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Distributed Optimization and Control

NREL is working to advance foundational science and translate advances in distributed optimization and control into breakthrough approaches for integrating sustainable and distributed infrastructures into our energy systems.

Photo of a group of researchers reviewing the results of numerical simulations in a test of real-time distributed optimization algorithms.

The electric power system is evolving toward a massively distributed infrastructure with millions of controllable nodes. Its future operational landscape will be markedly different from existing operations, in which power generation is concentrated at a few large fossil-fuel power plants, use of renewable generation and storage is relatively rare, and loads typically operate in open-loop fashion.

Current research and development efforts aim to leverage advances in optimization and control to develop distributed control frameworks for next-generation power systems that ensure stability, preserve reliability, and meet economic objectives and customer preferences.


  • Distributed optimization and control
  • Online optimization and learning
  • Stochastic optimization
  • Dynamics and stability
  • Cyber-physical systems
  • Numerical simulations and hardware-in-the-loop experiments 


NREL researchers are developing an innovative, distributed photovoltaic (PV) inverter control architecture that maximizes PV penetration while optimizing system performance and seamlessly integrates control, algorithms, and communications systems to support distribution grid operations.

The growth of PV capacity has introduced distribution system challenges. For example, reverse power flows increase the likelihood of voltages violating prescribed limits, while fast variations in PV output tend to cause transients that lead to wear-out of switchgear. Recent distributed optimization and control approaches that are inspired by—and adapted from—legacy methodologies and practices are not compatible with distribution systems with high PV penetrations and, therefore, do not address emerging efficiency, reliability, and power-quality concerns.

This project will develop distributed controllers that will be validated via comprehensive and tiered software-only simulation and hardware-in-the-loop simulation. Microcontroller boards will be used to create and embed the optimization-centric controllers into next-generation gateways and inverters.

Low-voltage electrical distribution systems were originally designed for one-way power flow to end-users. So as more customers install residential PV systems, there is increasing potential for adverse impacts on system reliability and power quality. In particular, system voltages can rise unacceptably high when PV generation exceeds load.

Leveraging advances in communications and optimization theory, this project is focused on developing a systematic and unified optimal inverter dispatch framework to facilitate high PV penetrations while ensuring network-wide optimization. The novel optimal inverter dispatch framework uses a communication network to control a collection of PV inverters to regulate system voltage and minimize energy losses. It provides increased flexibility over existing approaches by invoking a joint optimization of both active and reactive powers. Ultimately, the performance enhancements afforded by the optimal inverter dispatch approach will allow PV penetration to be safely and reliably increased well above existing levels.

The objective of this project is to advance the foundational science for control and optimization of multi-energy systems by:

  • Uncovering and modeling intrinsic couplings among electricity, natural gas, water, and heating systems, with emphasis on distribution-level operational setups
  • Formulating new classes of multi-energy-system optimization problems incorporating the inter-system dependencies and formalizing well-defined optimization and control objectives
  • Addressing the solution of the formulated problems by tapping into contemporary advances in convex relaxations and distributed optimization and control. 

Departing from existing approaches based on off-the-shelf black-box tools, the project will produce innovative, computationally affordable distributed optimization and control schemes that are grounded on solid analytical foundations and will pave the way to the next -generation real-time control architecture for integrated energy systems.


Optimal Power Flow Pursuit, IEEE Transactions on Smart Grid (2016)

Unlocking Flexibility: Integrated Optimization and Control of Multi-Energy Systems, IEEE Power and Energy Magazine (2017)

Chance-Constrained AC Optimal Power Flow for Distribution Systems with Renewables, IEEE Transactions on Power Systems (2017)

Network-Cognizant Voltage Droop Control for Distribution Grids (2017)

Distributed Controllers Seeking Optimal Power Flow Solutions Using ADMM, IEEE Transactions on Smart Grid (2017)

View all NREL publications about distributed controls and optimization.


Andrey Bernstein

Group Manager