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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.
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.
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.
The LIINES is happy to announce that our recent paper entitled: “Symmetrica: Test Case for Tansportation Electrification Research” has been published in the journal Infrastructure Complexity. Written by Prof. Amro M. Farid, this paper presents a test case for electric vehicle integration studies.
Electrified transportation has emerged in recent years as a means to reduce CO2 emissions and support energy efficiency. For this trend to succeed in the long term, electric vehicles must be integrated into the infrastructure systems that support them. Electric vehicles couple two such large systems; the transportation system and the electric power system into a nexus.
Electric vehicle integration, much like solar PV and wind integration years ago, has been fairly confined to small fleets of tens of vehicles. Such small pilot projects do not present a significant technical challenge. Their large scale adoption, however, must be carefully studied to avoid degrading overall infrastructure performance. Transportation electrification test cases serve to study infrastructure behavior well before reaching a full deployment of electric vehicles. Such a test case would resemble those often used in power systems engineering to serve methodological development in the design, planning, and operation of such systems.
The arguments for a test case to study the transportation electricity nexus are five-fold. First, a standardized test case is required to test, and compare analytical methods. In power systems, test cases served an essential role in the maturation of power flow analysis, stability studies, and contingency analysis. The transportation-electricity nexus will ultimately also require similar assessments. Secondly, using real data from critical infrastructure may be imprudent. For example, real data may reveal weak points in a power system which may be exploited by unauthorized personnel. Thirdly, a test case serves to support fundamental understanding by broadening intuition development. For the transportation-electricity nexus, understanding the effect of increasingly interdependent dynamics, will result in new requirements for optimization and control for its planning and operation. Naturally, this new found intuition serves the fourth reason of methodological development. A test case serves facilitates the design, planning, and operation of the system before it is built. Unexpected behaviors may be identified in an early stage and can subsequently be avoided or mitigated. Finally, the privacy of personal data is protected through using a test case. Transportation simulation requires microscopic data (tracking each vehicle through a full day’s events), which raises grave privacy and ethical concerns if real data is used.
To address these needs, the proposed test case includes three structural descriptions: a transportation system topology, an electric power topology, and a charging system topology. Additional data includes transportation demand and charging demand. The test case consists of a number of desirable characteristics, including completeness, functional heterogeneity, moderate size, regular topology, regular demand data, realism, and objectivity. The figure below shows the three topologies; a fully detailed description test casenamed ‘Symmetrica’ is available in the paper.
The transportation electrification test case can potentially be used for research within planning and operation management applications. A recent study (Al Junaibi et al. 2013) showed that the planning of the charging system as the couple of two infrastructure systems highly impacts the overall performance of the transportation electrification nexus. Matching the spatial layout of charging infrastructure to the demand for electrified transportation is key a infrastructure developent challenge. Furthermore, investment costs to upgrade power lines and transformers must be matched to the expected adoption of electric vehicles, providing an interesting starting point for return-on-investment and operations research methods. Using operation management applications such as charging station queue management or vehicle-2-grid stabilization could optimize the integration of electric vehicles within the nexus. Opportunities such as these present rich applications areas which have the potential to significant reduce the extra expenditure in infrastructure investments.
In depth materials on LIINES electrified transportation systems research can be found on the LIINES websitte.
Prof. Amro M. Farid joins the University of Massachusetts Transportation Center as an affiliated Researcher
On April 27th, 2016, Prof. Amro M. Farid gave an invited lecture at the Utility Variable-Generation Integration Group (UVIG) Spring Technical Workshop held in Sacramento, CA. The presentation entitled: “Enterprise Control as a Holistic Assessment Method for Variable Generation & Demand Response Integration” featured many of the LIINES’ research on renewable energy integration assessment methodologies.
The presentation advocated the concept of “Power Grid Enterprise Control” which has been the subject of several recent blogposts. (See here and here). Traditionally, power system operation & control methods are conducted individually. In contrast, “Power Grid Enterprise Control” integrates these methods into a single simulation of how a power system enterprise behaves as a physical power grid tied to multiple layers of control, optimization and market behavior. Such an integrated approach provides techno-economic performance results of the power grid. Furthermore, it highlights trade-off decisions between technical reliability and cost performance. The presentation showed how enterprise control simulation can be used to study renewable energy, energy storage, and demand-side energy resources.
In depth materials on LIINES smart grid research can be found on the LIINES website.
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.
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:
- The degree to which existing designs have achieved their intended level of reconfigurability.
- Which systems are quantitatively more reconfigurable.
- 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.
- Sharing all input datasets used to conduct the research for which no prior proprietary or security commitments have been made.
- Producing scientific publications in such a way that scientific peers can accurately verify & validate the work.
- Making the content of all conference, journal and book-chapter publications freely available in author preprint form. (Note: Most publishers allow self-archiving and open-distribution of author preprints).
