efficiency – Gonzology

Urban Mobility Hub – Concept

Posted on December 21, 2017December 28, 2017 by gonzorourke in Mobility

The world is urbanizing, the United States included. According to the United Nations Population Division , as of 2016, 82% of the US population lives in urban areas, with no signs of slowing . This influx of people into cities changes the value and use of land, emphasizing the importance of managing the delicate balance between plenty of inexpensive parking options to drive vibrancy and encouraging sustainable, environmentally friendly land uses that reduce parking options.

At the same time, mobility is being transformed . The one person, one fossil fuel powered car, ownership model for transportation that exists today and has driven priorities for city planners for decades is giving way to a shared, electrified and autonomous personal mobility services model , with millennials at the core of this shift . Car and suburban home ownership will give way to shared electromobility and urban renting over the coming decades.

The Urban Mobility Hub (UM-Hub) combines flexible multi-use infrastructure with technology for easy to use, highly utilized mobility services to deliver an economically viable way to manage the transition. With services that meet today’s reality, services that meet tomorrow’s possibilities and the ability to optimize this mix over time, city planners and land developers can simultaneously embrace this change and meet the demands of an increasingly urban society today and tomorrow.

The Mission: Develop optimized multi-use infrastructure that embraces and fosters the transition from one person, one car to shared electro-mobility within an urban environment.

Goals:

Make urban mobility and the urban-suburban connection easy
Leverage technology to create and capture customer value
Deliver services with elastic capacity and optimized pricing
Provide complementary and sustainable revenue streams

Primary Customers:

Urbanite: Lives downtown, works downtown, owns no vehicle
Commuter: Lives in the suburbs, works downtown, owns an ICE[i] vehicle
Developer: Invests in new infrastructure, operates at a profit over 20+ years
City Planner: Balances urban vibrancy against environmental sustainability

Requirements & Features:

Easy to get from point A to point B: daily commute, ad hoc, multi-mode
Real-time service pricing that reflects supply and demand
Elastic service capacity: expands/contracts over a day, by day of the week, seasonally, yearly
Mobile app for easy planning and use of mobility services
Integrated usage data across mobility services to drive optimizations
Low-cost, automated enforcement
Customer safety: uniform lighting, convex mirrors, emergency call buttons, video
Solar generation & storage to control EV charging costs

Broadband Wi-Fi access throughout
EV charging: level 2, 3 & 4 plus inductive charging
Valet services for fast/late transitions: car, self-parking car, bicycle
Shared delivery services for last mile: fixed route, ad hoc
Car sharing and bike sharing services
Bicycle racks and lockers
Changing and shower rooms with lockers

LEED Green Garage certification[ii]
APO certification[iii]
TDM integration[iv]

Amenities by Floor:

Rooftop Park – Landscaping, paths, benches w/USB charging, lunch spots (table & chairs), play structure for youngsters, bouldering wall, solar shades
Elastic Environment[v] – Traditional parking, convertible event space w/view (weddings, wine tastings, yoga classes, etc.)
Traditional Parking – Availability, securing and paying for ad hoc or monthly parking all done via mobile app (no attendant needed)
Premium Car Services/Parking – Auto detailing salon, self-service auto bays w/lift, long-term climate-controlled vehicle storage w/valet in & out
EV Charging/Parking – Level 2, 3 & 4 stations, inductive charging, parking/charging for shared autonomous vehicles across categories (2-seat, truck, van, wagon, etc.) waiting for next use
Sharing – Bike sharing kiosk, flex-car service (e.g., ZipCar), van-pool, vehicle drop-off service w/valet & self-parking stalls[vi][vii], bicycle valet service, private bike lockers

Revenue Streams:

Parking[viii][ix][x]

Hourly parking
Drop-off service: valet & self-parking
Valet overflow parking for downtown hotels
Long-term travel parking w/shuttle: to airport, vehicle leasing
Climate controlled vehicle storage w/valet in & out (via mobile app)

Services (Own & Operate)

Cash machine
Private bike & gear lockers w/showers
EV charging
Shuttle: fixed route & ad hoc

