In this work, we show the optimization of the dailyarbitrage operation of a PV-battery power generating system. Genetic algorithms (GA) metaheuristic technique is used for the optimization. A new arbitrage method is applied. An integer variable which can take one of three values (-1, 0 or 1) for each hour of the day decides the operation of the battery (charge/inactive/discharge), considering as inputs the average hourly irradiance, temperature and electricity price forecast for the day-ahead, and the state of charge (SOC) at the first hour of the day-ahead. The optimal arbitrage operation obtains the maximum net incomes, that is, incomes of selling electricity minus cost of purchasing electricity and degradation cost of the battery. The method is applied to a PV-battery power generating system near Zaragoza (Spain) for a specific day, obtaining net incomes 7% higher than using a previously published optimization method. Key words: Grid-connected PV-battery system, arbitrage, daily operation, control strategy, optimization, genetic algorithms.

In this work, we study the stable generation of hydrogen by means of the electrolyzer fed by renewable sources, battery and grid. Due to the intermittent nature of the renewable sources (PV, wind), the hydrogen generation by the electrolyzer cannot be stable during the time except if there is another electricity source to fulfil the difference between the electrolyzer nominal power and the renewable power. The AC electrical grid will supply that difference during hours when the electricity price is low, while the batteries will supply the difference when the electricity price is high. Also, batteries will be charged by the grid when electricity price is low. We compare the performance and economical results with the case of using only the grid for supplying that difference. Considering a hypothetical electricity hourly price with 3% annual inflation, the system with battery has a levelized cost of hydrogen (LCOH) of 4.25 €/kg with the actual present battery CAPEX (200 €/kWh) while it has a LCOH of 3.95 €/kg if we consider a much lower future battery CAPEX of 20 €/kWh (10 times lower than nowadays). The system without battery has a LCOH of 4.14 €/kg. Key words. Electrolyzer, hydrogen, renewable, wind, off-grid, daily operation, control strategy, optimization, genetic algorithms.

The project “Profitable small-scale renewable energy systems in agrifood industry and rural areas: demonstration in the wine sector (LIFE REWIND)” is partly funded by a €676,265 grant from the European Union’s LIFE+ program. This project addresses climate change in regard to the rural environment with objectives in both mitigation and adaptation. In terms of mitigation, it seeks to decrease the CO2 emissions resulting from energy consumption in rural areas. In terms of adaptation, the project facilitates the acclimation of agriculture to climate change by allowing the production of clean energy for irrigation in locations without an electric grid. The project provides other positive outcomes by omitting noise, waste and other undesirable environmental effects. It also reduces visual impacts by avoiding the construction of electrical grids. The demonstration takes place in the wine sector, where two different environments are considered: field and winery. In each one a prototype is installed that produces on-site renewable energy through photovoltaic generation.

In this work, the short term (daily) operation of an off-grid hybrid PV-diesel-battery system is optimized by genetic algorithms. An integer variable (0, 1 or 2) for each hour of the day decides the way the battery works. With the forecast of the hourly irradiation, temperature and load consumption for the next day, and estimating the state of charge of the battery (SOC) at the first hour of the day, we perform the optimization of the integer variables for the 24 hours of next day. To avoid inadmissible computation time, the optimization is performed by using genetic algorithms (GA) obtaining in roughly 1 hour the optimal solution or a solution near the optimal one. The optimization tries to obtain the minimal total cost of the daily operation while supplying the whole load. We compare the results of the optimization with the typical control strategies (load following, cycle charging and set point strategies), obtaining better results with the new optimized strategy. The reduction in the operational cost obtained varies from 2.5% to 62%, compared to the typical control strategies (load following or cycle charging). Key words. PV-diesel-battery systems, off-grid, daily operation, control strategy, optimization, genetic algorithms.

