Open Access
An energy management system design using fuzzy logic control: smoothing the grid power profile of a residential electro-thermal microgrid
(IEEE, 2021) Arcos Avilés, Diego; Pascual Miqueleiz, Julio María; Guinjoan Gispert, Francesc; Marroyo Palomo, Luis; García Gutiérrez, Gabriel; Gordillo, Rodolfo; Llanos, Jacqueline; Sanchis Gúrpide, Pablo; Motoasca, Emilia; Ingeniería Eléctrica, Electrónica y de Comunicación; Ingeniaritza Elektrikoa, Elektronikoaren eta Telekomunikazio Ingeniaritzaren
This work deals with the design of a Fuzzy Logic Control (FLC) based Energy Management System (EMS) for smoothing the grid power prole of a grid-connected electro-thermal microgrid. The case study aims to design an Energy Management System (EMS) to reduce the impact on the grid power when renewable energy sources are incorporated to pre-existing grid-connected household appliances. The scenario considers a residential microgrid comprising photovoltaic and wind generators, at-plate collectors, electric and thermal loads and electrical and thermal energy storage systems and assumes that neither renewable generation nor the electrical and thermal load demands are controllable. The EMS is built through two low-complexity FLC blocks of only 25 rules each. The first one is in charge of smoothing the power prfile exchanged with the grid, whereas the second FLC block drives the power of the Electrical Water Heater (EWH). The EMS uses the forecast of the electrical and thermal power balance between generation and consumption to predict the microgrid behavior, for each 15-minute interval, over the next 12 hours. Simulations results, using real one-year measured data show that the proposed EMS design achieves 11.4% reduction of the maximum power absorbed from the grid and an outstanding reduction of the grid power profile ramp-rates when compared with other state-of-the-art studies.
Open Access
Energy management for an electro-thermal renewable based residential microgrid with energy balance forecasting and demand side management
(Elsevier, 2021) Pascual Miqueleiz, Julio María; Arcos Avilés, Diego; Ursúa Rubio, Alfredo; Sanchis Gúrpide, Pablo; Marroyo Palomo, Luis; Ingeniería Eléctrica, Electrónica y de Comunicación; Institute of Smart Cities - ISC; Ingeniaritza Elektrikoa, Elektronikoaren eta Telekomunikazio Ingeniaritzaren
This paper proposes an energy management strategy for a residential microgrid comprising photovoltaic (PV) panels, a small wind turbine and solar thermal collectors. The microgrid can control the power exchanged with the grid thanks to a battery and a controllable electric water heater, which provide two degrees of freedom to the control strategy. As input data, the proposed control strategy uses the battery state of charge (SOC), the temperature of the hot water tank, the power of each microgrid element as well as the demand and renewable generation forecasts. By using forecasted data and by controlling the electric water heater, the strategy is able to achieve a better grid power profile while using a smaller battery than previous works, hence reducing the overall cost of the system. The strategy is tested by means of simulation with real data for one year and it is also experimentally validated in the microgrid built at the Renewable Energy Laboratory at the UPNA.
Open Access
Identification of critical parameters for the design of energy management algorithms for Li-ion batteries operating in PV power plants
(IEEE, 2020) Berrueta Irigoyen, Alberto; Soto Cabria, Adrián; Marcos Álvarez, Javier; Parra Laita, Íñigo de la; Sanchis Gúrpide, Pablo; Ursúa Rubio, Alfredo; Ingeniaritza Elektrikoa, Elektronikoaren eta Telekomunikazio Ingeniaritzaren; Institute of Smart Cities - ISC; Ingeniería Eléctrica, Electrónica y de Comunicación; Universidad Pública de Navarra / Nafarroako Unibertsitate Publikoa, ReBMS PJUPNA1904; Gobierno de Navarra / Nafarroako Gobernua, 0011-1411-2018-000029 GERA
Lithium-ion batteries are gaining importance for a variety of applications due to their price decrease and characteristics improvement. For a proper use of such storage systems, an energy management algorithm (EMA) is required. A number of EMAs, with various characteristics, have been published recently, given the diverse nature of battery problems. The EMA of deterministic battery problems is usually based on an optimization algorithm. The selection of such an algorithm depends on a few problem characteristics, which need to be identified and closely analyzed. The aim of this article is to identify the critical optimization problem parameters that determine the most suitable EMA for a Li-ion battery. With this purpose, the starting point is a detailed model of a Li-ion battery. Three EMAs based on the algorithms used to face deterministic problems, namely dynamic, linear, and quadratic programming, are designed to optimize the energy dispatch of such a battery. Using real irradiation and power price data, the results of these EMAs are compared for various case studies. Given that none of the EMAs achieves the best results for all analyzed cases, the problem parameters that determine the most suitable algorithm are identified to be four, i.e., desired computation intensity, characteristics of the battery aging model, battery energy and power capabilities, and the number of optimization variables, which are determined by the number of energy storage systems, the length of the optimization problem, and the desired time step.
Open Access
Critical comparison of energy management algorithms for lithium-ion batteries in renewable power plants
(IEEE, 2019) Berrueta Irigoyen, Alberto; Soto Cabria, Adrián; García Solano, Miguel; Parra Laita, Íñigo de la; Sanchis Gúrpide, Pablo; Ursúa Rubio, Alfredo; Ingeniaritza Elektrikoa, Elektronikoaren eta Telekomunikazio Ingeniaritzaren; Institute of Smart Cities - ISC; Ingeniería Eléctrica, Electrónica y de Comunicación; Universidad Pública de Navarra / Nafarroako Unibertsitate Publikoa
Lithium-ion batteries are gaining importance for a variety of applications due to their price decrease and characteristics improvement. A good energy management strategy is required in order to increase the profitability of an energy system using a Li-ion battery for storage. The vast number of management algorithms that has been proposed to optimize the achieved profit, with diverse computational power requirements and using models with different complexity, raise doubts about the suitability of an algorithm and the required computation power for a particular application. The performance of three energy management algorithms based on linear, quadratic, and dynamic programming are compared in this work. A realistic scenario of a medium-sized PV plant with a constraint of peak shaving is used for this comparison. The results achieved by the three algorithms are compared and the grounds of the differences are analyzed. Among the three compared algorithms, the quadratic one seems to be the most suitable for renewableenergy applications, given the undue simplification of the battery aging required by the linear algorithm and the discretization and computational power required by a dynamic algorithm.

Sanchis Gúrpide, Pablo

Email Address

person.page.identifierURI

Birth Date

Job Title

Last Name

First Name

person.page.departamento

person.page.instituteName

ORCID

person.page.observainves

person.page.upna

Name

Filters

Author

Subject

Date

Has files

Item Type

Type

Settings

Sort By

Results per page

Search Results