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Journal Paper Accepted: The need for holistic enterprise control assessment methods for the future electricity grid

The LIINES is happy to announce the publication of the journal article The need for holistic enterprise control assessment methods for the future electricity grid, by Prof. Amro M. Farid (Dartmouth), Bo Jiang (MIT), Aramazd Muzhikyan (Dartmouth), and Prof. Kamal Youcef-Toumi (MIT) in the journal Renewable and Sustainable Energy Reviews.

In this comprehensive literature-based study, the LIINES presents a logical case for integrating power grid assessment methods into a holistic enterprise control framework.  Such a framework is explicitly techno-economic and merges methods power systems engineering and economics.   To support the argument, the LIINES has conducted the most comprehensive review of renewable energy integration studies completed to date.

The paper discusses the need for change in the assessment of the electricity grid as a result of five driving forces.  The driving forces are identified as: decarbonization, growth of electricity demand, transportation electrification, electric power deregulation, and increasing numbers of responsive (“smart”) consumers.  These five drivers require the steadily increasing penetration of solar and wind generation as well as evolving capabilities to support demand side management for the tremendous diversity of loads that connect to the electrical grid.  The integration of these three new grid technologies of renewable energy, electric vehicles, and demand side resources ultimately imposes fundamental changes to the grid’s structure and behavior.

The paper argues that the future electric grid’s needs for reliability, cost efficiency and sustainability necessitates a holistic assessment approach.  Figure 1 shows a guiding structure that leads to five techno-economic control objectives.  This work also uses five lifecycle properties to integrate rather than decompose the engineering design.  The lifecycle properties core to the power grid are dispatchability, flexibility, forecastability, stability, and resilience. The use of these five properties avoids overlap in function of solutions.

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Figure 1: Guiding Structure of Argument

Using such a holistic paradigm for techno-economic assessment, the journal paper conducts the most comprehensive review of renewable energy studies completed to date. It found several limitations to the existing renewable energy integration studies. Firstly, in order to address the holistic nature of the power grid, the real potential of demand side resources needs to be included. Additionally, for power grid balancing, validated simulations rather than statistical methods based on questionable assumptions need to be used.  Furthermore, the consistency between future development of the real market structure and modeling methods needs to be assured. Finally, the investment costs related to the support of the future power grid need to be considered in simulation.

Thus, the paper concludes based on the defined model requirements and the assessment of the current literature, that a framework for holistic power grid enterprise control assessment needs to satisfy the following requirements:

  1. Allows for an evolving mixture of generation and demand as dispatchable energy resources
  2. Allows for an evolving mixture of generation and demand as variable energy resources
  3. Allows for the simultaneous study of transmission and distribution systems
  4. Allows for the time domain simulation of the convolution of relevant grid enterprise control functions
  5. Allows for the time domain simulation of power grid topology reconfiguration in operation time scale
  6. Specifically addresses the holistic dynamic properties of dispatchability, flexibility, forecastability, stability, and resilience
  7. Represents potential changes in enterprise grid control functions and technologies as impacts on these dynamic properties
  8. Accounts for the consequent changes in operating cost and the required investment costs.

These requirements have been realized in a power grid enterprise control simulator that was used for an extensive study of renewable energy integration in the power grid [Link 1], [Link 2].  The simulator includes the physical electrical grid layer and incorporates primary, secondary, and tertiary control functions. This model fits the requirements of the holistic enterprise control method as defined previously.

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 Figure 2: The Enterprise Control Power Grid Simulator

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Journal Paper Accepted at Applied Energy – Demand Side Management in Power Grid Enterprise Control: A Comparison of Industrial & Social Welfare Approaches

The LIINES is happy to announce that our recent paper entitled: Demand Side Management in Power Grid Enterprise Control: A Comparison of Industrial & Social Welfare Approaches, has been accepted to the Applied Energy Journal. This study comes as a result of collaboration between three universities; MIT, Masdar Institute, and Dartmouth. The work is authored by Bo Jiang (MIT), Aramazd Muzhikyan (Masdar Institute), Prof. Amro M. Farid (Dartmouth) and Prof. Kamal Youcef-Toumi (MIT).