Leases (3^rd Party Services)

Coffee and breakfast items
Beer garden/patio
Bike sharing kiosk
Flex-car spaces & kiosk
Auto detailing salon
Self-service auto repair bays w/lift
Scheduled events: yoga class, musical performance
Special events: wedding, wine tasting

References:

[i] Internal Combustion Engine – https://www.washingtonpost.com/news/innovations/wp/2017/10/11/why-2017-will-go-down-as-the-beginning-of-the-end-of-the-internal-combustion-engine/?utm_term=.7d7bbe873119

[ii] Green Garage Certification – https://www.usgbc.org/articles/gbci-administer-green-garage-certification-program

[iii] Accredited Parking Organization – http://www.parking.org/professional-development/accredited-parking-organization-program/

[iv] Transportation Demand Management – https://mobilitylab.org/about-us/what-is-tdm/

[v] Elastic Environment – https://www.psfk.com/2013/04/multipurpose-garage-event-space.html

[vi] 5by2 Parking – http://www.5by2parking.com/

[vii] PerfectPark – http://perfectparkusa.com/index.html

[viii] The Parking Garage of the Future – http://blog.caranddriver.com/parking-garages-poised-for-big-makeover-in-autonomous-age/

[ix] The World’s 18 Strangest Parking Garages – http://www.popularmechanics.com/cars/g324/worlds-strangest-parking-garages/

[x] Smart Multi-Purpose Garage – http://www.popularmechanics.com/cars/g324/worlds-strangest-parking-garages/

Things

Posted on December 21, 2017 by gonzorourke in Energy, Internet of Things (IoT)

The Internet of Things, or IoT, is vast, consisting of nearly 50 billion “things” by 2020 according to Philip Howard. The IoT is also nebulous. Defined as a network of physical objects or “things” embedded with electronics, software, sensors and connectivity, this IoT as we know it today includes devices as diverse as heart monitoring implants, biochip transponders on farm animals, automobiles with built-in sensors, refrigerators providing online status, bio-hazardous particulate sensors, centrally scheduled and monitored outdoor lighting, distributed net-energy meters, and many more. Plus who knows what kinds of things are on the drawing board.

Connecting all these things to the Internet is a certainty. Economics insure it. Publicly traded companies making data center hardware and software, delivering connectivity plumbing like fiber, providing cloud services, offering mobile services like smart phone connectivity, are all looking for that next hundred million in revenue offered by an emerging market of 50 billion things. Plus like those bulls in Pamplona, startups are running toward this bullring of opportunity too, hoping to create the killer app or uncover the dominant business model for all these things. How, though, will all these things get connected? Why wirelessly of course.

Cellular

The edge of the Internet is hard to get to, because it is either remote or always moving or both. If it were easy, it would already be part of the Internet! Imagine an IoT application that utilizes RFID tags to track tools and equipment assigned to a truck and used by a field service worker. Depending upon the job and the day, this field service truck and worker may be in town where connectivity is easy, or way out of town at a remote, high-value asset like a pipeline pump station. Only a wireless connection works in both situations. One glimpse of a typical cellular provider’s mobile data coverage map and it’s easy to see that cellular coverage is prodigious. Ever increasing ARPU powering a never ending rollout of data connection speeds (… 2G, 3G, 4G/LTE …) has insured that cellular is very nearly everywhere. This fact lies in stark contrast to the many failures of Municipal Wi-Fi, doomed by technical, economic and business model shortcomings, foreshadowing a future bathed in cellular.

Cellular, however, is not the Internet per se because it does not operate using the Internet Protocol known as TCP/IP. Yet cellular routers and mobile applications with their cloud services have become quite adept at marshaling TCP/IP payloads across cellular networks, so cellular is perfectly capable of being used to extend the edge of the Internet as far and wide as cellular networks reach today, and tomorrow.

