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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.
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:
- Allows for an evolving mixture of generation and demand as dispatchable energy resources
- Allows for an evolving mixture of generation and demand as variable energy resources
- Allows for the simultaneous study of transmission and distribution systems
- Allows for the time domain simulation of the convolution of relevant grid enterprise control functions
- Allows for the time domain simulation of power grid topology reconfiguration in operation time scale
- Specifically addresses the holistic dynamic properties of dispatchability, flexibility, forecastability, stability, and resilience
- Represents potential changes in enterprise grid control functions and technologies as impacts on these dynamic properties
- 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.
LIINES Website: http://engineering.dartmouth.edu/liines
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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Journal Paper Accepted: Relative Merits of Load Following Reserves & Energy Storage Market Integration Towards Power System Imbalances
We are happy to announce that our recent paper entitled: “Relative Merits of Load Following Reserves & Energy Storage Market Integration Towards Power System Imbalances”, has been published in the International Journal of Electrical Power & Energy Systems (IJEPES). This study comes as a result of collaboration between three universities; Masdar Institute, Dartmouth, and MIT. The work is authored by Aramazd Muzhikyan (Masdar Institute), Prof. Amro M. Farid (Dartmouth) and Prof. Kamal Youcef-Toumi (MIT).
The existing energy storage resource (ESR) studies bound their discussion to a single timescale of power system operations, such as day-ahead scheduling or real-time balancing. As a result, these studies are only able to capture the impact of the ESR integration on the associated timescale, while any effects that may span across adjacent timescales are omitted. Recently, power grid enterprise control has been developed that integrates different timescales of balancing operations into a multi-layer control hierarchy. The benefits of such holistic power system modeling have been demonstrated for studies on renewable energy integration, the determination of the power system imbalances and the assessment of reserve requirements.
This paper integrates ESRs into the power system enterprise control for the first time. While the ESR integration is expected to mainly affect its associated timescale, such methodology also allows capturing the potential impact on adjacent timescales. If such coupling of timescales exists, it can be exploited to reduce the system resource requirements. This methodology is also used to demonstrate the differences in imbalance mitigation performance of ESRs and load following reserves. While both these resources can be used for balancing the system, the enterprise control methodology unveils their differences and relative merits for different balancing scenarios. The notion of ‘‘utilization efficiency’’ of a given resource is introduced here which is defined as the amount of that resource required to mitigate 1MW of imbalance.
A novel ESR scheduling method has also been developed in this paper that beneficially exploits the coupling between different timescales. Since the day-ahead market has hourly time step, the obtained generation schedule has a stair-like profile with constant values for each hourly interval. However, such stair-like profile does not capture the intra-hour variations of the demand, leading to higher load following reserve requirement. Taking advantage of the timescale coupling, a sub-hourly ESR profile is designed based on the day-ahead market output that, in addition to the traditional benefits of shaving the peak load and reducing the operating cost, also simultaneously reduces the load following reserves requirement. The newly designed ESR schedule is based on piecewise linear harmonic functions and resembles the smooth demand profile within hourly intervals.
The results show that the ESR and the load following reserves have different performances and are better suited for applications in different circumstances. While the utilization efficiency is nearly constant for the load following reserves, the performance of the ESR significantly depends on the temporal characteristics, namely the net load variability and the day-ahead market time step. Higher variability and smaller day-ahead market time step result in better ESR utilization efficiency. The results also show that the generation schedule of the system without ESR has a stair-like form, while the total generation+ESR schedule of the system with ESR integration has a much smoother form and more closely resembles the actual demand profile. This difference defines the actual load following reserve requirement for each system. The results show that the load following reserve requirement of the system with ESR integration is significantly lower compared to the traditional system without ESR.
The comparison of the schedules for a system without ESR and a system with ESR scheduled according to the proposed method
The difference of load following reserve requirements for systems without and with ESR.
In depth materials on LIINES smart power grid research can be found on the LIINES website.
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Journal Paper Accepted: An A Priori Analytical Method for the Determination of Operating Reserve Requirements
We are happy to announce that our recent paper entitled: “An A Priori Analytical Method for the Determination of Operating Reserve Requirements”, has been accepted at the International Journal of Electrical Power & Energy Systems (IJEPES). This study comes as a result of collaboration between three universities; Masdar Institute, Dartmouth, and MIT. The work is authored by Aramazd Muzhikyan (Masdar Institute), Prof. Amro M. Farid (Dartmouth) and Prof. Kamal Youcef-Toumi (MIT).