Demand response is an integral part of a reliable and cost-effective power grid.  As wind and solar energy become two important power generation sources that reduce CO2 emissions and ensure domestic energy security, their intermittent and uncertain nature poses operational challenges on the electrical grid’s reliability. Instead of relying solely on dispatchable generation, power grid operators, called ISOs, are adopting Demand Response (DR) programs to allow customers to adjust electricity consumption in response to market signals. These DR programs are an efficient way to introduce dispatchable demand side resources that mitigate the variable effects of renewable energy, enhance power grid reliability and reduce electricity costs. Fortunately, the U.S. Supreme Court’s recent ruling Federal Energy Regulatory Commission vs. Electric Power Supply Association, has upheld the implementation of Demand Response allowing its role to mature in the coming years.

Despite the recognized importance and potential of DR, the academic and industrial literature have taken divergent approaches to its implementation. The popular approach in the scientific literature uses the concept of “Transactive Energy” which works much like a stock market of energy; where customers provide bids for a certain quantity of electricity that they wish to consume. Meanwhile industrial implementations (such as those described by FERC order 745) compensate customers according to their load reduction from a predefined electricity consumption baseline that would have occurred without DR. Such a counter-factual baseline may be erroneous. At the LIINES, we have rigorously compared the two approaches. Our previous journal paper published at Applied Energy “Demand side management in a day-ahead wholesale market: A comparison of industrial & social welfare approaches” conducted the comparison in a day-ahead wholesale market context.  It showed, both analytically and numerically, that the use of power consumption baselines in demand response introduces power system imbalances and costlier dispatch.

Our recent paper now expands the analysis from a single day-ahead electricity market to the multiple layers of wholesale markets found in many regions of the North American power grid. This holistic analysis includes the day-ahead, real-time, and ancillary service markets. The integration of these multiple layers of power system operations captures the coupling between them and reveals the the impacts of DR implementation over the course of a full-day with a granularity of tens of seconds. The paper quantifies both the technical and economic impacts of industrial baseline errors in the day-ahead and real-time markets, namely their impacts on power system operating reserve requirements, operating costs and market prices.

The paper concludes that the presence of demand baseline errors – present only in the industrial implementaiton – leads to a cascade of additional system imbalances and costs as compared to the Transactive Energy model. A baseline error introduced in the day-ahead market will increase costs not just in the day-ahead market, but will also introduce a greater net load error residual in the real-time market causing additional costs and imbalances. These imbalances if left unmitigated degrade system reliability or otherwise require costly regulating reserves to achieve the same reliability.

Figure 1: Cascading Cost Increase of Demand Response Baseline Errors in Day-Ahead Energy Market

An additional baseline error introduced in the real-time market further compounds this cascading effect with additional costs in the real-time market, amplified downstream imbalances, and further regulation capacity for its mitigation.

Figure 2: Cascading Cost Increase of Demand Response Baseline Errors in Real-Time Energy Market

Based on these results, the potential for baseline inflation should be given attention by federal energy policy-makers. The effects of industrial baseline errors can be mitigated with effective policy. As a first solution, ISOs could calculate demand response baselines using the same methods of load prediction normally used in energy markets. Such an approach leaves less potential for baseline manipulation. A more comprehensive solution to this problem will be the upcoming trend of transactive energy and would eliminate the concept of baselines and their associated uncertainties entirely.

In depth materials on LIINES smart power grid research can be found on the LIINES website.

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Prof. Amro M. Farid contributes to World Wind Energy Association Report

The World Wind Energy Association (WWEA) technical committee has recently published a report entitled “Wind Energy 2050: On the shape of near 100% RE grid”, which studies the challenges of wind energy integration into the power grid and discusses some of the solutions to address these challenges. Chapters 5 and 6 of this report are based upon the work of Dr. Amro M. Farid and discuss the evolution the power grid as it accommodates increasing capacities of wind energy.