Spanning Networks

At the Internet’s edge, IoT application developers are hard at work building businesses on devices connected to the Internet via a spanning network. First, a spanning network extends the reach of the Internet using cellular, from a cell tower outward, as far as a cell tower can reach – the so-called last mile of connectivity. Then from the edge of a cell tower’s reach, a spanning network extends the Internet even further. Wired protocols like PLC for gas, water and power meters or RS-485 for fieldbus devices have been used in the past, but the ease and economics of wireless mesh networks like Zigbee and its many variants are rendering wired protocols obsolete. So more commonly, the last foot of connectivity is provided by wireless mesh protocols.

Each IoT application needs a spanning network. The nuts and bolts of this network are built from standard, off-the-shelf components like cellular routers and RF radios, but the performance characteristics of a spanning network are very application specific. How big are the payloads? How far and wide must payloads be distributed and through what routes? With what frequency must payloads be uploaded and downloaded? These application details along with the economics involved in operating a spanning network at scale drive the success of an IoT application, perhaps even more than its functionality.

Designing, testing and then operationalizing a spanning network at scale is nontrivial. Delicately balancing throughput requirements against cellular data plan requirements and costs is just one of the key drivers, but one that has an oversized effect on operational costs. How many wireless mesh nodes worth of payloads can a single cellular edge router manage? How many cellular edge routers are required to cover an IoT application’s service area? How big a machine-to-machine data plan does each cellular edge router need and what will the costs be in full operation?

Early investigations on these topics during the IoT application design phase can be dramatically simplified by a cellular edge router with the right functionality. The same is true during testing, operational scaling and even maintenance over a service agreement’s term. A cellular edge router designed for IoT application developers would support these features and functions:

Application Agnostic
Cloud Connected
Virtualization
Wireless Mesh NAT and DHCP
Bandwidth Modeling
Energy Management
Differential Monitoring

Application Agnostic

Attempting to be the Ginsu Knife of cellular edge routers for IoT developers is folly. There is no way to predict how a customer in a particular vertical market segment will wish to integrate IoT devices with a spanning network, and even if you could, satisfying such a disparate set would bloat a cellular edge router and render performance for any specific customer lame. Companies have struggled for years trying to be just such a solution.

Instead, the paradigm needs to change. The interface between a specific IoT application and the cellular edge router becomes Ethernet only, with the app developer encapsulating their app logic into an Ethernet push device like Synapse Wireless’ SNAP Connect E10 and E20 or EKM Metering’s EKM Push. This push device has intimate knowledge of the payloads being exchanged between the wireless mesh and the cloud as well as message semantics, recovery strategies and the like, which frees the cellular edge router to focus solely on optimized TCP/IP payload exchange.

Cloud Connected

Public IP addresses are too valuable a resource to dole out willy-nilly so instead, carriers dole out private IP addresses to cellular edge routers, which require a VPN connection into the carrier’s network for direct access to a cellular edge router’s configuration. These private IP addresses are used to configure, troubleshoot and optimize the performance of a cellular edge router. For initial configuration a VPN client and configuration may not be necessary because the router can be connected locally to a computer via an Ethernet cable, but once the router heads into the R&D lab or out into the wild it’s a different story. VPN client licensing and configuration across multiple roles within an organization is an unwieldy proposition at best, and one that gets disproportionately worse as the number of routers grows. Edge router support, troubleshooting and optimizations over time to maintain an IoT application’s spanning network must be simple and low-cost.

The solution is for a cellular edge router targeting IoT application developers to be “cloud connected”. Instead of connecting directly to an edge router’s configuration webpage through a VPN pipe, the IoT app developer securely logs into a cloud service provided by the edge router manufacturer in order to manage the edge router’s configuration initially as well as over time. Once provisioned into the carrier’s network, the edge router receives all of its configuration parameters from this manufacturer cloud service while pushing router monitoring and status information to the cloud service as well. No VPN client is required. No direct connection to the edge router’s webpage is needed either. The IoT app developer can then manage roles, authentication and authorization to specific edge routers in a way that is consistent with other managed devices. What’s more, a cloud service enables a stickier, longer-lasting relationship between the edge router manufacturer and the IoT app developer that improves monetization over time and can help fund cloud service development for the cellular edge router manufacturer.

