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The introduction of variable energy resources (VERs) like solar and wind into New England’s bulk electric power system necessitates fundamental changes to the grid’s operation. VER supplies are uncertain and intermittent thus requiring higher levels of operating reserves. We present the methodology and key findings of the 2017 ISO New England System Operational Analysis and Renewable Energy Integration Study (SOARES) commissioned by the ISO New England stakeholders to investigate the effect of several scenarios of varying generation mix on normal operating reserves. Insights into the emerging roles of curtailment, energy storage, and demand response as integral parts of normal balancing performance will also be covered.
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.
On Tuesday May 17, 2016, Prof. Amro M. Farid presented at the Third International Conference and Workshop on Transactive Energy Systems in Portland, Oregon. The presentation entitled: “Microgrids as a Key Enabling Transactive Energy Technology for Resilient Self-Healing Power Grid Operation” featured some of the LIINES’ recent research on resilience in power systems.
Building upon the recent IEEE Vision for Smart Grid Controls, the presentation advocated the concept of resilience self-healing operation in future power grids. This continues to be an important area of LIINES research and has been the subject of several recent blogposts. (See here, here and here). The concept of resilient power systems effectively means that healthy regions of the grid can continue to operate while disrupted and perturbed regions bring themselves back to normal operation. A key technology enabling this resilience is microgrids because they are often able to island themselves from the rest of the grid and continue to operate successfully. In this presentation, the microgrids were controlled with a transactive energy control architecture that couples several control layers to achieve both technical reliability as well as cost effectiveness. Furthermore, the presentation showed the ability for several microgrids to self-coordinate so as to demonstrate “strength-in-numbers” when adverse power grid conditions like net load ramps and variability arise. The presentation concluded with the need for significant new research where transactive energy control concepts are intertwined with recent work on power grid enterprise control.
In depth materials on LIINES smart power grid research can be found on the LIINES website.
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.
- 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).
One major disciplinary expertise at the Laboratory for the Intelligent Integrated Networks for Engineering Systems is operations management and research. Naturally, using optimization techniques in the form of mathematical programming is an essential aspect of this competence. One really useful software package to allow the straightforward numerical optimization is the General Algebraic Modeling System (GAMS) and it has been used extensively in the smart power grid application domain. Many researchers in the field also link Matlab to GAMS using the former for data processing and results visualization and the latter as a solver.
The implementations at the LIINES, however, have some challenging implementation demands. For example, model predictive control problems require the solution of a numerical optimization at every discrete time step simulation evolution. When Matlab calls GAMS — on the Windows platform — it spawns a new graphical user interface integrated development environment (GUI-IDE) window (and all associated dynamic link libraries). This slows down simulation tremendously. Even worse, the Windows OS may not be able to reliably handle these repeated calls leading to a crash of the simulation. Trust us, when you are many hours into a fully automatic simulation, that’s hardly what you are looking for.
Fortunately, the GAMS version of Linux and Mac OS X does not have a GUI-IDE and runs purely from the command line. We have found this to be not just faster for simulation but also much more stable when tied to MATLAB. We highly suggest this approach.
Now some will say, that they need the GAMS GUI-IDE for development. We agree that this can be useful! Fortunately, you can have the best of both worlds. Use the command line native Linux/Mac OS X version for reliable simulation. In the meantime, a Windows version installed over WINE can be used purely for development. The GAMS support page provides very clear installation instructions here.
LIINES Website: http://amfarid.scripts.mit.edu