Marija D. Ilic

Optimal Charge Control of Plug-In Hybrid Electric Vehicles in Deregulated Electricity Markets

Plug-in hybrid electric vehicles are a midterm solution to reduce the transportation sectors dependency on oil. However, if implemented in a large scale without control, peak load increases significantly and the grid may be overloaded. Two algorithms to address this problem are proposed and analyzed. Both are based on a forecast of future electricity prices and use dynamic programming to find the economically optimal solution for the vehicle owner. The first optimizes the charging time and energy flows. It reduces daily electricity cost substantially without increasing battery degradation. The latter also takes into account vehicle to grid support as a means of generating additional profits by participating in ancillary service markets. Constraints caused by vehicle utilization as well as technical limitations are taken into account. An analysis, based on data of the California independent system operator, indicates that smart charge timing reduces daily electricity costs for driving from

Stabilizing a multimachine power system via decentralized feedback linearizing excitation control

0.43 to

Wind Integration in Power Systems: Operational Challenges and Possible Solutions

0.2. Provision of regulating power substantially improves plug-in hybrid electric vehicle economics and the daily profits amount to

Parallel processing in power systems computation

1.71, including the cost of driving.

Modeling of Future Cyber–Physical Energy Systems for Distributed Sensing and Control

A new controller for the generator excitation system is described that uses a combination of feedback linearizing and the observation decoupled state space. This creates a controller that can be realistically implemented using only local measurements, and whose performance is consistent with respect to changes in network configuration, loading and power transfer conditions. The control differs in this respect from linear constant-gain controllers such as power system stabilizers, whose characteristics can vary significantly with changes in operating conditions. The design is well-suited to a multimachine setting, in that it is not based on an infinite-bus approximation. Simulations were performed on a 38-bus reduced modelof the Northeast Power Coordinating Council system and benchmarked against simulations in which automatic voltage regulators with power system stabilizers were substituted in place of the nonlinear controls. >

Optimal investments in power generation under centralized and decentralized decision making

This paper surveys major technical challenges for power system operations in support of large-scale wind energy integration. The fundamental difficulties of integrating wind power arise from its high inter-temporal variation and limited predictability. The impact of wind power integration is manifested in, but not limited to, scheduling, frequency regulations, and system stabilization requirements. Possible alternatives are suggested for a more reliable and cost-effective power system operation. New computationally efficient methods for improving system performances by using prediction and operational interdependencies over different time horizons remain critical open research problems.

A mathematical framework for the analysis and management of power transactions under open access

The availability of parallel processing hardware and software presents an opportunity and a challenge to apply this new computation technology to solve power system problems. The allure of parallel processing is that this technology has the potential to be cost effectively used on computationally intense problems. The objective of this paper is to define the state of the art and identify what the authors see to be the most fertile grounds for future research in parallel processing as applied to power system computation. As always, such projections are risky in a fast changing field, but the authors hope that this paper will be useful to the researchers and practitioners in this growing area.

Efficient Coordination of Wind Power and Price-Responsive Demand—Part I: Theoretical Foundations

This paper proposes modeling the rapidly evolving energy systems as cyber-based physical systems. It introduces a novel cyber-based dynamical model whose mathematical description depends on the cyber technologies supporting the physical system. This paper discusses how such a model can be used to ensure full observability through a cooperative information exchange among its components; this is achieved without requiring local observability of the system components. This paper also shows how this cyber-physical model is used to develop interactive protocols between the controllers embedded within the system layers and the network operator. Our approach leads to a synergistic framework for model-based sensing and control of future energy systems. The newly introduced cyber-physical model has network structure-preserving properties that are key to effective distributed decision making. The aggregate load modeling that we develop using data mining techniques and novel sensing technologies facilitates operations of complex electric power systems.

Feedback linearizing excitation control on a full-scale power system model

This work presents a novel model for optimization of investments in new power generation under uncertainty. The model can calculate optimal investment strategies under both centralized social welfare and decentralized profit objectives. The power market is represented with linear supply and demand curves. A stochastic dynamic programming algorithm is used to solve the investment problem, where uncertainty in demand is represented as a discrete Markov chain. The stochastic dynamic model allows us to evaluate investment projects in new base and peak load power generation as real options, and determine optimal timing of the investments. In a case study, we use the model to compare optimal investment strategies under centralized and decentralized decision making. A number of interesting results follow by varying the assumptions about market structure and price response on the demand side.

Model predictive economic/environmental dispatch of power systems with intermittent resources

Several models are being considered by the power industry for competition under open access transmission. Each alternative offers a radically different solution which must be evaluated, not only in terms of economic benefits, but also in terms of impact on power system security. This paper therefore presents a general mathematical framework for the analysis and management of power transactions under open access subject to system security constraints. The framework introduces the notions of a virtual network of transactions and the transactions matrix, both describing virtual power flows among financial entities. Finally, this paper shows how the transactions selected by the market forces are influenced by the security requirements of the physical network.