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Timothy M. Hansen
South Dakota State University, Brookings, SD, USA

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Journal article
Published: 18 August 2021 in IEEE Access
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The displacement of rotational generation and the consequent reduction in system inertia is expected to have major stability and reliability impacts on modern power systems. Fast-frequency support strategies using energy storage systems (ESSs) can be deployed to maintain the inertial response of the system, but information regarding the inertial response of the system is critical for the effective implementation of such control strategies. In this paper, a moving horizon estimation (MHE)-based approach for online estimation of inertia constant of low inertia microgrids is presented. Based on the frequency measurements obtained in response to a non-intrusive excitation signal from an ESS, the inertia constant was estimated using local measurements from the ESS’s phase-locked loop. The proposed MHE formulation was first tested in a linearized power system model, followed by tests in a modified microgrid benchmark from Cordova, Alaska. Even under moderate measurement noise, the technique was able to estimate the inertia constant of the system well within ±20% of the true value. Estimates provided by the proposed method could be utilized for applications such as fast-frequency support, adaptive protection schemes, and planning and procurement of spinning reserves.

ACS Style

Ujjwol Tamrakar; David A. Copp; Tu A. Nguyen; Timothy M. Hansen; Reinaldo Tonkoski. Real-Time Estimation of Microgrid Inertia and Damping Constant. IEEE Access 2021, 9, 114523 -114534.

AMA Style

Ujjwol Tamrakar, David A. Copp, Tu A. Nguyen, Timothy M. Hansen, Reinaldo Tonkoski. Real-Time Estimation of Microgrid Inertia and Damping Constant. IEEE Access. 2021; 9 ():114523-114534.

Chicago/Turabian Style

Ujjwol Tamrakar; David A. Copp; Tu A. Nguyen; Timothy M. Hansen; Reinaldo Tonkoski. 2021. "Real-Time Estimation of Microgrid Inertia and Damping Constant." IEEE Access 9, no. : 114523-114534.

Review
Published: 17 June 2021 in IEEE Access
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Converter-based generators are increasingly replacing classical synchronous generation, resulting in significant challenges to the operation and planning of modern power systems. Power electronics (PE)-based equipment, along with non-linear PE-driven loads, introduce time-varying characteristics and fast switching behavior that increases the complexity of the power system model. Faster control actions are needed to overcome the fast switching dynamics to ensure the reliability and stability of future power systems. Thus, this requires advanced and detailed simulation methods and tools with highly accurate equivalent models to embody the relatively slower electromechanical to faster electromagnetic transient (EMT) phenomena. Conventional transient stability analysis using positive-sequence simulators has become inadequate for representing converter-dominated power systems, while EMT simulators suffer from the high computational burden. This review paper presents accelerated EMT simulation methods and tools that are categorized and discussed in three topics: system equivalents, simulation methods, and accelerating tools. Dynamic system equivalent techniques are discussed to model small to large interconnected external systems of the grid network. Moreover, a systematic review is made for existing EMT simulation methods, along with advanced co-simulation methods, for addressing simulation speed and accuracy issues in large power system networks. Emerging hardware-based simulation tools are reviewed that reduce the computational burden and increase the simulation efficiency of the power system model. Challenges and trends in EMT simulation are also presented and concluded by providing perspectives on this research topic.

ACS Style

Sunil Subedi; Manisha Rauniyar; Saima Ishaq; Timothy M. Hansen; Reinaldo Tonkoski; Mariko Shirazi; Richard Wies; Phylicia Cicilio. Review of Methods to Accelerate Electromagnetic Transient Simulation of Power Systems. IEEE Access 2021, 9, 1 -1.

AMA Style

Sunil Subedi, Manisha Rauniyar, Saima Ishaq, Timothy M. Hansen, Reinaldo Tonkoski, Mariko Shirazi, Richard Wies, Phylicia Cicilio. Review of Methods to Accelerate Electromagnetic Transient Simulation of Power Systems. IEEE Access. 2021; 9 ():1-1.

Chicago/Turabian Style

Sunil Subedi; Manisha Rauniyar; Saima Ishaq; Timothy M. Hansen; Reinaldo Tonkoski; Mariko Shirazi; Richard Wies; Phylicia Cicilio. 2021. "Review of Methods to Accelerate Electromagnetic Transient Simulation of Power Systems." IEEE Access 9, no. : 1-1.

Review
Published: 04 June 2021 in IEEE Access
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In response to national and international carbon reduction goals, renewable energy resources like photovoltaics (PV) and wind, and energy storage technologies like fuel-cells are being extensively integrated in electric grids. All these energy resources require power electronic converters (PECs) to interconnect to the electric grid. These PECs have different response characteristics to dynamic stability issues compared to conventional synchronous generators. As a result, the demand for validated models to study and control these stability issues of PECs has increased drastically. This paper provides a review of the existing PEC model types and their applicable uses. The paper provides a description of the suitable model types based on the relevant dynamic stability issues. Challenges and benefits of using the appropriate PEC model type for studying each type of stability issue are also presented.

