Between the Poles

Microgrid technology might have prevented the Fukushima Daiichi disaster

As readers of this blog might remember, I began following the Fukushima Daiichi and Daiini events as they unfolded starting on March 11, 2011.  The disaster at Fukushima Daiichi occurred because of the lack of external power to the plant to keep cooling processes operating.  While external power was restored to Fukushima Daiini within hours preventing a major disaster at that plant, it took weeks to restore external power to Fukushima Daiichi. 

Microgrids might be a way to help prevent this kind of disaster in the future.  Navigant Research has just released a report on what it calls  Community Resilience Microgrids (CRMs) which  Navigant defines as microgrids that  provide emergency power services to communities rather than private sector end users, national security critical infrastructure assets such as military bases, or for overall grid reliability.  The focus in the Navigant report is on microgrids for resilence and community.  Another differentiator is that the CRM segment is being stimulated by specific government programs that are providing funding and regulatory support.  The Navigant research is centered on recent programs and projects specifically linked to resilience in communities in light of recent natural and man-made disasters such as Hurricane Sandy in the United States and the Fukushima Daiichi disaster in Japan.

CRMs are an interesting segment of the microgrid market.  Navigant's perspective is that CRMs represents an emerging market opportunity, but  that there are important challenges including regulatory inhibitors and an uncertain business model.  Communities are interested in CRMs because for energy resilience they represent an alternative to their local utility.  Utilities may perceive CRMs as a threat because they  potentially could mean losing customers and revenue.

Navigant forecasts that the CRM "implementation revenue", which will amount to about $160 million in 2015, will reach $1.4 billion by 2024. The United States currently leads in terms of policy and technology innovation, but Navigant projects that the Asia Pacific region will become the largest market share due to government programs in place in Japan and China. By 2024 Asia Pacific is projected to be roughly half of the total CRM market.

EPRI's Smart Grid Demonstration Project reveals value of volt-var control

Conservation voltage reduction (CVR) or volt-var is an approach to demand response (DR) and energy efficiency (EE) that can provide major benefits without significant alterations to the power distribution system,  unlike other DR/EE approaches.  Volt-var is used to reduce demand and energy consumption during peak load when electricity prices are inflated and demand may exceed the available energy while maintaining customer voltage power quality according to tolerances mandated by the regulator to protect consumer and utility devices.  Peak demand can be reduced typically by 2 to 4 %.  The business benefits are a greater percentage of energy delivered to paying customers, reduced investment in peaking generation plants or in buying power from generators at peak market prices, and a reduction in the environmental impact of energy delivery (reduced emissions).

For the past seven years the Electric Power Research Institute (EPRI) has been leading a smart grid demonstration project initiative that includes regional demonstrations and supporting research focusing on smart grid activities related to integration of distributed energy resources (DER) including distributed generation, storage, renewables, and demand response technology. A number of well-known electric power utilities have participated in this program by developing and reporting on smart grid demonstration projects.

1. AEP Smart Grid Demonstration
2. Con Edison Smart Grid Demonstration
3. Duke Energy Smart Grid Demonstration
4. EDF Smart Grid Demonstration
5. Ergon Energy EPRI Smart Grid Demonstration
6. ESB Smart Grid Demonstration
7. Exelon (ComEd/PECO) Smart Grid Demonstration
8. Hawaiian Electric Company (HECO) Smart Grid Demonstration Project
9. FirstEnergy Smart Grid Demonstration
10. Hydro Quebec Smart Grid Demonstration
11. KCP&L Smart Grid Demonstration
12. PNM Smart Grid Demonstration
13. Sacramento Municipal Utility District Smart Grid Demonstration     
14. Southern California Edison Smart Grid Demonstration
15. Southern Company Smart Grid Demonstration

As an example, AEP's smart grid demonstration project is based on a 10,000 customer pilot that includes smart meters, communications, end-use tariffs and controls, and distribution automation and volt/var control. It integrates other distributed and end-use technologies that are being evaluated by AEP including four MW scale sodium sulfur battery installations, two 70-kW roof-top photovoltaic systems, a new 5.7 kW concentrating solar technology, three 60 kW natural gas-fired reciprocating engines capable of combined heat and power generation, two plug-in hybrid electric vehicles, a large air conditioning system, two 10 kW wind turbines, and several 25 kW community energy storage systems (CES).

