III Level Course

"Control and Optimization in Smart-Grids"

Teacher: Fredy Orlando Ruiz-Palacios (Pontificia Universidad Javeriana of Bogota', Colombia)

Aims of course
In recent years, several factors have induced a revolution in the way power systems are operated and controlled. For example, the incorporation of renewable energies to the generation portfolio imposes limitations in the controllability of the power generation. In few decades, the operation has evolved from big (usually national) electric companies that own and operate generation plants, transmission assets and distribution systems to a dynamic environment with many players that compete in uncertain markets, selling and buying energy from traditional and random sources. There is also a social pressure to reduce the carbon foot-print of the energy sector.
The introduction of Information and communication technologies (ICT) in the electric sector has opened a great opportunities for the application of optimization and automatic control techniques in the operation of the power systems. For example, the optimal scheduling of generation plants in front of uncertain renewable source, or the manipulation of flexible loads, such as, electric vehicles to balance load and generation. The new environment is plenty of opportunities for the application of optimization and control methods, for the proper sizing, design and operation of modern (smart) grids.
This course describes some of the existing challenges in smart-grids, where researchers from the control community can offer possible innovative solutions. Some of these challenges are the optimal management of flexible loads to minimize the requirement of carbon-intensive generation, or the automatic operation of storage devices, minimizing the negative effect of variable wind sources.

Course length: 20 hours

Course language: English

Course schedule:
    - lesson #1:   Tuesday  08/05/2018, from 14.00 to 18:00, c/o Aula C
    - lesson #2:   Thursday 10/05/2018, from 09.00 to 12:00, c/o Aula C
    - laboratory:  Tuesday  15/05/2018, from 09.00 to 12:00, c/o LaDiSpe sez. Automatica
    - lesson #3:   Thursday 17/05/2018, from 09.00 to 12:00, c/o Aula C
    - lesson #4:   Tuesday  22/05/2018, from 14.00 to 18:00, c/o Aula C
    - lesson #5:   Thursday 24/05/2018, from 09.00 to 12:00, c/o Aula C

The lessons will be held in AULA C (near Aula 14), while the laboratory will be held in LADISPE sez. Automatica (just over Aula 14) of the Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129, Torino.

Involved Doctorate Courses: Ing. Informatica e dei Sistemi; Energetica; Fisica;  Fluidodinamica; Ing. Aerospaziale; Ing. Ambientale; Ing. Biomedica; Ing. Chimica; Ing. Civile e Ambientale; Ing. delle Strutture; Ing. Elettrica; Ing. Elettronica; Ing. Elettrica, Elettronica e delle Comunicazioni; Ing. Idraulica; Matematica per le Scienze dell'Ingegneria; Ing. Meccanica; Meccanica Applicata; Meccatronica; Metrologia: Scienze e Tecnica delle Misure; Progettazione e Costruzione di Macchine; Scienza e Tecnologia dei Materiali

Course contents

1) Introduction to Power systems operation.
In this introductory session, a broad overview of power systems is performed. It is described how electric systems are operated today. Then, the challenges imposed by the introduction of renewable sources and possible solutions are illustrated.
     a. From generation to the consumer.
     b. From vertically integrated utilities to deregulated markets.
     c. ICT in power systems.
     d. Renewable energies and the grid revolution.
     e. Modeling and prediction of wind and solar generation.
     f. Dispatching random sources.
     g. Ancillary services and new market actors.

2) Reorganization of electricity markets.
The co-existence of a variety of generation technologies is an interesting problem from a gaming point of view and even more with the integration of DR into the electricity market. The generators have different technologies, costs, revenues, and each firm seeks to maximize its profit (the difference between producer's revenue and costs). The system operator is responsible for arbitrage services in order to establish a proper environment for competition, guaranteeing a reliable operation and minimizing cost and possibly green-house emissions. In this session variants of the classic economic dispatch are studied.
     a. Selling random energy (Incorporation of uncertain renewables in energy markets).
     b. Joint energy and reserve markets, bi-level optimization.
     c. Time of use tariffs.
     d. Duration differentiated energy services.