ACS Style

Chinmay Shah; Jesus D. Vasquez-Plaza; Daniel D. Campo-Ossa; Juan F. Patarroyo-Montenegro; Nischal Guruwacharya; Niranjan Bhujel; Rodrigo D. Trevizan; Fabio Andrade Rengifo; Mariko Shirazi; Reinaldo Tonkoski; Richard Wies; Timothy M. Hansen; Phylicia Cicilio. Review of Dynamic and Transient Modeling of Power Electronic Converters for Converter Dominated Power Systems. IEEE Access 2021, 9, 82094 -82117.

AMA Style

Chinmay Shah, Jesus D. Vasquez-Plaza, Daniel D. Campo-Ossa, Juan F. Patarroyo-Montenegro, Nischal Guruwacharya, Niranjan Bhujel, Rodrigo D. Trevizan, Fabio Andrade Rengifo, Mariko Shirazi, Reinaldo Tonkoski, Richard Wies, Timothy M. Hansen, Phylicia Cicilio. Review of Dynamic and Transient Modeling of Power Electronic Converters for Converter Dominated Power Systems. IEEE Access. 2021; 9 ():82094-82117.

Chicago/Turabian Style

Chinmay Shah; Jesus D. Vasquez-Plaza; Daniel D. Campo-Ossa; Juan F. Patarroyo-Montenegro; Nischal Guruwacharya; Niranjan Bhujel; Rodrigo D. Trevizan; Fabio Andrade Rengifo; Mariko Shirazi; Reinaldo Tonkoski; Richard Wies; Timothy M. Hansen; Phylicia Cicilio. 2021. "Review of Dynamic and Transient Modeling of Power Electronic Converters for Converter Dominated Power Systems." IEEE Access 9, no. : 82094-82117.

Original research paper
Published: 21 February 2021 in IET Smart Grid
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A data‐driven technique to determine greenhouse gas (GHG) and air‐pollutant (AP) emissions from bulk‐power system simulations is proposed. The proposed technique emulates the dispatch of a bulk‐power system using open‐source hourly fuel‐energy data from an actual U.S. electricity market (i.e. PJM). Sixteen different fuel types were analysed from real generator data and dynamically assigned to power system test cases to statistically represent the real fuel‐energy mix. Each test case generator is assigned a heat‐rate function based on open‐source real generator data to estimate realistic emissions from power system test case simulations. These augmented test cases can be used to simulate how changes in load and generation impact power system emissions to determine the environmental sustainability of new technologies (e.g. demand‐side management). The proposed technique is implemented on three different power system test cases, and the simulated emissions are compared with the actual emissions of the PJM system. The results from the test systems are found to accurately emulate the time‐series values of fuel‐mix, emissions, and marginal costs of PJM.

ACS Style

Venkat Durvasulu; Timothy M. Hansen. A data‐driven approach to estimate emissions for market‐based power system test cases. IET Smart Grid 2021, 1 .

AMA Style

Venkat Durvasulu, Timothy M. Hansen. A data‐driven approach to estimate emissions for market‐based power system test cases. IET Smart Grid. 2021; ():1.

Chicago/Turabian Style

Venkat Durvasulu; Timothy M. Hansen. 2021. "A data‐driven approach to estimate emissions for market‐based power system test cases." IET Smart Grid , no. : 1.

Journal article
Published: 24 November 2020 in IEEE Transactions on Energy Conversion
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The lack of inertial response from non-synchronous, inverter-based generation in microgrids makes the power system vulnerable to a large rate of change of frequency (ROCOF) and frequency excursions. Energy storage systems (ESSs) can be utilized to provide fast-frequency support to prevent such large excursions in the system. However, fast-frequency support is a power-intensive application that has a significant impact on the ESS lifetime. In this paper, a framework that allows the ESS operator to provide fast-frequency support as a service is proposed. The framework maintains the desired quality-of-service (limiting the ROCOF and frequency) while taking into account the ESS lifetime and physical limits. The framework utilizes moving horizon estimation (MHE) to estimate the frequency deviation and ROCOF from noisy phase-locked loop (PLL) measurements. These estimates are employed by a model predictive control (MPC) algorithm that computes control actions by solving a finite-horizon, online optimization problem. Additionally, this approach avoids oscillatory behavior induced by delays that are common when using low-pass filters as with traditional derivative-based (virtual inertia) controllers. MATLAB/Simulink simulations on a test system from Cordova, Alaska, show the effectiveness of the MHE-MPC approach to reduce frequency deviations and ROCOF of a low-inertia microgrid.