Virtualization

Virtualization has been an economic boon for corporate IT and datacenters because of its dramatic improvement in utilization. Shared connectivity was the enabling technology, lower operating costs the benefit.

A similar benefit occurs when all of the edge routers in a spanning network share connectivity as they do when cloud connected. Cellular data plan utilization improves. In fact, the IoT application developer can optimize this part of their business, which can have a huge impact on the bottom line when considered across many customer installations.

Additionally, spanning network reliability improves. Each cellular edge router’s configuration for a particular IoT application resides in the cloud, simplifying failover and reducing downtime. A cellular edge router can be re-flashed in minutes. Or the router can be swapped in the field by lower cost field resources that know nothing about the IoT application, and then flashed and spun up remotely by the application developer. A spanning network can even be designed with overlapping meshes and overhead bandwidth so that a single cellular edge router can temporarily backhaul multiple meshes should an edge router fail in the field. This temporary releveling can be done remotely to preserve uptime at the expense of throughput, but then returned once the edge router gets replaced, all without rolling a truck.

Wireless Mesh NAT and DHCP

Low power, low throughput wireless meshes are the norm for IoT applications because the operating expenses are more favorable. Unfortunately, these meshes do not use the Internet Protocol. Neither IP addresses nor protocols like DHCP are supported, but a cellular edge router designed for IoT application developers could deliver these capabilities. Using IPv6, a cellular edge router could individually address each node in an 802.15.4 mesh, and provide NAT as well as DHCP to simplify management from the cloud. These edge router features would further simplify the application design process for IoT developers, adding even more value.

Bandwidth Modeling

Many, possibly even most, IoT applications will be delivered as financed services so that the “customer” pays over time, often in the context of a performance contract. Financing adds a time dimension to the economics of a solution, and heightens the importance of operational expenses like cellular backhaul data plans to the overall value proposition of an IoT application. Initially identifying the optimal data plans becomes crucial. Maintaining the optimal data plans over time as carriers change plans also becomes essential.

A cellular edge router will not know the dollars per megabyte for its backhaul pipe, but it will know the megabytes moved through the gateway per month, which obviously drives data plan economics. Early on in the design of an IoT application, the megabytes per month for each class of IoT device must be determined and then used to model the throughput of each router in the IoT application’s spanning network. Making this analysis and optimization easy and then simplifying verification in the lab as well as out in the wild during a performance contract has huge value to the IoT application developer.

A set of bandwidth modeling steps might unfold like this:

Connect an IoT device to the router using a wireless mesh and enable real time throughput monitoring, then run the device through its usage scenarios, keeping track of payload size and frequency (i.e., data usage) per scenario.
Assemble a collection of IoT devices sharing a single wireless mesh along with a single router into a scaled down spanning network, then put the IoT devices through their combined usage scenarios to determine the maximum number of IoT devices a single router can effectively backhaul.
Operate the scaled down spanning network beyond the router’s capacity to understand throughput failure modes and how to set alert thresholds for managing to a performance contract.
Expand to a multi-router, multi-wireless mesh spanning network to fine tune the IoT application’s operational parameters and alerts, all the while using the router’s bandwidth modeling tools as the design feedback loop.

Throughout, easily accessible bandwidth information provided by the cellular edge router enables the IoT developer to economically deliver optimized spanning networks for the IoT application.

Energy Management

Remote IoT applications may be battery powered, so understanding the energy characteristics of a cellular edge router across a broad set of scenarios, as well as being able to affect the router’s energy profile programmatically and in real time, is crucial. However, even when the IoT application is not remote, energy matters. The cost of energy comes out of the IoT application developer’s top line revenue when providing a service. Nowhere is this truer than in IoT applications targeting the energy sector, where every kilowatt generated or saved gets monetized.

The solution involves insuring the IoT application developer has access to rich energy usage data for the cellular edge router as well as a programmatic way to affect the router’s energy profile over time. Like bandwidth data, energy usage data provided by the router helps during the design and test phase and then rolls into differential monitoring to help the IoT application developer craft, then meet, a customer performance contract.

