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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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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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