ACS Style

Ujjwol Tamrakar; David A. Copp; Tu Anh Nguyen; Timothy M. Hansen; Reinaldo Tonkoski. Optimization-Based Fast-Frequency Estimation and Control of Low-Inertia Microgrids. IEEE Transactions on Energy Conversion 2020, 36, 1459 -1468.

AMA Style

Ujjwol Tamrakar, David A. Copp, Tu Anh Nguyen, Timothy M. Hansen, Reinaldo Tonkoski. Optimization-Based Fast-Frequency Estimation and Control of Low-Inertia Microgrids. IEEE Transactions on Energy Conversion. 2020; 36 (2):1459-1468.

Chicago/Turabian Style

Ujjwol Tamrakar; David A. Copp; Tu Anh Nguyen; Timothy M. Hansen; Reinaldo Tonkoski. 2020. "Optimization-Based Fast-Frequency Estimation and Control of Low-Inertia Microgrids." IEEE Transactions on Energy Conversion 36, no. 2: 1459-1468.

Research article
Published: 19 May 2020 in IET Smart Grid
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The ability to control tens of thousands of residential electricity customers in a coordinated manner has the potential to enact system-wide electric load changes, such as reduce congestion and peak demand, among other benefits. To quantify the potential benefits of demand-side management and other power system simulation studies (e.g. home energy management, large-scale residential demand response), synthetic load datasets that accurately characterise the system load are required. This study designs a combined top-down and bottom-up approach for modelling individual residential customers and their individual electric assets, each possessing their own characteristics, using time-varying queueing models. The aggregation of all customer loads created by the queueing models represents a known city-sized load curve to be used in simulation studies. The three presented residential queueing load models use only publicly available data. An open-source Python tool to allow researchers to generate residential load data for their studies is also provided. The simulation results presented consider the ComEd region (utility company from Chicago, IL) and demonstrate the characteristics of the three proposed residential queueing load models, the impact of the choice of model parameters, and scalability performance of the Python tool.

ACS Style

Fernando B. dos Reis; Reinaldo Tonkoski; Timothy M. Hansen. Synthetic residential load models for smart city energy management simulations. IET Smart Grid 2020, 3, 342 -354.

AMA Style

Fernando B. dos Reis, Reinaldo Tonkoski, Timothy M. Hansen. Synthetic residential load models for smart city energy management simulations. IET Smart Grid. 2020; 3 (3):342-354.

Chicago/Turabian Style

Fernando B. dos Reis; Reinaldo Tonkoski; Timothy M. Hansen. 2020. "Synthetic residential load models for smart city energy management simulations." IET Smart Grid 3, no. 3: 342-354.

Journal article
Published: 10 July 2019 in IEEE Transactions on Smart Grid
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Residential energy optimization provides economic and reliability benefits to the electric utility and consumers. Two major challenges in community energy optimization are: 1) to efficiently coordinate among a large number of residential consumers’ electric appliances and 2) to ensure participating consumers are comfortable and are rewarded with financial incentives during demand reduction. This paper proposes a hierarchical control framework with a novel bidding scheme that manages the use of consumers’ electric appliances while satisfying utility demand reduction requests. A new demand reduction bidding strategy is introduced for the efficient coordination among several local controllers (LCs) under a central controller (CC) in the proposed framework. Incentives are provided to the residential consumers for their participation, while considering their preferences, using a continuous reward structure. A simulation study on the 6-bus Roy Billinton test system with 1200 residential consumers demonstrates the financial benefits to the electric utility and consumers by performing a 6% demand reduction during peak times. The results show that the utility saves $28 217, and a residential consumer earns $9.37 on average for a one-hour demand reduction event (e.g., reducing 1.2 MW peak power). The reward scheme designed from this framework is more economical to utilities compared to existing utility reward schemes.

ACS Style

Priti Paudyal; Prateek Munankarmi; Zhen Ni; Timothy M. Hansen. A Hierarchical Control Framework With a Novel Bidding Scheme for Residential Community Energy Optimization. IEEE Transactions on Smart Grid 2019, 11, 710 -719.

AMA Style

Priti Paudyal, Prateek Munankarmi, Zhen Ni, Timothy M. Hansen. A Hierarchical Control Framework With a Novel Bidding Scheme for Residential Community Energy Optimization. IEEE Transactions on Smart Grid. 2019; 11 (1):710-719.

Chicago/Turabian Style

Priti Paudyal; Prateek Munankarmi; Zhen Ni; Timothy M. Hansen. 2019. "A Hierarchical Control Framework With a Novel Bidding Scheme for Residential Community Energy Optimization." IEEE Transactions on Smart Grid 11, no. 1: 710-719.