Differential Monitoring

A typical wide area IoT application requires a spanning network with numerous cellular edge routers for backhaul. A successful IoT application developer will have many customers, each with an instance of a wide area IoT application spanning network. Therefore, a successful IoT application developer must manage a large number of routers. Proactively assessing each router’s ongoing performance is untenable at scale, even if doing so can be accomplished using a cloud service. Instead, differential monitoring hosted at the cellular edge router’s cloud service is the key. Granular, side-by-side, near real time graphs of many routers performing similar functions is the simplest way to identify anomalies at scale. Once identified, troubleshooting can begin.

Exceptions to normal behavior, surfaced as alerts, are another form of differential monitoring. Performance thresholds that trigger alerts can be configured to proactively manage a spanning network’s performance to a service level agreement, a competitive advantage in the IoT space. Facilitating the performance analysis of an IoT application’s spanning network in order to craft the terms and conditions of a service level agreement, and then creating the associated alerts, enables the IoT developer to over deliver in the eyes of the customer.

Three Examples

A cellular edge router with these features could be used to design IoT applications where the spanning network provides stateless connectivity only as well as where the spanning network is state-full and provides unique capabilities to the application. A few examples should help illustrate.

Remember the tool tracking and utilization service for truck fleets from above? This application is primarily a monitoring application, so no algorithms need to reside and run at the edge and the spanning network simply passes data from RFID tags on tools through the truck’s cellular edge router and up to the cloud. No app aggregator would be needed in the wireless mesh because no state or semantics reside there. However, IPv6 addressing and DHCP from the wireless mesh all the way through to the cloud would be very beneficial and easily delivered by this cellular edge router.

Similar to the tool tracking example, imagine a service for tracking a department’s fleet of police cars. This application is also primarily a monitoring application without algorithms at the edge, but there are additional store and forward semantics that would improve data collection and bandwidth utilization. Desired data might include location of the vehicle, of course, but also identifiers for the officers in or near the vehicle as well as gun access and stow events. An application aggregator, in this case, would be needed in the wireless mesh and would include a GPS chip for location, an RFID receiver for officer and gun identification plus a holster detector. These monitoring payloads would be packaged up by the aggregator and then passed through the Ethernet interface of the cellular edge router to the cloud. The cellular edge router would know nothing of the application beyond throughput requirements.

At the other end of the spectrum, imagine a mesh of off-grid solar lights that coordinate a shared dusk and dawn demarcation for a cloud-based lighting schedule. Each solar light has a solar collector and can detect dawn and dusk, but these detections will vary from light to light causing a rolling turn on across the entire mesh. For a single on and off across all lights, a coordinated on/off can be determined by majority. Once a majority of the lights within the mesh detect dusk, for example, all lights turn on simultaneously. Ditto for dawn, except that the lights turn off. These semantics are handled within the mesh rather than in the cloud to eliminate the data throughput requirements and connectivity latency. Here an application aggregator would be required, with the algorithm to determine “majority” and then broadcast the turn on or turn off message to the mesh. This aggregator would include a wireless mesh radio so that it can communicate with all the solar light nodes in the mesh, as well as a processor to execute the coordinated on/off algorithm and an Ethernet chip for communications with the cellular edge router. Though more functionality resides at the edge in this example, the cellular edge router still knows nothing about these semantics because they are encapsulated in the application aggregator.

A Missed Opportunity

Nobody seems to be targeting IoT application developers and building this cellular edge router, which seems like a missed opportunity. Fifty billion reasons seems like plenty of motivation, I wonder where the takers are.

Franken’home

Posted on December 21, 2017December 21, 2017 by gonzorourke in Energy

I love architecture. I also love technology, so blending the two is a fantasy, or so I thought. Turns out my day job in highly distributed renewable energy forces me to rethink all of the systems in a home in the context of the latest efficiency, generation and storage technologies. Doing so is hard and turns my fantasy into some kind of Franken’home, stitched together from bits and pieces across several industries. Here’s what I mean.