Currently a significant amount (about 10 %) of electric energy produced by power plants is lost during transmission and distribution to consumers. About 40 % of this total loss occurs on the distribution network. 

In a recent blog, Jared Green, Project Manager for EPRI's Smart Grid Demonstration Initiative reported a surprising finding from the Initiative.  Through the Smart Grid Demonstration Initiative EPRI found that volt-var control was was one of the most effective technologies in reducing energy demand. EPRI reported that most of the utilities that ran demonstration projects had already deployed or were deploying volt-var technologies to optimize their distribution grids. Results from the demonstration projects showed that a significant reduction in energy demand could be  achieved. EPRI's analyses showed that for each 1 %  reduction in voltage a corresponding 0.4-0.7 % reduction in energy demand was achieved. 

For utilities that used volt-var control for targeted demand reduction, volt-var can reduce peak demand as well.  Duke Energy, for example, reported reducing peak demand by about two hundred megawatts (MW) during the 2014 cold period in the Eastern U.S.  It has been estimated that in the U.S. with every one percent reduction in peak demand there would be a reduced need to build a 7,900 MW power plant.

Even greater control and reduced risk can be achieved by Integrating volt-var with advanced metering infrastructure (AMI) and GIS.  Volt-var/AMI/GIS provides greater precision in managing voltage reduction. At Distributech 2014, Tantalus reported using GIS is to produce voltage maps. Voltages reported by smart meters can be mapped geographically in real-time across the entire distribution network in the form of isovolt maps. This makes it possible to rapidly identify areas of low voltage and correct them in real time.

Google deprecates enterprise products Google Earth Enterprise, Google Maps Engine

A blog post has been posted by Harsha Vardhan about Google's plans for retiring its enterprise geospatial products.  According to Harsha the Maps Business Unit of Google, which provides mapping services consumers and businesses, is moving forward with a different strategy with respect to enterprise users. As part of this strategy,  Google is deprecating Google Earth Enterprise, Google Maps Engine and Google Maps Coordinate.  The dates when these geospatial products are to be shut down are listed below.  Google has deprecated other geospatial products in the past such as Google Earth API, Google Maps Geocoding API and Google Maps Javascript API.

Product	Supported till
Google Earth Enterprise	December 12, 2015
Google Earth API	December 12, 2015
Google Maps Engine	January 29, 2016
Google Maps Coordinate Product & API	January 21, 2016

Harsha's blog post provides insightful speculation as to Google's reasons for terminating these products. 

Dale Lutz points out that ESRI appears to be working with Google to take on Google's enterprise customers. According to ESRI's Google relationship page: "Google and Esri are working closely together to provide replacement software and training to all of Google's enterprise customers and partners that have implemented Google Earth Enterprise and Google Maps Engine technology. Esri will be providing the new 10.3 version of ArcGIS for Server and related client/app technology to all Google Earth Enterprise and Google Maps Engine customers and partners.”

Augmented reality standard adopted by OGC

The Open Geospatial Consortium (OGC) has approved the Augmented Reality Markup Language 2.0 Interface Standard (ARML 2.0).  ARML 2.0 provides a free and open, non-proprietary encoding that content providers can use to specify the location and visual appearance of real world objects and virtual objects in an augmented reality scene. Additionally, ARML 2.0 defines a Javascript interface for communicating how user input selects, queries and dynamically changes the properties of these virtual objects.

Augmented reality involves a smartphone or a tablet that has a screen, camera, GPS and an accelerometer that detects camera motion and orientation.  The real world "background" is comprised of data, including location, of real world objects or visible objects .  For example, in the context of construction virtual objects representing the design of a new building or new infrastructure or a 3D model of underground infrastructure can be superimposed on a map showing existing conditions or a map of surface structures such as roads and buildings.  The augmented reality application superimposes the virtual design objects or the underground infrastructure on the map of existing objects or the surface map.  (Image showing 3D model of Las Vegas underground infrastructure from VTN).