Journal article
Published: 11 January 2019 in IEEE Transactions on Sustainable Energy
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Demand response (DR) and renewable energy sources have opened new avenues for end-users to lower their energy expenses via energy management systems. Aggregators facilitate the participation of end-users by acting on their behalf and interacting with bulk electricity markets. In this paper, an energy management algorithm is presented to investigate the impact of distributed photovoltaic (PV) and central energy storage system (ESS) assets on the economic performance of an energy aggregator in the residential sector. To enable DR, the aggregator provides a competitive incentive price to end-users, and centrally optimizes the central ESS assets and schedule of committed customer elastic loads. Thus, customers reduce their daily electricity bill while the aggregator decreases the aggregated peak consumption and earns profits as a return for providing DR services. The scope of this paper pertains to the economic impact of distributed PV and central ESS assets on aggregator profits and customer savings resulting from DR, including ESS degradation. Simulation results showed that the central ESS increases the income of the aggregator, whereas residential PV reduces the impact of DR.

ACS Style

Berk Celik; Siddharth Suryanarayanan; Robin Roche; Timothy M. Hansen. Quantifying the Impact of Solar Photovoltaic and Energy Storage Assets on the Performance of a Residential Energy Aggregator. IEEE Transactions on Sustainable Energy 2019, 11, 405 -414.

AMA Style

Berk Celik, Siddharth Suryanarayanan, Robin Roche, Timothy M. Hansen. Quantifying the Impact of Solar Photovoltaic and Energy Storage Assets on the Performance of a Residential Energy Aggregator. IEEE Transactions on Sustainable Energy. 2019; 11 (1):405-414.

Chicago/Turabian Style

Berk Celik; Siddharth Suryanarayanan; Robin Roche; Timothy M. Hansen. 2019. "Quantifying the Impact of Solar Photovoltaic and Energy Storage Assets on the Performance of a Residential Energy Aggregator." IEEE Transactions on Sustainable Energy 11, no. 1: 405-414.

Journal article
Published: 19 December 2018 in Applied Sciences
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The rapid transition towards an inverter-dominated power system has reduced the inertial response capability of modern power systems. As a solution, inverters are equipped with control strategies, which can emulate inertia by exchanging power with the grid based on frequency changes. This paper discusses the various current control techniques for application in these systems, known as virtual inertia systems. Some classic control techniques like the proportional-integral, the proportional-resonant, and the hysteresis control are presented first, followed by the design and discussion of two more advanced control techniques based on model prediction and machine learning, respectively. MATLAB/Simulink-based simulations are performed, and results are presented to compare these control techniques in terms of harmonic performance, switching frequency, and transient response.

ACS Style

Ujjwol Tamrakar; Dipesh Shrestha; Naresh Malla; Zhen Ni; Timothy M. Hansen; Indraman Tamrakar; Reinaldo Tonkoski. Comparative Analysis of Current Control Techniques to Support Virtual Inertia Applications. Applied Sciences 2018, 8, 2695 .

AMA Style

Ujjwol Tamrakar, Dipesh Shrestha, Naresh Malla, Zhen Ni, Timothy M. Hansen, Indraman Tamrakar, Reinaldo Tonkoski. Comparative Analysis of Current Control Techniques to Support Virtual Inertia Applications. Applied Sciences. 2018; 8 (12):2695.

Chicago/Turabian Style

Ujjwol Tamrakar; Dipesh Shrestha; Naresh Malla; Zhen Ni; Timothy M. Hansen; Indraman Tamrakar; Reinaldo Tonkoski. 2018. "Comparative Analysis of Current Control Techniques to Support Virtual Inertia Applications." Applied Sciences 8, no. 12: 2695.

Journal article
Published: 01 December 2018 in Energies
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In most U.S. market sponsored demand response (DR) programs, revenue earned from energy markets has been relatively low compared to DR used for capacity markets and ancillary services. This paper presents an aggregated DR model participating in the bulk-power market as a service through a pool-based entity called demand response exchange (DRX). Using the DRX structure, DR providers can participate in energy markets as a service to benefit bulk-power market entities. The benefits and challenges to each market entity using DR-as-a-service are presented in an extended review. The DRX model in this study is a market entity that operates with the day-ahead market to select DR offers that minimize electric utility payments. A case study was performed using the proposed DRX model on the IEEE 24-bus system, augmented to represent actual bulk-power market prices to study factors that influence utility payments under the DRX-market paradigm. Two high-price days of the PJM market were simulated, and it was shown for a single day on the augmented test case that spending $69,955 for DR-as-a-service results in a reduction of utility payments of $864,199. The day-ahead generator supply curve, network congestion, and DR curtailment were found to be the most influencing factors that impact the benefit of using DR-as-a-service.

ACS Style

Venkat Durvasulu; Timothy M. Hansen. Benefits of a Demand Response Exchange Participating in Existing Bulk-Power Markets. Energies 2018, 11, 3361 .

AMA Style

Venkat Durvasulu, Timothy M. Hansen. Benefits of a Demand Response Exchange Participating in Existing Bulk-Power Markets. Energies. 2018; 11 (12):3361.