Wind and solar energy have already become mainstream energy sources in some regions of the world. While the integration of wind energy has numerous benefits, it also creates new challenges for power system operations. Wind energy is inherently variable and, in order to successfully accommodate it, the power system has to undergo a dramatic change.   Furthermore, and in contrast to the traditional thermal generation units, wind energy sources are non-dispatchable in the traditional sense, meaning their outputs cannot be set to the desired value. As a result, the integration of wind energy requires new approaches to power grid planning and management, including investments into improved wind forecasting techniques and reconsidering operating reserve requirements.

A conventional power system consists of relatively few centralized and dispatchable generation units, and a large number of distributed and stochastic (but accurately forecastable) loads. The electricity is delivered from the centralized and predominantly thermal power plants to the distributed electrical loads. During many decades of operations, power system operators and utilities have developed improved methods for performing their tasks. Generation scheduling and dispatch, reserve management and control technologies have matured. Load forecasting accuracy has improved significantly, reducing forecast errors to as low as a few percent. Power system security and reliability standards have also evolved accordingly.

Six key drivers currently govern the evolution of the grid, namely environment protection, reliability concerns, renewable energy integration, transportation electrification, consumer participation and power market deregulation. This evolution will lead to a diversification of the power grid energy portfolio to include more solar, wind, energy storage and demand-side resources. Thus, the newly emerging operation procedures will not only engage with generators but also with consumers and other ancillary units. As a result, the already existing control technologies and procedures will expand significantly in both number and type.  This will challenge the basic assumptions of power system design and operations. Therefore, the question is not how to mitigate wind variability, but rather how the power grid should evolve to successfully accommodate a high penetration of wind energy.

Governed by these drivers, power system generation and consumption will evolve towards more equal roles in grid operations.  First, from the perspective of dispatchability, wind energy sources resemble traditional consumption in that they are non-dispatchable and forecasted. On the other hand, the introduction of demand response creates makes some portion of the energy consumption dispatchable much like traditional power generation facilities. These two trends change the balance of dispatchability and forecastability as shown in Table 1. Second, the integration of wind energy, like most renewable energy sources, changes the spatial distribution of the generation. Wind energy sources can vary from several kWs to hundreds of MWs.  While larger facilities will continue to be installed centrally into the transmission system, the smaller facilities will be installed at the power grid periphery as distributed generation.  (See Figure 2).  This creates the potential for upstream flow in the distribution system, which was not generally allowed before, and requires the redesign of the protection system accordingly.

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Table 1: Future grid generation and demand portfolio

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Figure 2: Graphic representation of the evolving power grid structure

While many power grid phenomena overlap, the literature has traditionally treated them strictly separately. The evolution of the power grid necessitates reconsidering the distinction between  timescales.   It also requires revisiting the distinction between the transmission and distribution systems. In advocating for power grid enterprise control, our work encourages holistic approaches that work across time scales as well as the fully supply chain of electricity including both the transmission as well as the distribution system.

This work also moves away from the traditional classification of technical and economic control objectives and utilizes the concept of integrated enterprise control as a strategy for enabling holistic techno-economic performance of wind integration. As shown in Figure 3, the power system is modeled as a cyber-physical system, where the physical integration of wind energy and demand-side resources must be assessed in the context of the control, automation, and information technologies. The horizontal axis represents the energy value chain from the generation to the consumption. Finally, the third axis classifies both the generation and the consumption into dispatchable as well as stochastic units. This graph represents the scope of the power system that must address a complex mix of technological, system and societal objectives.

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Figure 3: Electrical power grid as a cyber-physical system

This work also moves away from the traditional classification of technical and economic control objectives and utilizes the concept of integrated enterprise control as a strategy for enabling holistic techno-economic performance of wind integration. As shown in Figure 3, the power system is modeled as a cyber-physical system, where the physical integration of wind energy and demand-side resources must be assessed in the context of the control, automation, and information technologies. The horizontal axis represents the energy value chain from the generation to the consumption. Finally, the third axis classifies both the generation and the consumption into dispatchable as well as stochastic units. This graph represents the scope of the power system that must address a complex mix of technological, system and societal objectives.

In depth materials on LIINES smart power grid research can be found on the LIINES website.