First online course for BIM-integrated energy modeling for buildings

Energy performance modeling for buildings is a new field, but one that is getting a lot of interest under the impetus of government mandates and incentives.  It's so new that there is no set of standard best practices.  Energy modelers are having to make it up as they go.   But this is beginning to change.  Trailloop has just released an online course for BIM-Integrated Energy Modeling for buildings.  The course was created by Jean Carriere who is one of the early pioneers in applied energy performance modeling.  Jean has been working commercially in this very new field for about 5 years.  Jean also teaches BIM modeling at a local community college.

In the United States according to the Environmental Protection Agency (EPA), buildings are responsible for 65 % of electricity consumption.  An important motivation for energy efficient buildings in many jurisdictions are aggressive building codes that push energy efficiency.   For example, the 2013 California Green Building Standards Code (Title 24) is one of the first “green” building codes.   Other motivations are customer driven certification such as LEED and other "green" certification - LEED v4 incorporates up to 18 credits for demand response -  and financial incentives from local governments and power utilities to reduce energy consumption, peak load or both. Government mandates for zero energy buildings (ZEB) have been introduced in E.U., the U.S. and Japan.   According to Navigant Research, global ZEB revenue is expected to grow from $629.3 million in 2014 to $1.4 trillion by 2035.

Energy performance modeling is an essential tool for estimating the energy requirements of a new or existing building.  An energy performance analysis allows you to determine how much energy your building will consume in a year, assess the most cost effective insulation and glazing, and assess other things that you can do as part of the building design to optimize energy usage.  An energy analysis requires a lot of data - geometry of the building, performance characteristics of materials, geolocation and orientation of the building, and so on.  Simulation applications allow you to include local environmental conditions and conduct thermal modeling, daylight and airflow simulations.  Thermal modeling includes energy consumption, thermal comfort, CO₂ emissions, renewable energy integration, and electric power load. Natural lighting includes visual comfort (glare) and the reduction of energy use through natural lighting.  Airflow simulation includes external wind simulation, internal airflow simulation, clean room ventilation, and reduction in electrical load as a result of using natural ventilation.

There are many energy analysis tools available (lighting, thermal, emissions, water usage, etc) , many are very complex, and the volume of data that are required is increasing exponentially.  Many energy modelers follow a best-of-breed approach so interoperablity is a major challenge in improving productivity in energy performance analysis.

Increasingly for energy modelers the natural place to start is with a Building Information Model (BIM).  There are several reasons for this.  First of all it is what many of the energy performance analysis packages expect and it is supported by the gbXML standard.  Secondly it allows all the information required by the architect, engineers and construction contractors to be accessed in one place.  And thirdly it helps in communicating the results of the energy performance analysis to the people who need it including heating and cooling, lighting and other types of engineers, all  of whom may require the same  information but communicated in different ways.

In most projects the energy modeler is brought in after the building has been designed.  If the building was designed using BIM,  the starting point is the architect's BIM model and an associated database containing information about elements of the building.  Otherwise it is necessary to start with paper drawings and generate the BIM model from scratch.  In addition the geolocation and orientation of the building and local environmental conditions are required.  The first thing the energy modeler does is to create a parallel BIM model, which is a simplified model derived from the architect's BIM model that contains the key elements that are required for the energy analysis such as simplified walls and floors, room bounding elements, complete volumes, and window frames and curtain walls.  The simplified model is exported as a gbXML file and imported into an energy analysis package.   The energy performance application is used to run a simulation or several simulations if the energy modeler is asked to consider alternative designs.  Finally, a visualization showing energy consumption using the BIM model is used to communicate the results of the analyses.