Chicago/Turabian Style

Venkat Durvasulu; Timothy M. Hansen. 2018. "Benefits of a Demand Response Exchange Participating in Existing Bulk-Power Markets." Energies 11, no. 12: 3361.

Journal article
Published: 06 November 2018 in IET Cyber-Physical Systems: Theory & Applications
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Post-restructuring, generators are dispatched using cleared offers in the day-ahead market in the cyber-physical power system. This study proposes a novel method to design generator cost functions to emulate existing market costs for power system test cases. Cost functions on existing test cases are based on fuel costs, which do not represent organised markets. In such markets, the marginal cost of energy is determined by generator offers, not fuel costs. In this work, the authors classify real market generator offers from an independent system operator organised electricity market into generator types. Generator offers are used to develop market-based generator cost functions for use in power system test cases to emulate electricity market behaviour. The proposed method is illustrated using PJM data on eight standard power system test cases from a six bus 240 MW generation case to 2000 buses with 95,000 MW of generation. The marginal price of the proposed market-based generator costs shows on average 280% improvement in accuracy of simulating the day-ahead PJM marginal energy price over existing fuel-cost-based test cases from 2014 to 2016. By using the new market-based generator cost functions, power system simulation studies will better represent actual economic impacts.

ACS Style

Venkat Durvasulu; Timothy M. Hansen. Market‐based generator cost functions for power system test cases. IET Cyber-Physical Systems: Theory & Applications 2018, 3, 194 -205.

AMA Style

Venkat Durvasulu, Timothy M. Hansen. Market‐based generator cost functions for power system test cases. IET Cyber-Physical Systems: Theory & Applications. 2018; 3 (4):194-205.

Chicago/Turabian Style

Venkat Durvasulu; Timothy M. Hansen. 2018. "Market‐based generator cost functions for power system test cases." IET Cyber-Physical Systems: Theory & Applications 3, no. 4: 194-205.

Journal article
Published: 22 October 2018 in IEEE Access
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Modern data centers consume large amounts of electricity, resulting in high operational costs. The efficiency of a data center power distribution system can be increased, and the operational cost reduced, if the number of power conversion stages can be minimized and more efficient converters, such as wide bandgap (WBG) converters, are used. This can be achieved by using DC distribution voltage at the rack level by eliminating extra conversion stages. In this paper, benchmarks for both AC and 380V DC data centers were developed and efficiency analyses were performed for an entire year. The impact of integrating photovoltaic (PV) systems into the data centers has also been analyzed in both cases in terms of efficiency. The results show that 380V DC data centers are more efficient than AC data centers with and without PV integration. Furthermore, the reliability of an AC system was compared to a 380V DC architecture with Tier-IV standard. Monte-Carlo simulations were used to perform reliability analyses for different levels of redundancy in the Uninterruptible Power Supply (UPS) system for both cases. The simulation results showed that the 380V DC distribution system had a higher level of reliability than the AC distribution system in data centers.

ACS Style

Bijen R. Shrestha; Ujjwol Tamrakar; Timothy M. Hansen; Bishnu P. Bhattarai; Sean James; Reinaldo Tonkoski. Efficiency and Reliability Analyses of AC and 380 V DC Distribution in Data Centers. IEEE Access 2018, 6, 63305 -63315.

AMA Style

Bijen R. Shrestha, Ujjwol Tamrakar, Timothy M. Hansen, Bishnu P. Bhattarai, Sean James, Reinaldo Tonkoski. Efficiency and Reliability Analyses of AC and 380 V DC Distribution in Data Centers. IEEE Access. 2018; 6 (99):63305-63315.

Chicago/Turabian Style

Bijen R. Shrestha; Ujjwol Tamrakar; Timothy M. Hansen; Bishnu P. Bhattarai; Sean James; Reinaldo Tonkoski. 2018. "Efficiency and Reliability Analyses of AC and 380 V DC Distribution in Data Centers." IEEE Access 6, no. 99: 63305-63315.

Proceedings article
Published: 01 September 2018 in 2018 North American Power Symposium (NAPS)
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The increase in the penetration of photovoltaics (PVs) and wind energy resources has decreased the inertia of power systems and made them inverter-based. This makes the modern grid susceptible to frequency instability when facing generation-load imbalances. In this paper, we provide an overview of the changing trends in frequency response and frequency control strategies in the modern power grid under high renewable penetrations. Virtual inertia emulation through Energy Storage Systems (ESSs), which have fast-ramping capabilities, is reviewed as a potential solution to the frequency instability issue. Recent grid codes and rules related to fast frequency services in the power system are discussed. A case study of the PJM interconnection, which was one of the first ISOs/RTOs to introduce the use of ESSs for frequency response, is then presented. The challenges faced to properly procure and reward such fast frequency response services in the PJM interconnection is analyzed in detail.

