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In this paper, we consider the problem of controlling power consumption dynamics of residential heating, ventilation and air conditioning (HVAC) units so that they follow the grid-side power specifications. In order to do so, we design a novel dynamical energy controller which ensures regulation of the cumulative effects of power imbalances. For this, we derive a novel energy-based model that relates the HVAC physics-based dynamics to both real and reactive power balance at the point of interconnection with the grid. In contrast to several other approaches in the literature, we show that a limited number of HVAC units can meet the stringent performance metrics set by the ARPA-E/NODES program on following the frequency regulation signal, while maintaining consumer comfort. Theoretical and simulation-based model and control validation is provided by making use of real-world HVAC data., Comment: Preprint submitted to IEEE Transactions on Control Systems Technology

The power interactions of any component in electric energy systems with the rest of the system happen naturally, as governed by the energy conservation principles. There may, however, occur instances when the rate at which power gets generated by one component through local energy conversion is not exactly the same as that absorbed by rest of the system. This is when instabilities get induced. To model and control such instabilities, this paper generalizes the notion of interaction variable used to characterize diverse system components in a unified manner. The same variable captures aggregate system-wide effects and sets reference points for multi-layered distributed output feedback control. It has a physical interpretation of instantaneous power and generalized reactive power. The higher layer design utilizes the interactive energy state-space model to derive intermediate reactive power control, which becomes a control command to the lower layer physical model. This command is implemented using either Feedback Linearizing Control (FBLC) or Sliding Mode Control (SMC), for which sufficient stability conditions are stated. This paper claims that the proposed design is fundamental to aligning dynamic interactions between components for stability and feasibility. Without loss of generality, we utilize a simple RLC circuit with a controllable voltage source for illustrations, which is a simplified representation of any controllable component in microgrids., Comment: Preprint submitted to Automatica (Revision 1)

A qualitatively different graduate level curriculum for teaching electric power systems is needed. The motivation for such a new curriculum is outlined, and a specific program, now being implemented at Carnegie Mellon University, is described. The new curriculum: 1) provides students with a multidisciplinary introduction to the changing problems of the industry; 2) stresses the need for teaching systematic approaches to formulating power system problems; and 3) integrates teaching of the fundamentals for power systems with the fundamentals for other network industries. The program, referred to as the MS in Electric Power Systems (MSEPS) Program, is being developed as a special power-focused track within Carnegie Mellon's existing multidisciplinary Information Networking Institute (INI).

The concept of plug-in electric vehicles (PEV) are gaining increasing popularity in recent years, due to the growing societal awareness of reducing greenhouse gas (GHG) emissions, and gaining independence on foreign oil or petroleum. Large-scale deployment of PEVs currently faces many challenges. One particular concern is that the PEV charging can potentially cause significant impacts on the existing power distribution system, due to the increase in peak load. As such, this work tries to mitigate the impacts of PEV charging by proposing a decentralized smart PEV charging algorithm to minimize the distribution system load variance, so that a `flat' total load profile can be obtained. The charging algorithm is myopic, in that it controls the PEV charging processes in each time slot based entirely on the current power system states, without knowledge about future system dynamics. We provide theoretical guarantees on the asymptotic optimality of the proposed charging algorithm. Thus, compared to other forecast based smart charging approaches in the literature, the charging algorithm not only achieves optimality asymptotically in an on-line, and decentralized manner, but also is robust against various uncertainties in the power system, such as random PEV driving patterns and distributed generation (DG) with highly intermittent renewable energy sources., Comment: 12 pages, 9 figures

America seems to have decided that a "smart grid" is what we need to solve the problems of our electric power system. But, what exactly is a "smart grid"? The answer is that it is many different things. Some of the things that get talked about are relatively inexpensive and can go a long way toward solving key problems. Others will likely be very expensive, and at this stage may better be left to the realm of research.

Restructuring efforts in the U.S. electric power sector have tried to encourage transmission investment by independent (non-utility) transmission companies, and have promoted various levels of market-based transmission investment. Underlying this shift to merchant transmission investment is an assumption that new transmission infrastructure can be classified as providing a congestion-relief benefit or a reliability benefit. In this paper, we demonstrate that this assumption is largely incorrect for meshed interconnections such as electric power networks. We focus on a particular network topology known as the Wheatstone network to show how congestion and reliability can represent tradeoffs. Lines that cause congestion may be justified on reliability grounds. We decompose the congestion and reliability effects of a given network alteration, and demonstrate their dependence through simulations on a 118bus test network. The true relationship between congestion and reliability depends critically on identifying the relevant range of demand for evaluating any network externalities.

Although human error can be the proximate cause of a blackout, the real causes are found much deeper in the power system.

The essential oil isolated from Erica spiculifolia Salisb. by hydrodistillation was analysed by GC-MS. One hundred compounds representing 92.6% of total oil were identified. Among the detected compounds 38 were monoterpenoids (46.2%), 30 were sesquiterpenoids (31.7%), 2 diterpene (0.4%) and 30 compounds (14.3%) were with various non-terpenoid structures. Oxygenated monoerpenes were by far the main class (45.3%) with α-terpineol (7.5%) endo-borneol (7.2%), pinocarveol (5.9%) and thymol (3.7%) as the major compounds. The predominant components of sesquiterpenes were caryophyllene oxide (5.0%), caryophyllene (4.2%), τ –murrolol (3.5%), spathulenol (2.9) and α-cadinol (2.3%).

The essential oil isolated from Erica spiculifolia Salisb. by hydrodistillation was analysed by GC-MS. One hundred compounds representing 92.6% of total oil were identified. Among the detected compounds 38 were monoterpenoids (46.2%), 30 were sesquiterpenoids (31.7%), 2 diterpene (0.4%) and 30 compounds (14.3%) were with various non-terpenoid structures. Oxygenated monoerpenes were by far the main class (45.3%) with α-terpineol (7.5%) endo-borneol (7.2%), pinocarveol (5.9%) and thymol (3.7%) as the major compounds. The predominant components of sesquiterpenes were caryophyllene oxide (5.0%), caryophyllene (4.2%), τ –murrolol (3.5%), spathulenol (2.9) and α-cadinol (2.3%).