The Trailloop course covers the energy performance modeling workflow in detail including creating the BIM model, exporting it as a gbXML file,  importing the gbXML file into an energy performance package which performs the analysis, and then exporting the results back to the BIM model.  In the Trailloop course industry standard tools are used: Revit for BIM modeling (a free version is available for students) and IES VE for building energy modeling (a special low price is available for students).

In his commercial practice, Jean has focused on optimizing the energy modeling workflow so that starting from paper architectural drawings, he can develop the BIM model, compile energy performance parameters, generate a gbXML file, and conduct a complete energy analysis (daylighting, thermal analysis, etc) for the proposed building in as little as two weeks, and then provide weekly performance feedback from design changes​.

Course description

BIM-Integrated Energy Modeling

The BIM-Integrated Energy Modeling Online Course is the most competitive and time-efficient workflow because it avoids rework through integration during the design process, providing an early feedback of LEED credits.

Students learn about the foundations of Integrated Modeling for a seamless integration into the Virtual Environment’s energy modeling application by using a Revit model, and then gain practical experience in solving complex design integration problems. Model elements are precisely placed using a standard set of modeling rules to ensure a predictable quality. Input data is associated with spaces and zone for thermal template data integration through schedules. Techniques are given to troubleshoot and mitigate all errors from the building geometry in order to apply an accurate building envelope.

Once the building geometry is integrated, students learn how to perform early-stage energy simulations to generate preliminary results on energy performance for various systems. They will be able to edit the building geometry and add new forms to the energy model in order measure the impacts of the added building elements. After producing a building loads report, techniques are given to reduce the load to right-size mechanical equipment.

Learning objectives

1. Construct building geometries in Revit for a seamless integration into IES VE for energy modeling.
2. Update the building geometry from design changes and re-integrate it back into the energy model.
3. Select appropriate energy modeling input data for building constructions, space types and HVAC systems.
4. Describe the differences observed between a baseline run and an energy efficient case for peak heating and cooling load reductions.
5. Display the energy/load difference between the baseline run and the energy efficient case using charts, graphics and tabular data.

U.S. FCC adopts new rules to protect net neutrality

February 26, 2015 the U.S. Federal Communications Commission (FCC) adopted new rules  to protect net neutrality.  This is in response to a court decision in April 2010, when the U.S. Court of Appeals for the D.C. Circuit decided that the Federal Communications Commission (FCC) did not have the authority to impose net neutrality regulations on Internet providers.  The decision was made in the context of a court case against Comcast for throttling certain internet applications.

The new rules reclassify broadband Internet access service as a telecommunications service under Title II of the Communications Act of 1934. Title II applies to "common carriers" which in 1934 meant telephone companies providing voice communications.  It explicitly prevents common carriers from discriminating among users to “make any unjust or unreasonable discrimination in charges, practices, classifications, regulations, facilities, or services.”  The new rules also cite Section 706 of the Telecommunications Act of 1996, which a court has interpreted as  an independent grant of authority to the FCC that supports the adoption of open Internet rules. The new rules apply to both fixed and mobile (wireless) broadband service.  Net Neutrality has been strongly supported by the Obama administration and content providers like Google.

Referred to as "Bright Line Rules", the new rules specifically prohibit blocking, throttling, and paid prioritization by broadband providers.

No Blocking

A person engaged in the provision of broadband Internet access service shall not block lawful content, applications, services, or non-harmful devices, subject to reasonable network management.

No Throttling

A person engaged in the provision of broadband Internet access service shall not impair or degrade lawful Internet traffic on the basis of Internet content, application, or service, or use of a non-harmful device, subject to reasonable network management.

No Paid Prioritization

No “fast lanes”.  Broadband providers may not favor some lawful Internet traffic over other lawful traffic in exchange for consideration of any kind.

The Open Internet Rules and Order can be found here.

INSPIRE-Geospatial World Forum 2015 program released

INSPIRE-Geospatial World Forum 2015, a joint conference organized by the European Commission and Geospatial Media and Communications, has made available its full conference program. Almost 500 presentations are scheduled on topics including building information modelling (BIM), open data, big data analytics, open standards, linked data, cloud computing, crowdsourcing, Earth observation, indoor positioning, land information systems for smart cities, urban resilience and sustainability, health, agriculture and others.  Some 2000 delegates are expected to attend from more than 80 countries.  Top sponsors include Trimble, Topcon, ESRI, Digital Globe, Oracle and Bentley.