A global energy transition is crucial to combat climate change, involving a shift from fossil fuels to renewable sources and low-emission technologies. Solar photovoltaic technology has grown exponentially in the last decade, establishing itself as a cost-effective and sustainable option for electricity generation. However, its large-scale integration faces challenges due to its intermittency and lack of dispatchability. This study evaluates, from an energy perspective, the case of hybrid photovoltaic (PV) plants with battery storage systems. It addresses an aspect little explored in the literature: the sizing of battery storage to maintain a steady and constant 24 h power supply, which is usually avoided due to its high cost. Although the current economic feasibility is limited, the rapidly falling price of lithium batteries suggests that this solution could be viable in the near future. Using Matlab simulations, the system’s ability to deliver a constant energy production of electricity is assessed. Energy indicators are used to identify the optimal system size under different scenarios and power setpoints. The results determine the optimal storage size to supply a constant power that covers all or a large part of the daily PV generation, achieving steady and reliable electricity production. In addition, the impact of using setpoints at different time horizons is assessed. This approach has the potential to redefine the perception of solar PV, making it a dispatchable energy source, improving its integration into the electricity grid, and supporting the transition to more sustainable and resilient energy systems.

The variability of solar radiation presents significant challenges for the integration of solar photovoltaic (PV) energy into the electrical system. Incorporating battery storage technologies ensures energy reliability and promotes sustainable growth. In this work, an energy analysis is carried out to determine the installation size and the operating setpoint with optimal constant monthly power through an iterative calculation process, considering various operating setpoints and system parameters. A degradation model is integrated according to the curves offered by battery manufacturers and the charge–discharge cycles are calculated using the rainflow method to guarantee a reliable analysis of the plant. Through massive data analysis in a long-term simulation, indicators are generated that allow for establishing a relationship between the energy unavailability of the system and the BESS dimensions.

In this paper, a new coordinated maximum power point tracking (MPPT) algorithm has been developed for a grid-tied PV system, whose inverter follows a VDCIQ control scheme. The control objectives of this system are shared between 2 converters: a DC boost converter which performs MPPT of the PV plant, and an inverter which is responsible for DC voltage setpoint control, specific reactive current injection under request and reduced harmonic content of AC grid currents. The proposed algorithm operates upon a proper switching amongst conventional MPPT algorithms, namely perturb and observe (P&O) and incremental conductance (IC) algorithms, to take advantage of the best characteristics of each MPPT method with a different step size and considering the influence of the inverter control constants. Two coordination schemes are proposed for this algorithm to prioritise the improvement of different performance aspects over others. The impact of the proposed algorithm according to the 2 coordination schemes is evaluated and compared with the impact of conventional MPPT algorithms according to the trackability of power, the impact on DC voltage and on the AC grid side. The results are analysed by simulations conducted in MATLAB-Simulink.

Photovoltaic generation is one of the key technologies in the production of electricity from renewable sources. However, the intermittent nature of solar radiation poses a challenge to effectively integrate this renewable resource into the electrical power system. The price reduction of battery storage systems in the coming years presents an opportunity for their practical combination with utility-scale photovoltaic plants. The integration of properly sized photovoltaic and battery energy storage systems (PV-BESS) for the delivery of constant power not only guarantees high energy availability, but also enables a possible increase in the number of PV installations and the PV penetration. A massive data analysis with long-term simulations is carried out and indicators of energy unavailability of the combined system are identified to assess the reliability of power production. The proposed indicators allow to determine the appropriate sizing of the battery energy storage system for a utility-scale photovoltaic plant in a planning stage, as well as suggest the recommended operating points made for each month through a set of graphs and indicators. The presence of an inflection zone has been observed, beyond which any increase in storage does not generate significant reductions in the unavailability of energy. This critical zone is considered the sweet spot for the size of the storage, beyond which it is not sensible to increase its size. Identifying the critical point is crucial to determining the optimal storage size. The system is capable of providing reliable supply of constant power in monthly periods while ensuring capacity credit levels above 95%, which increases the penetration of this renewable resource. Despite the fact that the study focuses exclusively on the analysis from an energy perspective, it is important to consider the constraints associated to real storage systems and limit their oversizing.

This is the second part of a study on Power Quality (PQ) analysis of Wind Turbines (WT) installed in wind farms.A specifically designed measurement system has been installed in three wind farms with three different types of asynchronous generators of 600 kW and 700 kW classes.This part is focused on the analysis of transient events, connections and disconnections and power fluctuations.A new method to study power fluctuations based in joint timefrequency analysis is proposed.Transient events such as connection of capacitor banks are studied with the waveforms.The firing of thyristors during soft start is also studied through waveforms.The whole evolution during the connection of the generator is analyzed through the RMS value of each cycle of the grid because it is a longer transient.Power fluctuations are also studied through values of current and power each cycle or half-cycle.

