using static device settings and behaviors
- Doesn't account for the behavior of loads and distributed energy resources over time or fully capture grid device behavior
- Considers scenarios that are unlikely to occur (e.g., maximum output from all DPV systems simultaneous with minimum load).
There are a myriad of different methodologies that can be used to calculate static hosting capacity. For more information, see the Interstate Renewable Energy Council's Guide to Hosting Capacity Analyses for Distributed Energy Resources.
Dynamic Hosting Capacity
Dynamic hosting capacity is a new concept—and the foundation of NREL's analysis—based on quasi-static time-series simulation, which:
- Considers the behavior of DPV, loads, and grid devices over time
- Accounts for the fact that some over-voltages and thermal overloading are acceptable for short periods of time and during a limited number of time points during the year.
Dynamic hosting capacity is not based on worst-case snapshot power flows, so it requires probabilistic screens that consider the uncertainty around the time-series input variables, like hourly PV productions and building loads. This concept of dynamic hosting capacity is novel and still under development.
Depending on how the individual DPV and the utility-owned grid devices are controlled, two different types of dynamic hosting capacity should be used.
Uncoordinated dynamic hosting capacity — When only local, autonomous control functions for DER and grid devices are used without communication.
Coordinated dynamic hosting capacity — When a communications-based, coordinated control approach is used to adjust the
output of DPV. This coordination may occur at various levels, for example through
distributed controls within a certain portion of the feeder, at the substation level,
or throughout the distribution system and multiple substations. This may also involve
an optimization or simply adjusting the output according to a pre-defined set of rules
or principles of access.
There are many different control architectures that can be used in the coordinated case. Interconnecting in this coordinated dynamic regime has previously been referred to as flexible interconnection. Coordinated dynamic approaches to DPV integration have also been referred to as Active Network Management or as a subset of distributed energy management systems functionality.
Users can see all of the data that informs NREL's unit cost inputs in the Distribution Grid Integration Unit Cost Database.
Details of methodologies and assumptions are included in NREL's publicly available technical reports (see below).
And users can download the Electric Power Research Institute (EPRI) J1 feeder models that were used in NREL's 2018 technical report and conduct their own analysis.
NREL's hosting capacity analysis seeks to illuminate costs to all parties, including those that may be borne by utilities, DPV developers, or customers under current regulatory regimes. Thus, this research provides an overall picture of costs, cost drivers, and possible low-cost integration solutions as a function of penetration level that can be used to inform capital investment and policy or market design decisions.
Quasi-Static Time-Series PV Hosting Capacity Methodology and Metrics, IEEE Conference Paper (2019)
Sequential Mitigation Solutions to Enable Distributed PV Grid Integration: Preprint, IEEE Conference Paper (2018)
Distribution System Costs Associated with the Deployment of Photovoltaic Systems, Renewable and Sustainable Energy Reviews (2018)