As renewable energy becomes an ever present resource in power systems, so called “operating reserves” become increasingly important instruments for reliable power grid operations. One can think of operating reserves as additional generation capacity scheduled to compensate for real-time power supply and demand imbalances due to the existing uncertainties in forecasting not just demand but also renewable energy. On the one hand, the amount of operating reserves should be sufficient to successfully mitigate the real-time imbalances and maintain power system reliable operations. On the other hand, operating reserves are a costly commodity and they should not exceed the minimum required amount to avoid unnecessary expense. This makes accurate assessment of the operating reserve requirements vital for reliable, economic, and environmentally friendly operation of the power grid.
Currently, the necessary amount of the operating reserves is assessed based upon the power system operator experiences and the assumption that the circumstances of power system operations remain relatively unchanged. However, growing integration of renewable energy sources (RES), implementation of demand side management and transportation electrification alter the overall structure and the dynamics of the power grid. High penetration of RES brings new levels of variability and uncertainty to the grid which challenges the established practices of power system operations and the operating reserve requirement assessment methods. This newly published article provides closed-form analytical formulae that tells grid planners how much reserves to procure as they plan for more renewable energy without sacrificing economics or reliability.
While RES integration can potentially reduce the grid’s CO2 emissions and operating costs, it also brings new challenges that power grid operators need to address in order to maintain reliable operations. Wind power, for example, is known to have high intermittency; that is, the output power of a wind turbine may vary uncontrollably in a wide range. This, combined with comparably low wind forecasting accuracy, requires careful scheduling of traditional power plants and their operating reserves. Integration of solar power, on the other hand, has its own challenges. As shown in the figure below, the net load profile (the power demand minus the solar generation) of a system with integrated solar generation has a distinctive profile. It is often called the “Duck Curve” for its resemblance to the side-profile of a duck. The figure presents the net load profiles of the California Independent System Operator (CAISO) for the day of March 31 for forecasted from 2014 to 2020. The “belly” of the curve corresponds to the day time when the solar generation is at its maximum and is expected to grow with new solar power installations. With an estimated demand of 22,000MW in the year 2020, the solar generation accounts for 10,000MW or 45%; leaving only 12,000MW for the traditional generation. This situation increases the risk of overgeneration and solar generation curtailment. Another challenge is the steep jump of the net load around 6pm as solar generation wanes with the sunset and demand picks up for evening home life. Such severe variations of the net load require more careful consideration of the ramping capabilities of the scheduled generation.
The CAISO duck chart (source: P. Denholm, M. O’Connell, G. Brinkman, and J. Jorgenson, “Overgeneration from Solar Energy in California: A Field Guide to the Duck Chart,” National Renewable Energy Laboratory, Nov. 2015)
This publication has developed analytical formulae for calculation of the requirements for each type of operating reserves; namely, load following, ramping and regulation. The derivations show that the operating reserve requirements are effectively defined by a set of dimensionless parameters related to the RES characteristics and the operations of the power grid. Those parameters are the penetration level, renewable energy capacity factor, variability, day-ahead and short-term forecast errors of the integrated RES, and the power grid day-ahead scheduling and real-time balancing time steps. Such analytical expressions reveal how the requirements of each type of reserve will change when, for instance, more renewable energy is integrated, renewable energy forecasting accuracy is improved, and the day-ahead scheduling time step is reduced. This study show that higher RES variability significantly increases the requirements of all three types of reserves. Also, while the impact of the RES forecast error on the ramping reserve requirement is negligible, its impact on the load following and regulation reserve requirements can dominate that of the variability. On the other hand, reducing the day-ahead scheduling time step can mitigate the impact of the variability on the load following reserve requirement while having negligible impact on the ramping and regulation reserve requirements. Also, changing the balancing time step has no noticeable impact on the load following reserve requirement, it has opposing impacts on the ramping and regulation reserve requirements. Reducing the balancing time step reduces the regulation reserve requirement but increases the ramping reserve requirement.
These formulae can be used for renewable energy integration studies, such as those conducted in NE-ISO and PJM-ISO, to assess the required amount of reserves for the planned RES installation. They can also be adapted by the state and federal standards organizations to establish reserve procurement standards that reflect the evolution of the power grid.
In depth materials on LIINES smart power grid research can be found on the LIINES website.
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.
Table 1: Future grid generation and demand portfolio
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.
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.
Prof. Amro M. Farid joins the University of Massachusetts Transportation Center as an affiliated Researcher
Prof. Amro M. Farid presents at Transactive Energy Systems Conference
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.
Prof. Amro M. Farid gives invited lecture at UVIG
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.
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LIINES Website: http://engineering.dartmouth.edu/liines
