Power Quality Doctor

The Era of the Future Grid

The secondary evolution of a power quality engineer and AI.

Robert Black · Edison

01. From the physical world to the digital horizon

For the past three decades, I have been on the front lines of power quality mitigation and industrial power distribution. From the distribution networks of large industrial plants to new-energy grid connection; from reactive-power design to on-site harmonic commissioning; from voltage stability to system-level efficiency. I have watched the grid move from one generation of equipment to the next.

Over the past few years I slowed down, and looked again at how the technology, the business, and the work itself were changing.

Coming back in 2026, two currents are meeting:

• New energy and energy storage are rebuilding the physical grid.
• Artificial intelligence is changing how electrical engineering is analyzed.

That meeting is why Project Edison exists.

02. Power electronics, and the problems that come with it

Over the next decade the change that matters is not only more installed capacity. It is what the grid is made of.

• The older grid was built around synchronous machines and inertia. The grid ahead is dominated by power electronic devices.
• Storage converters, photovoltaic inverters, wind converters, high-power charging, and dense data centers are no longer only loads at the end of a feeder. They interact with the grid at high frequency.

That brings problems older experience does not cover on its own:

1. Nonlinear harmonics and high-frequency resonance get harder, and a conventional filter often fails.
2. Very fast voltage dips hit sensitive loads, including computing and semiconductor lines, and the cause is hard to trace.
3. Devices on a weak grid oscillate across a wide band. The operating boundary moves past what a person can watch by hand.

Field experience is still the base. On a multi-variable, nonlinear grid it is no longer enough by itself.

03. Why AI

A lot of sound electrical ideas used to stop at the cost of time. Reading long monitoring files, tying faults together, checking them against standards, and modeling a nonlinear system took senior people and long hours.

AI does not replace the engineer. It changes the tools. It turns scattered project experience into something that can be looked up. It shortens the repetitive reading. The judgment on site stays with a person.

04. The Edison framework

Edison is not one diagnostic program. It is a way to put field practice, power-quality standards, and assisted reading in one place.

• The base is thirty years of field work and industrial cases.
• The frame is mainstream power-quality standards plus measurements from site.
• The engine is assisted reading of those measurements. A person still decides.

05. Three pieces of work

Knowledge for grids that are full of power electronics: storage connection, microgrid stability, data-center loads, and diagnostic models that stay tied to the measurements.

A mobile platform that puts photovoltaics, storage, and power-quality equipment on one trailer, so the reading can be checked against a real system rather than a diagram alone.

PQ-Doc, the desk that turns a measurement file into a structured reading: harmonics, voltage dips, and the boundary of what the file actually supports.

06. For industrial partners

Engineering firms, equipment makers, and integrators are the people this is written for. The client on site stays with them. Edison reads the file from here.

07. Continuous evolution

The useful engineer in this grid is the one who keeps checking the work, with AI as a tool and with the responsibility still on a person. Edison is that practice, written down as I go. Further English essays will be added on this site as they are finished.

Edison · Future grid · Power quality · AI