ACS Style

Andre Luna; Ujjwol Tamrakar; Timothy M. Hansen; Reinaldo Tonkoski. Frequency Response in Grids with High Penetration of Renewable Energy Sources. 2018 North American Power Symposium (NAPS) 2018, 1 -5.

AMA Style

Andre Luna, Ujjwol Tamrakar, Timothy M. Hansen, Reinaldo Tonkoski. Frequency Response in Grids with High Penetration of Renewable Energy Sources. 2018 North American Power Symposium (NAPS). 2018; ():1-5.

Chicago/Turabian Style

Andre Luna; Ujjwol Tamrakar; Timothy M. Hansen; Reinaldo Tonkoski. 2018. "Frequency Response in Grids with High Penetration of Renewable Energy Sources." 2018 North American Power Symposium (NAPS) , no. : 1-5.

Proceedings article
Published: 01 August 2018 in 2018 IEEE Power & Energy Society General Meeting (PESGM)
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Residential energy management can be used to reduce peak electric demand, decrease electricity costs, and maintain grid reliability. Previous work only performs demand response to reduce the power consumption and the electricity bill. In this paper, we model the physical distribution system and investigate the impact of demand response program on the distribution network. This paper first introduces a residential energy management system that maintains residential consumers' demand within a utility-defined limit during peak times. The system further examines the impact of the residential energy management on the voltage profile of the distribution network. A case study is presented to demonstrate the effectiveness of the proposed system, showing that the proposed system is capable of reducing demand to remain within the demand limit while considering consumers' comfort and allocating reward incentives to each consumer. It is shown that the voltage profile of the distribution system is improved with the proposed system.

ACS Style

Priti Paudyal; Prateek Munankarmi; Zhen Ni; Timothy M. Hansen. Incentive-based Residential Energy Optimization Considering Comfort and Voltage Impacts. 2018 IEEE Power & Energy Society General Meeting (PESGM) 2018, 1 -5.

AMA Style

Priti Paudyal, Prateek Munankarmi, Zhen Ni, Timothy M. Hansen. Incentive-based Residential Energy Optimization Considering Comfort and Voltage Impacts. 2018 IEEE Power & Energy Society General Meeting (PESGM). 2018; ():1-5.

Chicago/Turabian Style

Priti Paudyal; Prateek Munankarmi; Zhen Ni; Timothy M. Hansen. 2018. "Incentive-based Residential Energy Optimization Considering Comfort and Voltage Impacts." 2018 IEEE Power & Energy Society General Meeting (PESGM) , no. : 1-5.

Journal article
Published: 12 July 2018 in Forecasting
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Forecasting hourly spot prices for real-time electricity markets is a key activity in economic and energy trading operations. This paper proposes a novel two-stage approach that uses a combination of Auto-Regressive Integrated Moving Average (ARIMA) with other forecasting models to improve residual errors in predicting the hourly spot prices. In Stage-1, the day-ahead price is forecasted using ARIMA and then the resulting residuals are fed to another forecasting method in Stage-2. This approach was successfully tested using datasets from the Iberian electricity market with duration periods ranging from one-week to ninety days for variables such as price, load and temperature. A comprehensive set of 17 variables were included in the proposed model to predict the day-ahead electricity price. The Mean Absolute Percentage Error (MAPE) results indicate that ARIMA-GLM combination performs better for longer duration periods, while ARIMA-SVM combination performs better for shorter duration periods.

ACS Style

Radhakrishnan Angamuthu Chinnathambi; Anupam Mukherjee; Mitch Campion; Hossein Salehfar; Timothy M. Hansen; Jeremy Lin; Prakash Ranganathan. A Multi-Stage Price Forecasting Model for Day-Ahead Electricity Markets. Forecasting 2018, 1, 26 -46.

AMA Style

Radhakrishnan Angamuthu Chinnathambi, Anupam Mukherjee, Mitch Campion, Hossein Salehfar, Timothy M. Hansen, Jeremy Lin, Prakash Ranganathan. A Multi-Stage Price Forecasting Model for Day-Ahead Electricity Markets. Forecasting. 2018; 1 (1):26-46.

Chicago/Turabian Style

Radhakrishnan Angamuthu Chinnathambi; Anupam Mukherjee; Mitch Campion; Hossein Salehfar; Timothy M. Hansen; Jeremy Lin; Prakash Ranganathan. 2018. "A Multi-Stage Price Forecasting Model for Day-Ahead Electricity Markets." Forecasting 1, no. 1: 26-46.

