Open Access
A PV ramp-rate control strategy to extend battery lifespan using forecasting
(Elsevier, 2022) González Moreno, Alejandro; Marcos Álvarez, Javier; Parra Laita, Íñigo de la; Marroyo Palomo, Luis; Ingeniería Eléctrica, Electrónica y de Comunicación; Ingeniaritza Elektrikoa, Elektronikoaren eta Telekomunikazio Ingeniaritzaren; Universidad Pública de Navarra / Nafarroako Unibertsitate Publikoa
This study analyses and presents a new ramp-rate control algorithm for smoothing PV power fluctuations, designed to address three fundamental objectives: to reduce battery cycling, to meet minimum storage requirements and to be able to operate, without ramp-rate violations, with real publicly-available forecasting. The algorithm was compared to three benchmark methods and, as a performance limit, also to a hypothetical perfect prediction. Different performance variables were analyzed for all the strategies within a restricted ramp-rate constraint (2%/min): minimum storage requirement, battery power distributions, throughput energy, state of charge (SOC) distributions, degradation (calendar and cycling), expected battery lifespan and levelized cost of energy (LCOE). The proposal proves to be the most cost-effective smoothing technique and the simulation results show that its performance is comparable to the obtained with the use of an assumed perfect prediction.
Open Access
Maximum expected ramp rates using cloud speed sensor measurements
(American Institute of Physics, 2020) Wang, Guang Chao; Kurtz, Ben; Bosch, Juan Luis; Parra Laita, Íñigo de la; Kleissl, Jan; Ingeniaritza Elektrikoa, Elektronikoaren eta Telekomunikazio Ingeniaritzaren; Institute of Smart Cities - ISC; Ingeniería Eléctrica, Electrónica y de Comunicación
Large ramps and ramp rates in photovoltaic (PV) power output are of concern and sometimes even explicitly restricted by grid operators. Battery energy storage systems can smooth the power output and maintain ramp rates within permissible limits. To enable PV plant and energy storage system design and planning, a method to estimate the largest expected ramps for a given location is proposed. Because clouds are the dominant source of PV power output variability, an analytical relationship between the worst expected ramp rate, cloud motion vector, and the geometrical layout of the PV plant is developed. The ability of the proposed method to bracket actual ramp rates is assessed over 10 months under different meteorological conditions, demonstrating an average compliance rate of 98.9% for a 2 min evaluation time window. The largest observed ramp of 29.7% s(-1)is contained with the worst case estimate of 34.3% s(-1). This method provides a convenient yet economical approach to worst-case PV ramp rate modeling and is compatible with solar irradiance measured at coarse temporal resolution.
Open Access
Worst expected ramp rates from cloud speed measurements
(IEEE, 2019) Wang, Guang Chao; Bosch, Juan Luis; Kurtz, Ben; Parra Laita, Íñigo de la; Wu, Elynn; Institute of Smart Cities - ISC
Large PV power ramp rates are of concern and sometimes even explicitly restricted by grid operators. Battery energy storage systems can smooth the power output and maintain ramp rates within permissible limits. To enable PV plant and energy storage systems design and planning, a method to estimate the largest expected ramps for a given location is proposed. Because clouds are the dominant source of PV power output variability, an analytical relationship between the worst expected ramp rates, cloud motion vectors, and the geometrical layout of the PV plant is developed. The ability of the proposed method to bracket actual ramp rates is assessed over 8 months under different meteorological conditions, demonstrating an average compliance rate of 96.9% for a 2 min evaluation time window.