The theme of the conference is CONVERGENCE: Policies + Practices + Processes via PPP with a focus on improving coordination among policy-makers, technology providers and users.  Including geospatial data and technology in construction, agriculture, health and other industry workflows is an enabler for more successful public–private partnerships (PPP) by facilitating more informed decision making among the stakeholders.

GeoWave aims at linking popular geospatial tools to "big data" technology

A very exciting project has been proposed at LocationTech (it's in the Project Proposal Phase as defined in the Eclipse Development Process).  Simply put, GeoWave intends to do for "big data" databases (initially Apache Accumulo) what PostGIS does for SQL databases (PostgreSQL).  GeoWave is open source software (licensed under Apache 2.0) that adds support for geographic objects, multi-dimensional indexing and geospatial operators to Apache Accumulo.  

NoSQL databases

To deal with data volumes that are too large for traditional SQL databases, beginning in 2004 Google developed "BigTable" which is a compressed, high performance, and proprietary data storage system built on the Google File System that is used by a number of Google applications including Google Maps.  Apache Accumulo is a distributed database that is based on Google's BigTable design and is built on top of Apache Hadoop and other Apache projects.  For putting geospatial data into a key/value store like Accumulo the key concept is that of the "geospatial hash" which converts a 2D, 3D or 4D coordinate such as a lon and lat, lon, lat and elevation or a lon, lat, elevation, and time to an integer index, such as a quadtree or R-Tree index, that can be used to order and rapidly retrieve spatial data.  GeoWave means that you can manage massive amounts of geoinformation in key/value databases such as Accumulo and take advantage of programs such as MapReduce which Accumulo uses for distributed processing.

Connecting Accumulo to GeoServer, GeoTools, and PDAL

In addition GeoWave includes a GeoServer plugin to enable geospatial data in Accumulo to be shared and visualized via GeoServer OGC standard web services. It provides plugins to connect the popular geospatial toolset GeoTools and the point cloud library PDAL to an Accumulo based data store. The PDAL plugin makes it possible to interact with point cloud data in Accumulo through the PDAL library.
 
The GeoWave project Work plans to extend the same geospatial capabilities to other distributed key-value stores in addtition to Accumulo.  The next data store will be HBase.  It also will support other geospatial frameworks in addition to GeoTools/GeoServer.  Mapnik is the next geospatial framework targeted for GeoWave support.  GeoWave says it is very interested in GeoGig and support for this geospatial data versioning library is currently on their backlog.  GeoGig takes the concepts used in distributed version control such as Git and applies them to versioned spatial data.

Background
 
GeoWave was developed at the National Geospatial-Intelligence Agency (NGA) in collaboration with RadiantBlue Technologies and Booz Allen Hamilton.  The NGA released GeoWave under an open source license in June, 2014. The primary goal of GeoWave is to bridge the gap between well-known geospatial projects such as GeoTools and distributed databases.

I blogged previously about GeoMesa, the first LocationTech project that aims at providing a foundation for storing, querying, and transforming spatio-temporal data in Accumulo.  It implements interfaces that enable Geoserver and other Geotools projects to use Accumulo as a data store.

Convergence of BIM and geospatial contributes to better management of information

Dr Anne Kemp, Director and Fellow, Atkins, Vice-Chair of BuildingSmart, UK, Chair of ICE BIM Action Group, and Chair of BIM4Infrastructure UK, has published very thought-provoking insights into how the convergence of BIM and geospatial can contribute to the better management of information to help generate the understanding to make better decisions.

Her first assertion “So, let’s put paid to the hang-ups of what is and is not GIS and BIM, and discover what really deserves our focus” is a very good place for all of us to start if we are going to tear down the discipline boundaries that are inhibiting us from moving to a more holistic approach to problem solving in the era of smart cities.