Journal Paper Accepted at Applied Energy Journal – Demand Side Management in a Day-Ahead Wholesale Market: A Comparison of Industrial & Social Welfare Approaches
The LIINES is pleased to announce the acceptance of the paper entitled: “Demand Side Management in a Day-Ahead Wholesale Market: A Comparison of Industrial & Social Welfare Approaches” to Applied Energy Journal for publication. The paper is authored by Bo Jiang, Prof. Amro M. Farid, and Prof. Kamal Youcef-Toumi.
The intermittent and unpredictable nature of renewable energy brings operational challenges to electrical grid reliability. The fast fluctuations in renewable energy generation require high ramping capability which must be met by dispatchable energy resources. In contrast, Demand Side management (DSM) with its ability to allow customers to adjust electricity consumption in response to market signals has been recognized as an efficient way to shape load profiles and mitigate the variable effects of renewable energy as well as to reduce system costs. However, the academic and industrial literature have taken divergent approaches to DSM implementation. While the popular approach among academia adopts a social welfare maximization formulation, defined as the net benefit from electricity consumption measured from zero, the industrial practice introduces an estimated baseline. This baseline represents the counterfactual electricity consumption that would have occurred without DSM, and customers are compensated according to their load reduction from this predefined electricity consumption baseline.
In response to the academic and industrial literature gap, our paper rigorously compares these two different approaches in a day-ahead wholesale market context. We developed models for the two methods using the same mathematical formalism and compared them analytically as well as in a test case using RTS-1996 reliability testing system. The comparison of the two models showed that a proper reconciliation of the two models might make them dispatch in fundamentally the same way, but only under very specific conditions that are rarely met in practice. While the social welfare model uses a stochastic net load composed of two terms, the industrial DSM model uses a stochastic net load composed of three terms including the additional baseline term. While very much discouraged, customers have an implicit incentive to surreptitiously inflate the administrative baseline in order to receive greater financial compensation. An artificially inflated baseline is shown to result in a higher resource dispatch and higher system costs.
The high resource scheduling due to inflated baseline likely require more control activity in subsequent layers of enterprise control including security constrained economic dispatch and regulation service layer. Future work will continue to explore the technical and economic effects of erroneous industrial baseline.
About the Author:
Bo Jiang conducted this research in collaboration with her Master’s thesis advisor Prof. Amro M. Farid and Prof. Kamal Youcef-Toumi at Massachusetts Institute of Technology. Her research interests include renewable energy integration, power system operations and optimization. Bo is now pursuing her PhD at MIT Mechanical Engineering Department.
A full reference list of Smart Power Grids and Intelligent Energy Systems research at LIINES can be found on the LIINES publication page: http://engineering.dartmouth.edu/liines
Journal Paper Accepted at Springer’s Intelligent Industrial Systems Journal: Multi-Agent System Design Principles for Resilient Coordination & Control of Future Power Systems
The LIINES is pleased to announce the acceptance of the paper: “Multi-Agent System Design Principles for Resilient Coordination & Control of Future Power Systems” in Springer’s Intelligent Industrial Systems Journal. The paper is authored by Amro M. Farid and was published online at May 28th 2015.
Recently, the vision of academia and industry has converged, defining future power system as intelligent, responsive, dynamic, adaptive, and flexible. This vision emphasizes the importance of resilience as a “smart grid” property. It’s implementation remains as a cyber-physical grand challenge.
Power grid resilience allows healthy regions to continue normal operation while disrupted or perturbed regions bring themselves back to normal operation. Previous literature has sought to achieve resilience with microgrids capable of islanded operation enabled by distributed renewable energy resources. These two factors require a holistic approach to managing a power system’s complex dynamics. In our recent work (e.g. link 1 and link 2), we have proposed as means of integrating a power system’s multiple layers of control into a single hierarchical control structure.
In addition to enterprise control, it is important to recognize that resilience requires controllers to be available even if parts of the power grid are disrupted. Therefore, distributed control systems, and more specifically Multi-Agent Systems have often been proposed as the key technology for implementing resilient control systems. Multi-agent systems are commonly used to distribute a specific decision-making algorithm such as those in market negotiation and stability control. However, very few have sought to apply multi-agent systems to achieve a resilient power system.
The purpose of the paper entitled “Multi-Agent System Design Principles for Resilient Coordination & Control of Future Power Systems” is two fold. First, it seeks to identify a set of Multi-Agent System design principles for resilient coordination and control. Second, the paper assesses the adherence of existing Multi-Agent System implementations in the literature with respect to those design principles.
The set of design principles is based on newly developed resilience measures for Large Flexible Engineering Systems. These measures use Axiomatic Design and are directly applicable to the power grid’s many types of functions and its changing structure. These design principles, when followed, guide the conception of a multi-agent system architecture to achieve greater resilience.
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.
LIINES Website: http://amfarid.scripts.mit.edu