Open Access
Outdoor performance of a CdTe based PV generator during 5 years of operation
(IEEE, 2022) Guerra Menjívar, Moisés Roberto; Parra Laita, Íñigo de la; Marcos Álvarez, Javier; García Solano, Miguel; Marroyo Palomo, Luis; Ingeniería Eléctrica, Electrónica y de Comunicación; Institute of Smart Cities - ISC; Ingeniaritza Elektrikoa, Elektronikoaren eta Telekomunikazio Ingeniaritzaren
Together with the huge growth of the traditional crystalline silicon (Si-x) PV manufacturers, other thin-film solar cells have also emerged such as cadmium telluride (CdTe) manufacturers. They are characterized by the fact that they were created to reduce costs and by the scarcity of silicon, from which the rest of the modules are made. Despite they need more space to generate the same amount of energy as crystalline modules, their price is supposed to be much lower, and argue that they have a better performance at high temperatures. However, real comparisons between the outdoor performance of CdTe and Si-x modules have been scarcely addressed in the literature. This paper provides a comparison under real operating conditions of a CdTe photovoltaic generator versus a conventional silicon generator during 5 years of operation in a mid-latitude area, identifying the causes of the differences observed.
Open Access
Control strategies to smooth short-term power fluctuations in large photovoltaic plants using battery storage systems
(MDPI, 2014) Marcos Álvarez, Javier; Parra Laita, Íñigo de la; García Solano, Miguel; Marroyo Palomo, Luis; Ingeniería Eléctrica y Electrónica; Ingeniaritza Elektrikoa eta Elektronikoa
The variations in irradiance produced by changes in cloud cover can cause rapid fluctuations in the power generated by large photovoltaic (PV) plants. As the PV power share in the grid increases, such fluctuations may adversely affect power quality and reliability. Thus, energy storage systems (ESS) are necessary in order to smooth power fluctuations below the maximum allowable. This article first proposes a new control strategy (step-control), to improve the results in relation to two state-of-the-art strategies, ramp-rate control and moving average. It also presents a method to quantify the storage capacity requirements according to the three different smoothing strategies and for different PV plant sizes. Finally, simulations shows that, although the moving-average (MA) strategy requires the smallest capacity, it presents more losses (2–3 times more) and produces a much higher number of cycles over the ESS (around 10 times more), making it unsuitable with storage technologies as lithium-ion. The step-control shown as a better option in scenery with exigent ramp restrictions (around 2%/min) and distributed generation against the ramp-rate control in all ESS key aspects: 20% less of capacity, up to 30% less of losses and a 40% less of ageing. All the simulations were based on real PV production data, taken every 5 s in the course of one year (2012) from a number of systems with power outputs ranging from 550 kW to 40 MW.
Open Access
The potential of forecasting in reducing the LCOE in PV plants under ramp-rate restrictions
(Elsevier, 2019) Cirés Buey, Eulalia; Marcos Álvarez, Javier; Parra Laita, Íñigo de la; García Solano, Miguel; Marroyo Palomo, Luis; Ingeniería Eléctrica, Electrónica y de Comunicación; Institute of Smart Cities - ISC; Ingeniaritza Elektrikoa, Elektronikoaren eta Telekomunikazio Ingeniaritzaren
An increasing number of grid codes are requiring the limitation of the PV output power fluctuation over a given time scale. Batteries represent the most obvious solution to smooth power fluctuations, with the corresponding negative impact on the PV energy cost. However, short-term forecasting is currently being proposed as a tool to reduce battery capacity requirements or even completely remove it. Although these solutions decrease or avoid the battery cost, it also entails some energy curtailment losses which obviously raise the final cost of PV energy. This energy losses, currently unknown, are independent of the forecasting accuracy and represent the minimal additional cost in the hypothetical case of a perfect prediction. Thus, this paper compares Levelized Cost of Energy (LCOE) of three ramp-rate control strategies in order to determine which would give the lowest cost: battery-based, ideal short-term forecasting, or a combination of both. Results show that curtailment losses would be small enough to make battery-less strategy an appropriate choice, so it is worthwhile improving short-term forecasting in view of the potential LCOE savings. Database is taken from high resolution measurements recorded for over a year at 8 PV plants ranging from 1 to 46 MWp.
