University Symphony and Student Soloists in a Concerto Concert, January 13, 1963

Concert program for University Symphony and Student Soloists in a Concerto Concert, January 13, 1963

University Concert Band, December 6, 1964

Concert program for University Concert Band, December 6, 1964

Concert of Harpsichord Music, November 3, 1966

Concert Program for Concert of Harpsichord Music, November 3, 1966

A Concert of 17th and 18th Century Music, November 16, 1953

Concert Program for A Concert of 17th and 18th Century Music, November 16, 1953

Noon Concert, William Bolcom, Harrison Ryker, Bruce Bailey, February 1, 1966

Concert Program for Noon Concert, William Bolcom, Harrison Ryker, Bruce Bailey, February 1, 1966

A Concert of Japanese Music, January 20, 1966

Concert Program for A Concert of Japanese Music, January 20, 1966

A Concert of Works by Ross Lee Finney, 1966

Concert Program for A Concert of Works by Ross Lee Finney, 1966

A Concert of American Music, February 9, 1964

Concert Program for A Concert of American Music, February 9, 1964

Concerto Concert with Members of the University Symphony Orchestra, May 14, 1969

Concert program for Concerto Concert with members of the University Symphony Orchestra, May 14, 1969

The Winter Jazz Concert, December 8, 1976

Concert program for The Winter Jazz Concert, December 8, 1976

Annual Christmas Concert, December 14, 1933

Concert Program for Annual Christmas Concert, December 14, 1933

Concert Program for Mallet Head Series, Mallet Jazz October 19, 2012

Concert Program

Virtual power players demand response programs management based on locational marginal prices

Power systems have been suffering huge changes mainly due to the substantial increase of distributed generation and to the operation in competitive environments. Virtual power players can aggregate a diversity of players, namely generators and consumers, and a diversity of energy resources, including electricity generation based on several technologies, storage and demand response. Resource management gains an increasing relevance in this competitive context, while demand side active role provides managers with increased demand elasticity. This makes demand response use more interesting and flexible, giving rise to a wide range of new opportunities.This paper proposes a methodology for managing demand response programs in the scope of virtual power players. The proposed method is based on the calculation of locational marginal prices (LMP). The evaluation of the impact of using demand response specific programs on the LMP value supports the manager decision concerning demand response use. The proposed method has been computationally implemented and its application is illustrated in this paper using a 32 bus network with intensive use of distributed generation.

A simulation tool for demand response programs implementation

The design and development of simulation models and tools for Demand Response (DR) programs are becoming more and more important for adequately taking the maximum advantages of DR programs use. Moreover, a more active consumers’ participation in DR programs can help improving the system reliability and decrease or defer the required investments. DemSi, a DR simulator, designed and implemented by the authors of this paper, allows studying DR actions and schemes in distribution networks. It undertakes the technical validation of the solution using realistic network simulation based on PSCAD. DemSi considers the players involved in DR actions, and the results can be analyzed from each specific player point of view.

Using data mining techniques to support DR programs definition in smart grids

In recent years, Power Systems (PS) have experimented many changes in their operation. The introduction of new players managing Distributed Generation (DG) units, and the existence of new Demand Response (DR) programs make the control of the system a more complex problem and allow a more flexible management. An intelligent resource management in the context of smart grids is of huge important so that smart grids functions are assured. This paper proposes a new methodology to support system operators and/or Virtual Power Players (VPPs) to determine effective and efficient DR programs that can be put into practice. This method is based on the use of data mining techniques applied to a database which is obtained for a large set of operation scenarios. The paper includes a case study based on 27,000 scenarios considering a diversity of distributed resources in a 32 bus distribution network.