3) Demand side management.
Demand Response (DR) is one of the most vital parts of the future smart grid. There are different ways to activate DR in the electric power. Broadly defined, controllable programs and indirect methods are found as DR solutions, which, are tools implemented by system operator (SO) to balance the demand with power generation by means of load modification. In particular, indirect methods are performed by changing energy price or giving an incentive payment. There are three key components of an incentive-based DR program:
1) A baseline, 2) A payment scheme and 3) Terms and conditions (such as penalties). Given the fact that incentive-based DR presents gaming concerns, mechanism design or contracts are studied in order to address these problems and guaranteeing that each agent reveals his truthful private information.  Some solutions for DR are presented and their properties analyzed.
     a. The new role of the consumer-prosumer.
     b. Incentive-based demand response.
          i. Strategic User behavior.
         ii. Mechanism design for DR.
        iii. The baseline estimation problem.

4) Flexible loads and DR.
Balance problems can be handled by DR initiatives in the energy consuming sectors. In order to solve balance problems, these sectors take advantage of several flexible loads that can provide energy services to the grid. Flexible loads can be clustered into two categories: adjustable and deferrable loads. An adjustable load is flexible during all time service. For example, Thermostatically Controlled Loads (TCLs) are adjusted by modifying the temperature set-point fixed by the user. A deferrable load has a fixed energy requirement at the end of the service. For example, a pool pump must be switched on a determined amount of time by the end of the day and can provide regulation services by turning it on and off; or an Electric Vehicle (EV) state of charge should be above a certain level at the departure time. Flexible loads can provide ancillary services such as regulation, spinning reserve, among others.
     a. Direct load control.
         i. Optimal scheduling of flexible loads.
        ii. The aggregation and synchronization problem.
     b. Electric vehicles.
          i. The Vehicle to grid concept.
         ii. EVs as storage resources.
        iii. Economic MPC of Vehicle charging operation.
         iv. Offering ancillary services through optimal charging.

5) Control of Micro-grids.
In standalone micro-grids, like the ones built in rural and remote regions with no access to the power grid, it is essential to have control systems that ensure optimal performance in the generation and storage of electrical energy for long periods of time.
Proper sizing of generation and storage assets is a fundamental step in the development of isolated systems. Also, proper estimation of the Battery State of Charge (SoC) is a fundamental problem in micro-grids operation. Finally, matching load with generation comes
as a low-cost solution in isolated systems with limited energy supply.
     a. Lean energy concept
     b. What criteria shall be used for optimal grid sizing?
     c. Balancing generation with demand.
     d. Battery state of charge estimation.
     e. Expanding battery life with Demand side management.

In addition to theoretical lectures, where the basic concepts and results are developed, a simulation session is developed, where sample problems and case studies are solved employing numeric methods and scientific software tools, such as Matlab.

Essential references:
Kirschen D., Strbac G., Fundamentals of Power System Economics, John Wiley & Sons, ISBN: 978-0470845721, 2005.
Morales González J.M., Conejo A.J., Madsen H., Pinson P., Zugno M., Integrating Renewables in Electricity Markets: Operational Problems, Springer: International Series in Operations Research and Management Science, vol. 205, DOI: 10.1007/978-1-4614-9411-9, 2014.
Bitar E. Y., Rajagopal R., Khargonekar P. P., Poolla K., Varaiya P., Bringing Wind Energy to Market, IEEE Transactions on Power Systems, vol. 27, no. 3, pp. 1225-1235, August 2012.
Rajagopal R., Bitar E., Varaiya P., Wu F., Risk-Limiting Dispatch for Integrating Renewable Power. International Journal of Electrical Power & Energy Systems, vol. 44, 2011.


Teaching material: Final exam: rules

For further information, please contact:
- prof. Fredy Ruiz,          tel. 011-090.7063, e-mail: ruizf@javeriana.edu.co
- prof. Michele Taragna, tel. 011-090.7063, e-mail: michele.taragna@polito.it


Michele Taragna                             Ultimo aggiornamento di questa pagina: 23/05/2018, 14:00 (M.T.)