Open Access
Control method to coordinate inverters and batteries for power ramp-rate control in large PV plants: minimizing energy losses and battery charging stress
(Elsevier, 2023) González Moreno, Alejandro; Marcos Álvarez, Javier; Parra Laita, Íñigo de la; Marroyo Palomo, Luis; Ingeniería Eléctrica, Electrónica y de Comunicación; Institute of Smart Cities - ISC; Ingeniaritza Elektrikoa, Elektronikoaren eta Telekomunikazio Ingeniaritzaren; Universidad Pública de Navarra / Nafarroako Unibertsitate Publikoa
This work presents a novel control method for multi-megawatt photovoltaic (PV) plants that is able to regulate each plant inverter and the battery system to mitigate PV power fluctuations. The proposed control method makes it possible to implement different PV ramp-rate control strategies based on the use of batteries and the limitation of inverters during positive fluctuations, which have been conceptually proposed in the specialized bibliography, but have omitted how to perform the coordination between PV generators. The dynamic model and the tuning of the control parameters are presented and the method is used to correctly implement different inverter-limitation strategies using 5-second data from a real 45 MWp PV plant. Furthermore, a new control strategy is proposed. This strategy reduces curtailment losses to negligible values and takes into account and addresses the intrinsic asymmetry in the battery charging and discharging capability, an issue that has been overlooked in the specialized bibliography. The results show that the proposed control method can effectively control each of the multiple inverters in order to obtain the desired PV plant operation to regulate the battery charging power, even during highly fluctuating scenarios.
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.
Open Access
Role of student associations in the acquisition of competences in university engineering programs
(IEEE, 2023) Samanes Pascual, Javier; Parra Laita, Íñigo de la; Berrueta Irigoyen, Alberto; Rosado Galparsoro, Leyre; Soto Cabria, Adrián; Elizondo Martínez, David; Catalán Ros, Leyre; Sanchis Gúrpide, Pablo; Institute of Smart Cities - ISC
Students in the STEM field (Science, Technology, Engineering and Mathematics), do not only require deep technical knowledge, but a complete set of global skills related to management, teamwork, lifelong learning, personal development, communications skills or proactiveness, abilities often referred as soft-skills. Student-led organizations, and specifically, university student associations, are one of the best alternatives to promote the acquisition of soft-skills in STEM high education fields. These skills are competences already included in official university programs that can hardly be addressed or acquired from traditional university education. This article studies how student enrollment in student led organizations (SLOs), with an active participation on their organization and activities, allows engineering students to achieve a better development of these soft skills. As case study, a medium size university, with 9000-students and eleven SLOs, six of them focused on STEM related fields, is used in this paper. A survey is conducted among the university community to identify their degree of participation in SLOs, and to test whether participation in these initiatives increases students' self-perception of their soft skill acquisition during their university studies. This survey shows how students of engineering programs, with a high degree of involvement in SLOs, demonstrated greater confidence in their soft skills at the end of their university years.
Open Access
A tool for the performance evaluation and failure detection of Amareleja PV plant (Acciona) from SCADA
(2015) Muñoz Escribano, Mikel; Parra Laita, Íñigo de la; García Solano, Miguel; Marcos Álvarez, Javier; Pérez, Miguel; Ingeniaritza Elektrikoa eta Elektronikoa; Institute of Smart Cities - ISC; Ingeniería Eléctrica y Electrónica
This paper describes a tool developed for the performance evaluation and failure detection in a 45.6 MWp PV plant installed by the company Acciona in Amareleja (Portugal). The paper describes the PV plant configuration and its SCADA (Supervisory Control And Data Acquisition), the measured variables and the main functionalities of the software. Some of these functionalities are the automatic and accurate PSTC (Power under standard test conditions1) calculation for each generator and for the whole PV Plant, the reference production that would be delivered by the PV plant assuming a 100% availability, the hierarchy of SCADA alarms, the detection of long-term trends and degradation in PV generators, possible hidden problems in the different equipment and systems composing the PV plant, etc. This tool entered into operation in 2011 and is working properly since then.