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Kamalinia S.,SandC Electrical Company | Shahidehpour M.,Illinois Institute of Technology | Wu L.,Clarkson University
Applied Energy | Year: 2014

This study investigates the role of sustainable energy volatility in a market participant's competitive expansion planning problem. The incomplete information non-cooperative game-theoretic method is utilized in which each generation company (GENCO) perceives strategies of other market participants in order to make a decision on its strategic generation capacity expansion. Sustainable generation incentives, carbon emission penalties, and fuel price forecast errors are considered in the strategic decisions. The market clearing process for energy and reserves is simulated by each GENCO for deriving generation expansion decisions. A merit criterion (i.e., the utility value) is proposed for a more realistic calculation of the expected payoff of a GENCO with sustainable energy resources. Finally, the impact of transmission constraints is investigated on the GENCO's expansion planning decision. The case studies illustrate the effectiveness of the proposed method. © 2014 Elsevier Ltd. Source

Aminifar F.,University of Tehran | Shahidehpour M.,Illinois Institute of Technology | Fotuhi-Firuzabad M.,Sharif University of Technology | Kamalinia S.,SandC Electrical Company
IEEE Transactions on Instrumentation and Measurement | Year: 2014

The dynamic state estimation (DSE) applied to power systems with synchrophasor measurements would estimate the system's true state based on measurements and predictions. In this application, as phasor measurement units (PMUs) are not deployed at all power system buses, state predictions would enhance the redundancy of DSE input data. The significance of predicted and measured data in DSE is affected by their confidence levels, which are inversely proportional to the corresponding variances. In practice, power system states may undergo drastic changes during hourly load fluctuations, component outages, or network switchings. In such conditions, the inclusion of predicted values could degrade the power system state estimation. This paper presents a mixed-integer programming formulation of DSE that is capable of simultaneously discarding predicted values whenever sudden changes in the system state are detected. This feature enhances the DSE computation and will not require iterative executions. The proposed model accommodates system-wide synchronized measurements of PMUs, which could be of interest to smart grid applications in energy management systems. The voltage phasors at buses without PMUs are calculated via voltage and current measurements of adjacent buses, which are referred to as indirect measurements. The guide to the expression of uncertainty in measurement is used for computing the confidence level of indirect measurements based on uncertainties associated with PMU measurements as well as with transmission line parameters. Simulation studies are conducted on an illustrative three-bus example and the IEEE 57-bus power system, and the performance of the proposed model is thoroughly discussed. © 2013 IEEE. Source

Kamalinia S.,SandC Electrical Company | Wu L.,Clarkson University | Shahidehpour M.,Illinois Institute of Technology
IEEE Transactions on Sustainable Energy | Year: 2014

This paper presents a stochastic security-constrained unit commitment (SCUC) model for the optimal midterm and flexible allocations of hydro and natural gas systems when accommodating a large integration of wind energy. Random errors in forecasting the hourly wind, natural water inflow, and electric load as well as random outages of power system components are modeled in scenarios via the Monte Carlo (MC) simulation. The proposed optimization model is formulated as a two-stage stochastic problem, where short-term and midterm generation resource optimizations are investigated in the first and the second stages, respectively. The reliability criteria including the loss of load expectation (LOLE) and load curtailment limits are incorporated into the midterm stochastic SCUC problem, where electric power and natural gas network constraints are checked. Numerical experiments signify the effectiveness of the proposed method for the midterm optimal scheduling of water and natural gas flexibilities when integrating wind energy resources. © 2010-2012 IEEE. Source

Khodaei A.,Illinois Institute of Technology | Shahidehpour M.,Illinois Institute of Technology | Bahramirad S.,SandC Electrical Company
IEEE Transactions on Smart Grid | Year: 2011

In this paper, the hourly demand response (DR) is incorporated into security-constrained unit commitment (SCUC) for economic and security purposes. SCUC considers fixed and responsive loads. Unlike fixed hourly loads, responsive loads are modeled with their intertemporal characteristics. The responsive loads linked to hourly market prices can be curtailed or shifted to other operating hours. The study results show that DR could shave the peak load, reduce the system operating cost, reduce fuel consumptions and carbon footprints, and reduce the transmission congestion by reshaping the hourly load profile. Numerical simulations in this paper exhibit the effectiveness of the proposed approach. © 2011 IEEE. Source

Masiello R.D.,DNV GL | Roberts B.,SandC Electrical Company | Sloan T.,Kansas House of Representatives
Proceedings of the IEEE | Year: 2014

Energy storage is a novel technology with perceived performance and lifecycle risks. In addition, there are many different business/regulatory paradigms for investors in storage resources based on existing business models for electric power assets today. At the heart of designing storage applications for best cost-benefit results and for evaluating storage economics of particular applications is the way different business models realize direct monetized benefits and indirect avoided costs from energy storage. This paper unpacks the complexities of deploying and operating energy storage and identifies any potential barriers to participation in storage. It lays out some of the existing and hypothetical business models for the investment in and operation of electric storage, and explores the complexities and possibilities of these business models when storage is bucketed' as a generation, transmission, distribution, or customer asset. It also identifies possible policy recommendations and areas for further analysis, including some alternative models that consider storage as a unique asset class that offers services offered by other assets today. © 1963-2012 IEEE. Source

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