Better outcomes, not BIM or geospatial

Her goal is not to support BIM or geospatial per se, but to use these technologies to improve outcomes.  From Anne's perspective the key outcomes we should be aiming at are

• CLARITY - Clarity of delivery
• TECHNICAL JUDGEMENT - Converging information production with sound engineering judgment and design
• ACCESS - Wider, faster access to comprehensible and integrated information
• LATERAL THINKING - Enabling reflective, adaptive thinking to incorporate whole life and integrated systems approach within the wider geographic context
• INNOVATION - Harnessing innovative technologies and harvesting intelligence from big data
• DECISIONS - Fostering instinctive, but rigorous collaboration and better decision making

Data, not documents

The construction industry is based on documents such as drawings. Documents lock data up within a discipline and prevents the wider access that can be used to build up an integrated view of an asset. In contrast digital data can be used, many times, for different purposes, by different disciplines.  This requires interoperability and the ability to map semantics across different disciplines.

Assets, not projects

The full lifecycle view of a building, road or airport requires thinking of assets not projects. Anne's perspective is that this is where the convergence of BIM with geospatial provides the biggest benefits. The UK government would agree. The short term objective of the UK Government BIM mandate is to reduce the cost of construction (design, tender, build) by 20%.  The longer term objective is by 2025 to reduce the costs associated with designing, building, operating and maintaining buildings and infrastructure by a third.  ‘In-use’ data from facilities management (FM) systems, building management  systems, and sensors including smart phones provides information on how an asset is actually serving the needs of people, and the patterns of behaviour of people using the infrastructure.  This information can be used to optimize building or infrastructure design. A geospatial perspective enables this data to be used not only with individual buildings or infrastructure, but for a whole neighbourhood, town or city.

Data ethics

Ensuring that data is not manipulated to distort decision making is critical to enabling the true data-driven organization of the future. Anne's perspective is that the industry is becoming increasingly dependent on data management professionals. This will require standards and a code of ethics to address challenges of privacy, distortion, and manipulation so as to ensure that data is made available in a way that aids rather than confuses decision making. In the future chief data officers and other information professionals will have even much greater responsibilities - they will be responsible for specifying, collecting, and analyzing the information for decision making that will be critical to the organization's success, even its existence.

Information is not understanding

Malcolm Gladwell in "Blink" points out that “We live in a world saturated with information. We have virtually unlimited amounts of data at our fingertips at all times, and we’re well versed in the arguments about the dangers of not knowing enough and not doing our homework. But what I have sensed is an enormous frustration with the unexpected costs of knowing too much, of being inundated with information. We have come to confuse information with understanding.”

At a recent BIM conference the term “infobesity” came up more than once. A decade ago people were concerned about not having enough data to make informed decisions. Now that we have more data being collected by sensors such as smart meters and smart phones, the problem is how do we make sense from the huge volumes of data that all these smart devices are collecting.

Anne makes the point that when managed correctly, “instant” decisions based on a small amount of data are not just as good, but can be better than those made after analyzing all available data. The "less is more" challenge is to distill the data to just the right subset to enable you can make better decisions faster with less data. Anne believes that this will require more sophisticated visualization techniques to enable insights from patterns in large amounts of data and better collaboration technology to enable a large number of individuals from different disciplines to understand each other (even when using different terms for the same piece of equipment or construction material) and to collaborate fruitfully.

This means that we will be asking our human or computer information  engineers to deliver that essential subset of information to the right people at the right time, and in an intuitively understandable way.  Anne suggests that our cartographic and GIS heritage of creating, analyzing and visualizing a view of the physical world as maps may provide a model for future data managers.  But, as Anne points out, this will have to be transformed for a virtual environment.

Unintended consequences

Anne's final point is often overlooked. BIM, geospatial, augmented reality and other technologies are transforming how we view "reality".  There are very real consequences for people working in a virtual world. Anne mentions the first case of internet addition disorder (IAD) involving Google Glasses on October 14, 2014 and asks how many of us are already there with our smartphones and tablets ?