First and foremost, my dream home is perched on a low-bank waterfront parcel on the Puget Sound near Seattle, Washington. If you have never meandered a salty sound beach, dodging star fish and geoducks and inhaling that pungent kelp-filled fragrance, you are missing out. But I digress…

Of course my dream home is efficient, adhering to the latest passive solar home design principles including a highly performant building envelope with carefully managed airflow, orientation that maximizes seasonal use of sunlight and a suitably sized thermal mass integrated into the home design as concrete flooring and walls. Combined these passive solar principles ensure my dream home barely sips energy.

Even so, today’s modern life filled with electronics comes at a price; the auxiliary energy load is high. Multiple computers, media equipment, appliances, electric car chargers and the like all require energy. Plus Seattle is not exactly bathed in sunshine all year long like the Southwest. To meet this load above and beyond the passive solar design, my dream home has rooftop solar, perhaps an 18 kilowatt installation. Leveraging the beachfront location, a 2 kilowatt micro-wind turbine takes advantage of the prevalent winds and helps to offset the load as well. Solar and wind variability necessitates storage, so my dream home also has a 30 kilowatt-hour, lithium-iron-phosphate battery storage system to smooth out this variability and accommodate the long winter nights at 48 degrees North latitude. Even with all this onsite generation and storage capacity, however, I still believe there will be long-term value in remaining connected to the electricity grid so my dream home includes a net meter with a connection to and relationship with my local electric utility.

Now that energy is covered, what’s next? Lighting. All lighting, indoor as well as outdoor and landscape lighting, leverages dimmable LED technology. Moreover, dedicated DC-only lighting circuits are built into my dream home and powered by the DC battery system. Doing so eliminates the incredible redundancy of converting natively DC lighting to AC every time it connects to power. The battery system is charged by solar and wind, which of course are both variable DC, and then on rare occasion by the AC connection to the electricity grid when renewable fuel falls short of demand or becomes more economical. In turn, the battery system serves to smooth out this variability, delivering consistent DC voltage for all lighting. This consistent DC voltage also gets used throughout my dream home to power DC accessories via Universal Serial Bus (USB) interfaces integrated everywhere. Imagine how convenient your kitchen island and counters, and even bathroom counters, become with traditional AC power receptacles plus USB ports for charging the myriad electronic devices now standardized on USB cables for power.

While the greater Seattle area ranks low for solar irradiance, rainfall is abundant, so rain water is carefully managed. All water on the structure and surrounding flat-scapes is collected, filtered and stored in an underground cistern, along with gray water generated inside the home from lavatories, tubs, showers, etc. Gray water in the cistern is then recycled for use in flushing toilets and for landscape watering.

On to heating. Have you ever experienced in-floor radiant heat, also known as hydronic radiant floors? The experience warms the soul (or sole anyway.) Because your feet are warm, and heat rises, the experience is very satisfying. It can also be very efficient, especially when embedded in concrete floors serving as thermal mass and mated to the latest solar water heating technology. Sure, a pump is required to recirculate the high energy-density fluid through the hydronic tubing, but very little electricity is required to actually heat the fluid. Only when the concrete flooring cools below the comfort level does in-floor radiant heat even need to kick in, and then only when there’s insufficient sunshine does the fluid need to be heated with an auxiliary electric heat exchanger. So my dream home includes in-floor radiant heating with a solar heat exchanger and electric backup.

What about cooling? The greater Seattle area is not known for its long stretches of 100+ degree days in the summer, but given the location of my dream home on the Puget Sound, taking in the view is paramount. View means glass, and glass means cooling load, especially when facing south or west. In-floor or in-ceiling radiant cooling is an elegant solution for all the same reasons in-floor radiant heating is. Unfortunately, radiant cooling is subject to condensation issues when relative humidity is high, which is the case in Seattle, so this solution will not work. Instead, careful attention is paid to passive solar design details like glass properties and thermal conduction between the poured concrete floor and the cool earth below, which dramatically reduces the cooling load overall. Then an efficient air-to-air heat exchanger like the one from Daikin is used for spot cooling where and when necessary.

