During the course of this series, we’ll make full use of the Intel Embedded Alliance Program and other IA resources. In this installment, we’ll use Intel design decision tools that aid in choosing candidate embedded processors from among Intel Architectures. The second installment will explore Compiler Alternatives and the unique VirtuaLab access to real world development hardware. Intel, Green Hills Software, and Wind River provide mainstream development tools considered.    In installment three we explore evaluating the Atom processor for suitability as the central processor. During the evaluation, we’ll consider a half a dozen commercially available boards and performance for a realtime control application.  


In installment four we consider adding a two-way wireless communications channel for monitoring and controlling functions.


For the last several years the popular press has been touting solar photovoltaic (PV)electric as an answer to our electric needs. The idea of getting “electricity for free” is seductive. But the facts are very serious. In 2007 the average home in the US consumed 936 kilo-watt-hours (kWH) per month! That’s about 12 of the top-of-the-line solar photovoltaic panels per house assuming that the sunlight is never blocked from the panels, the sun shines every day, and there are no efficiency losses.  In sunny climates, residential 2kW peak usage solar systems will deliver electricity at about $0.35 per kWH and in a cloudy climate the cost is about $0.78 per kWH. Only the absolutely largest solar installations of 500kW get the cost of electricity under $0.20 per kWH, which in some locations is competitive.

As you can see from the variability in generated cost per kWH, designing a solar-electric system including controls can’t be met with a single design. Most people think of a solar system that augments the electricity that comes from an electric utility, delivered through the electric grid. That’s because the vast majority of the population is connected to “the grid.” For this type of system, there is no requirement for energy storage which vastly simplifies the design and lowers costs. As can be seen in Figure 1, in a grid-attached system a special inverter is used to interface directly with the electric grid. In all of these systems, the inverter that converts from the Direct Current (DC) produced from solar panels is converted to Alternating Current (AC) in phase with the grid and at the voltage that is provided to the home – most often 240 Volts (V) in newer homes but sometimes 120V in much older homes.




I live in rural Arizona completely off-the-grid. The nearest power line is 4.9 miles away, making the prospect of connecting to the grid remote at best. This type of solar system can be quite complicated with multiple energy sources: solar PV, wind powered generator(s), diesel or gasoline backup generator, hydroelectric,  and other less common power sources.  Figure 2, Courtesy of Outback Power Systems, illustrates a more complete off-grid residential system. While there are many soft realtime algorithms used in a fully configured off-grid, just one of the more intensive computationally intensive algorithms is the signal processing required for controlling the speed of the generator.





Modern solar components like those from Outback contain local communications between components they manufacture and feature control over all of those same components. Even with these manufacturer-provided monitors, monitoring and controlling all of the pieces that can make up a solar electric generation system still requires a master control system beyond what state-of-the-art solar components provide. 

My personal off-grid system is shown in Figure 3.What differentiates it from the system shown in Figure 2 is that there are actually two semi-independent systems. System 1 is the solar electric for my wife’s studio: 5 solar panels, 1 wind generator, an inverter/charger, 6 2V batteries and a 50 amp gasoline generator. System 2 is the system for our house: 2.4 kW of solar panels (12 panels), 2 inverter/chargers, 6 2V batteries, and a 10kW diesel generator custom built from a slow speed Lister engine without any electronic monitoring or controls whatsoever.


What isn’t apparent to most people is the amount of physical monitoring necessary to ensure that electricity is available when it’s needed and in the amounts required. Since my solar components are mounted 50’ away from the house, the inconvenience factor can become overwhelming at night, in the extreme cold, when it’s raining, or in the winter when snow is on the ground. My objective is to create a monitoring/control system that can provide me with details on the state of the system. And remotely turn on the generator if it’s needed.

Looking at the system as currently defined, there are three subsystems that have real time components, and a variable bandwidth demand for the two way radio communications. Given the complexity and potential future expansion of the solar components, the control system will require a processor. But the choice is large. Within the Intel lineup there are 15 processor families to select from:


To narrow the choices to a more manageable set, we need to find the lowest power consumption alternatives. After all, this system is intended to control an off-grid system.   Using the Intel® System Design feature only the ATOM processors are recommended for power consumption of under 5 watts. This narrows the selection to a total of six processors


Having selected six candidate processors, we now need to verify that the processors are capable of performing the necessary algorithms. This development task must be completed quickly, with minimal investment in hardware and software before the final selection is made. In a later blog we’ll use VirtuaLab to perform the selection with minimal investment of both time and money.


If you were choosing a candidate embedded processor what criteria would you use?Can we use one criteria for processor evaluation?