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Journal Paper accepted at IEEE Transactions on Industrial Informatics – An Axiomatic Design of a Multi-Agent Reconfigurable Mechatronic System Architecture

The LIINES is pleased to announce the acceptance of the paper “An Axiomatic Design of a Multi-Agent Reconfigurable Mechatronic System Architecture” to the IEEE Transactions on Industrial Informatics. The paper is authored by Prof. Amro M. Farid and Prof. Luis Ribeiro.

Recent trends in manufacturing require production facilities to produce a wide variety of products with an increasingly shorter product lifecycle. These trends force production facilities to adjust and redesign production lines on a more regular basis.

Reconfigurable manufacturing systems are designed for rapid change in structure; in both hardware and software components to address the required changes in production capacity and functionality.

Qualitative methods have recently been successful in achieving reconfigurability through multi-agent systems (MAS). However, their implementation remains limited, as an unambiguous quantitative reference architecture for reconfigurability has not yet been developed.

A design methodology based on quantitative reconfigurability measurement would facilitate a logical, and seamless transition between the five stages of the MAS design methodology, as shown below.

DesMethodology

Previous work on the reconfigurability of automated manufacturing systems has shown that reconfigurability depends primarily on architectural decisions made in stages 1, 2, 3, and 5. Operational performance of the manufacturing system after the reconfiguration is also important, but is often overlooked by the existing literature. As a result, it’s not clear:

  1. The degree to which existing designs have achieved their intended level of reconfigurability.
  2. Which systems are quantitatively more reconfigurable.
  3. How these designs may overcome their inherent design limitations to achieve greater reconfigurability in subsequent design iterations.

In order to address the previously mentioned issues with existing design methodologies, this paper develops a multi-agent system reference architecture for reconfigurable manufacturing systems driven by a quantitative and formal design approach, directly in line with the above Figure.

The paper uses Axiomatic Design for Large Flexible Engineering Systems to support a well-conceptualized architecture, which is necessary for excellent production system performance. Additionally, Axiomatic Design highlights potential design flaws at an early conceptual stage. This results in the first formal and quantitative reference architecture based on rigorous mathematics.

About the Author

Wester C.H. Schoonenberg completed his B.Sc. in Systems Engineering and Policy Analysis Management at Delft University of Technology in 2014. After his bachelors’ degree, Wester started his graduate work for the LIINES at Masdar Institute, which he continues as a doctoral student at Thayer School of Engineering at Dartmouth College in 2015. Currently, Wester is working on the integrated operation of electrical grids and production systems with a special interest in Zero Carbon Emission Manufacturing Systems.

A full reference list of LIINES publications can be found here:
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Mendeley @ the LIINES

Reference management is a key competence in any research group or laboratory.   Think of a research workflow.