Conference paper
Published: 01 June 2018 in 2018 International Symposium on Power Electronics, Electrical Drives, Automation and Motion (SPEEDAM)
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Data centers have significant capital investments in large underutilized energy resources in the form of backup generators and batteries. In this paper, we propose to use these energy resources in demand response (DR) by operating a data center as a virtual power plant (VPP). An optimization model is designed which schedules the energy resources on a day-ahead basis using forecasted values of both renewable energy sources and the data center load for participation of the data center in DR. This optimization model also incorporates realtime dispatch of units to handle variations during operation. An improved battery cost model is designed and implemented as a soft constraint in the VPP energy management system (EMS) model, ensuring that the batteries' use in DR does not affect their float life. A case study is conducted in which the data center is connected to bus 8 of the modified IEEE 30-bus system. The results show that real-time operation of a data center participating in DR significantly reduces the operational cost, especially during network congestion, without causing battery degradation.

ACS Style

Prajina Tandukar; Labi Bajracharya; Timothy M. Hansen; Robert Fourney; Ujjwol Tamrakar; Reinaldo Tonkoski. Real-time Operation of a Data Center as Virtual Power Plant Considering Battery Lifetime. 2018 International Symposium on Power Electronics, Electrical Drives, Automation and Motion (SPEEDAM) 2018, 81 -86.

AMA Style

Prajina Tandukar, Labi Bajracharya, Timothy M. Hansen, Robert Fourney, Ujjwol Tamrakar, Reinaldo Tonkoski. Real-time Operation of a Data Center as Virtual Power Plant Considering Battery Lifetime. 2018 International Symposium on Power Electronics, Electrical Drives, Automation and Motion (SPEEDAM). 2018; ():81-86.

Chicago/Turabian Style

Prajina Tandukar; Labi Bajracharya; Timothy M. Hansen; Robert Fourney; Ujjwol Tamrakar; Reinaldo Tonkoski. 2018. "Real-time Operation of a Data Center as Virtual Power Plant Considering Battery Lifetime." 2018 International Symposium on Power Electronics, Electrical Drives, Automation and Motion (SPEEDAM) , no. : 81-86.

Conference paper
Published: 01 December 2017 in 2017 IEEE 19th International Conference on High Performance Computing and Communications; IEEE 15th International Conference on Smart City; IEEE 3rd International Conference on Data Science and Systems (HPCC/SmartCity/DSS)
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Assessing the effectiveness of a demand response (DR) program requires appropriate metrics of performance. In this paper, we propose the assessment of an aggregator-based residential DR program using two newly developed metrics addressing the economic and environmental aspects of sustainability. The economic sustainability metric of the DR method is quantified by the economic savings of the customers on electricity charges and the aggregator's profit. The environmental sustainability is quantified by measuring the reduction in capacity factors of fossil-fueled peaking power plants and the subsequent reduction in CO2 emissions. A simulation study is performed for a large-scale power system consisting of 5,555 users and 56,659 schedulable assets using real pricing data from a utility and a bulk electricity market for a 31-day period. Finally, we apply high-performance computing methods to the month-long study to yield a faster computation time.

ACS Style

Swagata Sharma; Venkat Durvasulu; Berk Celik; Siddharth Suryanarayanan; Timothy M. Hansen; Anthony A. Maciejewski; Howard Jay Siegel. Metrics-Based Assessment of Sustainability in Demand Response. 2017 IEEE 19th International Conference on High Performance Computing and Communications; IEEE 15th International Conference on Smart City; IEEE 3rd International Conference on Data Science and Systems (HPCC/SmartCity/DSS) 2017, 130 -137.

AMA Style

Swagata Sharma, Venkat Durvasulu, Berk Celik, Siddharth Suryanarayanan, Timothy M. Hansen, Anthony A. Maciejewski, Howard Jay Siegel. Metrics-Based Assessment of Sustainability in Demand Response. 2017 IEEE 19th International Conference on High Performance Computing and Communications; IEEE 15th International Conference on Smart City; IEEE 3rd International Conference on Data Science and Systems (HPCC/SmartCity/DSS). 2017; ():130-137.

Chicago/Turabian Style

Swagata Sharma; Venkat Durvasulu; Berk Celik; Siddharth Suryanarayanan; Timothy M. Hansen; Anthony A. Maciejewski; Howard Jay Siegel. 2017. "Metrics-Based Assessment of Sustainability in Demand Response." 2017 IEEE 19th International Conference on High Performance Computing and Communications; IEEE 15th International Conference on Smart City; IEEE 3rd International Conference on Data Science and Systems (HPCC/SmartCity/DSS) , no. : 130-137.

Proceedings article
Published: 01 July 2017 in 2017 IEEE Power & Energy Society General Meeting
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Solid State Transformers (SSTs) are power electronic-based transformers that will be a vital component of the future smart grid with high amount of renewable energy integration and the need for improved controllability. Among its various unique features, the reactive power compensating capabilities of SSTs can be exploited in future smart distribution systems for voltage regulation under high renewable energy penetrations. SSTs are power electronic devices that show fast and non-linear dynamics which means the simulation models are often complicated and need small time steps for accurate solutions. This prevents real-time and long-term simulation of large distribution systems as the simulations become computationally prohibitive. This paper designs a simplified equivalent model of an SST using simple current and voltage sources along with simple modeling equations. These simplified models can be used to perform long-term voltage regulation studies of distribution systems where traditional transformers are replaced with SSTs.