This paper presents a simplified model to represent a wind farm in a power flow study.This model has been developed taking into account the variability in the generated power from windmills and its normal operation.Its main advantages are its simplicity and the possibility of calculating the voltage in the park's network without having to run a power flow study.Another advantage of the proposed method is that it is based in the fourth-pole theory, widely used in electrical engineering.Finally, the uncertainty of the model is assessed.Up to now, distributed generation in Spain must inject power with unity power factor.But directive is going to change and some feasible regulations for reactive power are studied, attending specially to voltages across the grid.One possible application of this model is to study the management of reactive power in wind farms.Other possible application is to study the influence of nearby wind farms.

In this paper, we use MHOGA software for the optimization of an AC-coupled utility-scale PV-plus-battery system. Batteries are used for price arbitrage, being charged with the photovoltaic (PV) generation during hours of low electricity price and discharged during hours of high price. The correct estimation of the battery lifetime has great importance in the calculation of the net present value, to do this advanced models for estimating the Li-ion battery lifetime (considering cycle and calendar ageing) are used. With present components costs, considering the Spanish SPOT price of 2021 with an expected increase of 1% annual, the AC coupled utility-scale PV-plusbattery isn’t economically viable comparing to the PV-only system. If electricity hourly price was multiplied by two, in certain cases adding battery to the PV system would be profitable.

This paper studies the effect of a number of close wind farms, where there is a relationship among the farms.First of all, data are statistically analysed to check main relationships between farms.The second analysis goes further in the characterisation of wind farm relationships.Artificial Neural Networks (ANN) provide a powerful tool to classify data automatically.They are very useful in finding patterns of productions of a zone.The patterns are obtained only with data of the power of wind farms through competitive neural networks and selforganizing feature maps (SOFM).Time variations of wind farm output have been studied in the third analysis.Only hourly data is available, so only slow variations can be analysed (such as down and dusk variations).Two tools have been used in the time study: correlogram and spectrogram of each wind farm.In addition to this, those patterns found by ANN have been compared in the forth analysis with meteorological data of a nearby station.

In this paper, we use MHOGA software for the evaluation of a hydrogen generation system powered by wind turbines. We study the state of the art of the electrolyzers, obtaining the most important characteristics and costs of PEM electrolyzers. The optimization of a Wind-H2 system is performed, obtaining the best combination of components (wind turbines and electrolyzer) and control strategy for the hydrogen production. We will compare to the Wind-only system (wind farm which injects all the electricity produced to the gird). Two cases have been evaluated regarding the electricity price: Spanish SPOT price of 2019 and of 2021, with an expected increase of 1% annual. The Wind-H2 system can be competitive to the Wind-only system if the hydrogen sale price is 4.8 €/kg for the case of 2019 SPOT prices and 6.7 €/kg for the case of 2021 SPOT prices, considering 1% annual increase in the SPOT prices and 2% for the hydrogen price.

This paper describes a technical-economical analysis to achieve the most appropriate sizing of grid-connected photovoltaic systems for water pumping in irrigation communities. The profitability of different tracking systems are analysed based on the price of the electrical energy consumed from the network. The case study of a real pumping system of an irrigation community located in Zaragoza (Spain) is presented, which supplies a geographical area of 2000 Ha, with six 630kW pumps and eight 110kW units.

In this paper, we use MHOGA software for the evaluation of adding pumped hydro storage (PHS) for energy arbitrage in utility-scale PV generating systems. PHS is used for electricity price arbitrage, pumping water from the lower reservoir to the upper reservoir with the PV generation during hours of low electricity price and generating electricity by means of the stored water with the turbine during hours of high price (during these hours the PV generator also injects its production to the grid). The control strategy creates setpoints for the use of the pump and the turbine, trying to obtain the maximum benefits from the electricity sold to the grid, maximizing the net present value (NPV). An example of application is shown, obtaining conclusions about the economical viability of the PV-PHS system compared to the PV-only system: in the case studied in this work, it is not worth to add PHS to the PV system.