My Franken’home is lying on the operating table all stitched together, an amalgamation of disparate yet highly efficient systems. It is not, however, alive. To make my dream home live, it’s not lightening I need but a control system, and this is the biggest gap in today’s available technologies. Nest, recently purchased by Google for a whopping $3.2 billion, helps show the way with its clever activity-based learning and optimization. My dream home takes this idea and extends it throughout all systems in order to give it life. Sensors abound. Each room or area in my dream home has its own hydronic radiant floor zone, lighting zone, window covering or shading zone, temperature sensors at ground level, torso level and ceiling level, occupancy sensors and lumen sensors for brightness. These sensors provide the real time feedback loop necessary to optimize the various systems over time. Plus each room or area has a manual control for temperature, lighting and shading. Then like Nest on steroids, over the course of a year’s worth of seasons, my dream home’s control system learns the relationships between season, time of day and activity – reinforced by manual adjustments to systems – and derives common default behaviors with the twin goals of hands-free comfort and energy efficiency most of the time. Overrides will occur all the time, and will remain easy, but with more and more time the activity trends will emerge that enable the system to be comfortable and energy efficient, automatically.

Energy efficiency in the context of occupant comfort has more to do with load management. The other dimension of efficiency in my dream home with onsite energy generation and storage plus a connection to the electricity grid involves economics. When should onsite energy generation be used directly by house loads, stored in the battery system or inverted through the utility’s meter onto the grid? The answer lies in the relative costs and benefits of the various options based on the time of use. Utility energy prices over time are one key input. For example, if energy is being generated when the utility will pay a premium, then this energy is inverted onto the grid while the house runs off the battery system. However, if historically the next day has a particularly high demand for lighting and USB device usage and there is insufficient time to fully top off the battery system overnight, then some of the renewable energy generation is used to charge the battery system instead.

Like the temperature, lumen and occupancy sensors used to optimize the energy loads of comfort systems, optimizing energy economics needs sensors too. These sensors are called meters, with current transformers (CT), and they measure energy, power, current, voltage and a host of more esoteric power parameters. My dream home includes granular energy monitoring. Each of the comfort systems – heating, cooling, lighting and shading – has its own meter and CT for individual monitoring. The heating system utilizes a pump and backup electric heat exchanger so each of these sub-systems is individually monitored with its own meter and CT. All major appliances are individually monitored too – refrigerator, oven, induction cooktop, microwave, dishwasher, clothes washer and dryer, media equipment and EV car charger. All DC USB accessory circuits are monitored together with a single meter and CT, as are the conventional AC power receptacle circuits, so individual accessories won’t be identifiable but accessory energy usage as a whole will be. Energy generation systems are also individually monitored. Together, all this monitoring information gets used to learn and optimize the economic performance of my dream home over time.

This level of whole-house system integration centered on simplicity for the home owner does not exist today, which seems shocking. It is such an obvious problem and all the bits and pieces exist separately, yet the path to integration redemption is littered with carcasses of startups and mature multinationals that have tried and failed. The market for whole-house system integration and automation is fragmented, as are standards. Plus the sales channels are wide and varied, a testament to the many ways such systems come to be in a house. This is a tough business challenge, but one that I hope will come along for the ride as energy efficiency, generation and storage innovations needing integration and automation flourish in the coming years.

One additional gap in today’s technology keeps my stitched-together Franken’home from getting off the operating table and really living: fire. I love fire. The ambiance and warmth it provides as an aesthetic design feature inside and outside is difficult to beat. More importantly, I love to grill. My dream home has an outdoor kitchen worthy of a Food Network television show, though it is covered. We are talking the Seattle area after all. Yet fire needs fuel, and fire fuel is neither renewable nor green. It’s a conundrum. On second thought, it’s not so much a technology gap as a personal problem. I am too unevolved to live without fire, but may be exactly unevolved enough to work for Geico Insurance.