  1. Get papers
  2. Get paper reference information
  3. Read them from anywhere in the world.  Take notes.
  4. Share them with colleagues
  5. Do the research – referring to papers as required.
  6. Cite the papers easily in any document preparation system.
  7. Build the reference list easily and accurately.
  8. Be ready to change the reference list in subsequent revisions.
Reference management supports all steps of the research flow and can save dozens of hours for any given paper.  This compounds with the numbers of papers that are produced every year and the number of researchers and collaborators with whom you work.  Despite the associated controversies  journal editors and academic departments will continue to increasingly use bibliometric analysis in key decisions.  Therefore, systematic approaches to reference management is even more necessary.
At the LIINES, we use Mendeley in 2011 after a migration from EndNote.  While EndNote had been the default reference management software for many years, it did have several key disadvantages which others have also noted.
  1. Cost:  Endnote required a license for every LIINES researcher at a relatively hefty price tag.  Sharing with collaborators was an every harder proposition.  Furthermore, yearly upgrade licenses was an even tougher pill to swallow.
  2. PDF Organization:  Managing the filesystem associated with PDF files of all the references is a big challenge.  EndNote did not provide a headache-free solution to this.  Even worse, an EndNote database could lose links to PDF files making it quite difficult to find again.
  3. Collaboration & Sharing:  The above challenges were compounded when it came to share Endnote Libraries across the LIINES.  Endnote sharing through Dropbox across multiple operating systems can get quite hairy!
  4. Proprietary Platform & Database:  When reference databases get large, one increasingly becomes interested in automating tasks for its management.   While EndNote does provide plenty of built in automated functionality, the power user ultimately does need to manage records automatically.
Of course, when migrating from one reference management system to another, it is important to make an educated well-researched decision.  The folks at PhdOnTrack.net have provided an excellent introduction.  The University of Rhode Island library has made a comparison of leading options, while Wikipedia provide a comprehensive comparison
Ultimately, Mendeley did come out on top @ the LIINES for a number of reasons.
  1. Cost:  The Mendeley desktop application is free!  This meant that every LIINES researcher could work individually without paying a penny.  That said, the associated cost was in the cloud-based monthly data storage plan.   While this was a recurring cost, Mendeley’s “Solar System”, “Milky Way”, and “Big Bang” subscription plans were very much priced reasonably.   Since Elsevier’s purchase of Mendeley, the cost of new plans has risen; perhaps out of reach for many.  Fortunately, with a little computer savvy one could also use other cloud-based storage services like Dropbox or Google Drive to easily store and share reference libraries.  Alternatively, many institutions including MIT have recognized the need to provide a uniform platform for their researchers and so have purchased Mendeley Institutional Edition.
  2. PDF Organization:  Probably one of Mendeley’s strongest features is its ability to automatically name and organize PDF files based upon key reference information such as Author Name, Year, and Title.  This became a headache free solution.
  3. Collaboration & Sharing:  Another real strength of Mendeley’s is its recognition of Web 2.0 and social media.   Mendeley databases are easily shared and synchronized between multiple computers, operating systems, tablets, smart phones, and users in a seamless way.   For the LIINES, this meant native support for Windows, Mac OS X, Linux, iOS, and Android for dozens of researchers across the world.
  4. Standard Database:  Finally, Mendeley’s database is written in SQL.  This meant that for the advanced database programmer, Mendeley offers the potential to develop automated scripts to manage reference data.  This particular strength overcomes some of the feature limitations within the Mendeley desktop application itself.
And yet, the migration to Mendeley was not without its disadvantages.
  1. Integration with LatTeX/BibTex:  Mendeley is able to create and maintain an automatically synced BibTeX database file.  However, it provides no user control to the highly important Citation Key!  In the course of regular use, Mendeley can change these citation keys which will then cause LaTeX citation links to break in your document.  Make sure to keep backups of your BibTeX database unless you want to redo all the links!
  2. PDF File Import:  The jury is still out on this one. Mendeley can directly import PDF files.  It will scan the PDF for reference information and insert it into the database.  For many files of standard format (e.g. IEEE, Elsevier journals), it does this accurately.  However, for many others, it creates lots of errors; forcing the researcher to manually correct the information.  At the LIINES, we recommend going to established online reference databases (IEEE XploreScienceDirectCompendex & Google Scholar  to download the associated .ris or .bib files instead.
  3. Batched PDF Import:  Many researchers new to reference management have troves of organized pdf files.  Others are migrating to Mendeley.  Beware that a batch PDF import can create lots of duplicates in the Mendeley database!
  4. Duplicates Management:  Mendeley desktop does provide a “Check for Duplicates” feature but in then requires manual deletion of these duplicates.  For large databases, this can be very time consuming.
  5. Association with Elsevier:  Finally, some academics have chosen to boycott Elsevier’s service on ethical grounds.  Others distinguish Mendeley from its parent company, and then there is official Mendeley perspective from William Gunn   While the LIINES does not participate in this boycott, we recognize its existence out of academic respect and encourage awareness amongst our readership.  Ultimately, one must recognize that Mendeley is now a fully commercial product and service.  For those that maintain reservations, many highly functional, free and open-source reference management solutions continue to exist.
We hope to return to some of these weakness in coming blog posts.
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IEEE Statement on Appropriate use of Bibliometric Indicators

The use of bibliometric analysis has become an increasing part of scientific publishing today.   While bibliometric analysis has brought about a degree of quantified objectivity, many have raised concerns about the potential pitfalls of their usage.   We refer our LIINES readership to the recent IEEE Statement on the Appropriate use of Bibliometric Indicators.   The associated video can be found below.

 

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