ACS Style

Manisha Maharjan; Ujjwol Tamrakar; Surendra Bajagain; Timothy M. Hansen; Reinaldo Tonkoski. A steady-state equivalent model of solid state transformers for voltage regulation studies. 2017 IEEE Power & Energy Society General Meeting 2017, 1 -5.

AMA Style

Manisha Maharjan, Ujjwol Tamrakar, Surendra Bajagain, Timothy M. Hansen, Reinaldo Tonkoski. A steady-state equivalent model of solid state transformers for voltage regulation studies. 2017 IEEE Power & Energy Society General Meeting. 2017; ():1-5.

Chicago/Turabian Style

Manisha Maharjan; Ujjwol Tamrakar; Surendra Bajagain; Timothy M. Hansen; Reinaldo Tonkoski. 2017. "A steady-state equivalent model of solid state transformers for voltage regulation studies." 2017 IEEE Power & Energy Society General Meeting , no. : 1-5.

Proceedings article
Published: 01 July 2017 in 2017 IEEE Power & Energy Society General Meeting
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In this paper, a pool-based market structure is implemented to trade demand response (DR) in a fully deregulated day-ahead electricity market. In this structure, the demand response aggregator provides load shifting/curtailment as DR offers to the demand response exchange (DRX) market competitively. The independent system operator (ISO) utilizes the DR service only during economic inefficiency. The DRX needs to clear the DR offers such that the overall system economic efficiency improves. Two search techniques have been implemented to clear the DRX market efficiently. One of the search methods is a local search where one DR offer is selected at a time; the other is the genetic algorithm (GA). We implement a rank-based GA in which the bus sensitivities were used for seeding the initial population to speed up convergence. These search techniques are implemented on IEEE RTS-96 system, and the DRX was cleared efficiently to improve the economic performance of the system.

ACS Style

Venkat Durvasulu; Hendy Syahril; Timothy M. Hansen. A genetic algorithm approach for clearing aggregator offers in a demand response exchange. 2017 IEEE Power & Energy Society General Meeting 2017, 1 -5.

AMA Style

Venkat Durvasulu, Hendy Syahril, Timothy M. Hansen. A genetic algorithm approach for clearing aggregator offers in a demand response exchange. 2017 IEEE Power & Energy Society General Meeting. 2017; ():1-5.

Chicago/Turabian Style

Venkat Durvasulu; Hendy Syahril; Timothy M. Hansen. 2017. "A genetic algorithm approach for clearing aggregator offers in a demand response exchange." 2017 IEEE Power & Energy Society General Meeting , no. : 1-5.

Review
Published: 26 June 2017 in Applied Sciences
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The modern power system is progressing from a synchronous machine-based system towards an inverter-dominated system, with large-scale penetration of renewable energy sources (RESs) like wind and photovoltaics. RES units today represent a major share of the generation, and the traditional approach of integrating them as grid following units can lead to frequency instability. Many researchers have pointed towards using inverters with virtual inertia control algorithms so that they appear as synchronous generators to the grid, maintaining and enhancing system stability. This paper presents a literature review of the current state-of-the-art of virtual inertia implementation techniques, and explores potential research directions and challenges. The major virtual inertia topologies are compared and classified. Through literature review and simulations of some selected topologies it has been shown that similar inertial response can be achieved by relating the parameters of these topologies through time constants and inertia constants, although the exact frequency dynamics may vary slightly. The suitability of a topology depends on system control architecture and desired level of detail in replication of the dynamics of synchronous generators. A discussion on the challenges and research directions points out several research needs, especially for systems level integration of virtual inertia systems.

ACS Style

Ujjwol Tamrakar; Dipesh Shrestha; Manisha Maharjan; Bishnu P. Bhattarai; Timothy M. Hansen; Reinaldo Tonkoski. Virtual Inertia: Current Trends and Future Directions. Applied Sciences 2017, 7, 654 .

AMA Style

Ujjwol Tamrakar, Dipesh Shrestha, Manisha Maharjan, Bishnu P. Bhattarai, Timothy M. Hansen, Reinaldo Tonkoski. Virtual Inertia: Current Trends and Future Directions. Applied Sciences. 2017; 7 (7):654.

Chicago/Turabian Style

Ujjwol Tamrakar; Dipesh Shrestha; Manisha Maharjan; Bishnu P. Bhattarai; Timothy M. Hansen; Reinaldo Tonkoski. 2017. "Virtual Inertia: Current Trends and Future Directions." Applied Sciences 7, no. 7: 654.