The electrical generation of photovoltaic systems is variable and non-dispatchable. Energy storage systems can provide the system with energy management capabilities. In particular, with a hybrid system that combines a photovoltaic system and an energy storage system, it is possible to deliver firm power to the grid, if it is correctly dimensioned and operated. The objective of this work is to study the most appropriate relationship between the capacity of the battery energy storage system (BESS) and the peak power of the photovoltaic generator that enables the delivery of constant power throughout the year. Analysis parameters are presented that help to decide the most convenient energy injection constant value (PV-CPG set point) and the size of the storage system. As a case study, the most suitable battery capacity for a 1 MWp photovoltaic system with a battery located in Zaragoza (Spain), and the most convenient annual setpoint values for its operation are analyzed.

The aim of this work is to validate a theoretical model with actual data from an installation of photovoltaic thermal PVT-glazed collectors in a tertiary sector building, a four-star hotel located in Tenerife (Spain).The paper describes the main technical elements of the hybrid solar installation, explains the methodology followed in the validation process and details how the calculations were performed to obtain the successful results. The acquired numbers have been examined qualitatively and quantitatively throughout the manuscript.The main novelty of this analysis is that the theoretical calculations made by Abora software are compared with experimental data, i.e. the thermal energy and the electricity production, measured in situ at the installation.The overall energy performance (thermal and photovoltaic) proves to be 22.0 % lower than the one estimated by Abora software. Nevertheless, if shading and distribution losses are considered, this value would only be 9.1 % below what was simulated a priori . The results obtained in this validation provide an estimate of the avoided emissions.In the medium term, one of the most attractive objectives of this study would be the possibility to use this software for prediction of collected data, including the uncertainty with which they are provided.

Electrical power systems have begun a transition process towards a new paradigm characterized by decarbonization, decentralization of generation, electrification of the economy, more active participation of consumers and sustainable use of resources. Current networks must be redesigned to become more effective and robust networks, so that they can support future needs, following the criteria that determine what has been called Smart Grids. Elements based on power electronics play a relevant role in these smart power networks. The aim of this paper is to show the functionalities of power electronics in the electrical power systems, in the context of the teaching of the subject of Smart Grids in the Electrical Engineering degree and Industrial Technologies degree at the University of Zaragoza.

A facility based on a photovoltaic and thermal hybrid solar field with a seasonal storage tank coupled to a water-to-water heat pump is presented in this paper as an adequate energy supply system for a building of social homes in Zaragoza (Spain), currently under construction. Two types of complementary software have been used for the complete design, sizing, and simulation of the system. DesignBuilder was used to determine the hourly demands from the construction drawings, and TRNSYS was then implemented to dynamically simulate the whole energy system. System performance has been tested in terms of 3E aspects (energy, environmental and economic) with a few well-known key performance indicators. Results obtained by the combined use of the demand simulation software and quantification with different indicators (KPI) show that the proposed solution is suitable for this building: the calculated coverage of the domestic hot water demand is about 80%, the payback period is 8.5 years, and the installation could avoid 44,200 kgCO2/year of global warming potential. To sum up, this paper shows how this novel, high-efficiency heating system is a good solution for social housing, owing to its low energy costs and a possible subsidization of a fraction of the high initial investment.

The implementation of photovoltaic systems is increasingly high in electrical power systems. The electrical generation of PV systems is variable and non-dispatchable, which creates challenges in its integration into power systems. For technical and economic reasons, it would be very convenient to provide firmness to photovoltaic generation. Battery energy storage systems (BESS) can offer such firm capacity, giving the system management capabilities for the photovoltaic energy generated.The objective of this work is to study the most appropriate relationship between the capacity of the storage system and the peak power of the photovoltaic generator that allows the delivery of a firm power throughout the year. Analysis parameters are presented that allow deciding the most convenient constant photovoltaic power generation value (PV-CPG setpoint) and the size of the storage system, as well as studying management strategies to reduce its deviation from the setpoint. As a case study, the evolution of the parameters in a 1MWp photovoltaic system located in Zaragoza, (Spain) with battery is analyzed.