Five Reasons to Embrace LED Street Lighting

Posted on December 21, 2017 by gonzorourke in Energy, Lighting

The verdict is in: LED street lighting is better! Many cities including San Jose[1] and Oakland[2], CA, Portland[3], OR and others[4] have commissioned independent, third party studies that have all reached the same conclusion – LED street lighting meets or exceeds existing street lighting technologies in terms of the amount and quality of light while simultaneously consuming much less energy.

Here are five reasons why LED is better, the cocktail napkin for LED street lighting:

1. Improved Visibility for Motorists and Pedestrians

Typical nighttime locomotion occurs with lighting in the Mesopic range, so it is important that luminous flux (lumens) and illuminance (lux) values are properly adjusted for the Mesopic range. Huh? Okay, remember those rods and cones you learned about in seventh grade science? They operate best at the wavelengths in the Mesopic range where LED lighting shines (pun intended.)

When you move from a brightly lit room in your home to a room with the lights off, it takes several seconds for your eyes to adjust. This adjustment time can be hazardous when piloting a multi-ton vehicle at 35 mph or higher. And yet the High Pressure Sodium (HPS) roadway lighting prevalent today creates just such a situation as you drive from a very bright spot under an HPS light into a dark spot between lights. This poor uniformity, where the difference in brightness between the brightest and dimmest spots is high, causes the human eye to continually and dangerously adjust, with each adjustment taking seconds. A lighting layout with LED lights optimized for human rods and cones and better uniformity – the difference between the brightest and dimmest spots is low – dramatically improves safety.

To be sure, it is still possible to create a poor layout with LED lighting, which is much more directional. Focusing on very high light levels with large separation between poles, combined with the less diffuse lighting of LED, can create uniformity on par with HPS lighting – which is to say dangerous – so good lighting design is still a prerequisite.

BUGs also play a role here, though not the ones that sacrifice themselves on the altar of your windshield, reducing visibility, or ruining a peaceful nighttime walk with their itchy insurgence. The Illuminating Engineering Society (IES) defines a different kind of BUG, one that stands for Backlight, Up-light and Glare. LED lighting is directional, much more so than other lighting sources like HPS. As a result, it goes where intended. Much less is wasted to backlight, up-light or glare, improving motorist and pedestrian safety.

2. Reduced Energy Consumption

With an LED street lighting system, improved visibility for motorists and pedestrians requires less energy. I know, seems like some fundament law of nature is being violated here, but it’s a true win-win. The wattage needed per LED light to deliver more effective illumination as described above is less than the wattage needed per HPS light today, or other types of lighting as well (e.g., Low Pressure Sodium, Metal Hallide, Mercury Vapor.) Reduced wattage over time means reduced energy consumption and a lower carbon footprint.

3. More Accurate Color Representation

Color is an important ingredient when determining what something is from behind the steering wheel, like slippery anti-freeze on the road ahead or a deer just off the shoulder. If natural daylight provides a color representation of 100, HPS lights provide a color representation of about 25 while LED lights are typically over 70, much closer to natural daylight and much easier to identify potential hazards.

4. Meets the Latest Lighting Standards

Many, perhaps even most, street lighting systems today meet no lighting standards whatsoever or meet lighting standards that are way out of date. While stepping up to an LED street lighting system saves money and improves the quality of light, it’s also the perfect time to come into compliance with the latest standards like ANSI/IESNA’s RP-8-05[1] standard for roadway and adaptive street lighting and the International Commission on Illumination’s CIE-191:2010[2] standard for Mesopic Photometry. Doing so capitalizes on many years of research into the safest and most economical way to provide street lighting.

5. Leverages Adaptability

Huge strides have been made these past five years in lighting control technology allowing street lighting system owners to modify light output in response to environmental conditions like surrounding levels of activity levels, local motion, other nearby sources of lighting, etc. This is called adaptive lighting. Adaptive lighting not only reduces energy consumption further through the use of dimming, but also prevents over-lighting, reduces glare and minimizes light pollution. In other words, it helps deliver just the right amount of light when and where it’s needed most.