Search Results (46)

Building Integrated Photovoltaic (BIPV) systems have emerged as an option to design Net Zero Energy Buildings (NZEB), thus helping to meet sustainable development goals. Based on an exhaustive review of papers, this work identifies characteristics and solutions to address power management issues in BIPV systems through three key approaches: (1) configurations of photovoltaic arrays, (2) MPPT methods, and (3) granularity level of the MPPT action. The analysis also highlights the advantages of deploying DC buses alongside conventional AC infrastructure to reduce conversion losses. This work also provides information concerning the trends in design and performance of BIPV systems, which is useful as a background for researchers and designers. In addition, the cross-coupling phenomena occurring in distributed MPPT solutions for BIPV systems is explained and evaluated in order to propose a mitigation strategy. These findings offer practical guidelines for developing more efficient BIPV systems that effectively support the transition to sustainable buildings and cities. Full article

The introduction of renewable energy sources in microgrids increases energy reliability, especially in small communities that operate disconnected from the main power grid. A battery energy storage system (BESS) plays an important role in microgrids because it helps mitigate the problems caused by the variability of renewable energy sources, such as unattended demand and voltage instability. However, a BESS increases the cost of a microgrid due to the initial investment and maintenance, requiring a cost–benefit analysis to determine its size for each application. This paper addresses this problem by formulating a method that combines economic and technical approaches to provide favorable relations between costs and performances. Mixed integer linear programming (MILP) is used as optimization algorithm to size BESS, which is applied to an isolated community in Colombia located at Isla Múcura. The results indicate that the optimal BESS requires a maximum power of 17.6 kW and a capacity of 76.61 kWh, which is significantly smaller than the existing 480 kWh system. Thus, a reduction of 83.33% in the number of batteries is obtained. This optimized size reduces operational costs while maintaining technical reliability. The proposed method aims to solve an important problem concerning state policy and the universalization of electrical services, providing more opportunities to decision makers in minimizing the costs and efforts in the implementation of energy storage systems for isolated microgrids. Full article

Hybrid energy storage systems (HESSs) are essential for adopting sustainable energy sources. HESSs combine complementary storage technologies, such as batteries and supercapacitors, to optimize efficiency, grid stability, and demand management. This work proposes a semi-active HESS formed by a battery connected to the DC bus and a supercapacitor managed by a Sepic/Zeta converter, which has the aim of avoiding high-frequency variations in the battery current on any operation condition. The converter control structure is formed by an LQG controller, an optimal state observer, and an adaptive strategy to ensure the correct controller operation in any condition: step-up, step-down, and unitary gain. This adaptive LQG controller consists of two control loops, an internal current loop and an external voltage loop, which use only two sensors. Compared with classical PI and LQG controllers, the adaptive LQG solution exhibits a better performance in all operation modes, up to 68% better than the LQG controller and up to 84% better than the PI controller. Therefore, the control strategy proposed for this HESS provides a fast-tracking of DC-bus current, driving the high-frequency component to the supercapacitor and the low-frequency component to the battery. Thus, fast changes in the battery power are avoided, reducing the degradation. Finally, the system adaptability to changes up to 67% in the operation range are experimentally tested, and the implementation of the control system using commercial hardware is verified. Full article

Hybrid energy storage systems significantly impact the renewable energy sector due to their role in enhancing grid stability and managing its variability. However, implementing these systems requires advanced control strategies to ensure correct operation. This paper presents an algorithm for designing the power and control stages of a hybrid energy storage system formed by a battery, a supercapacitor, and a bidirectional Zeta converter. The control stage involves an adaptive sliding-mode controller co-designed with the power circuit parameters. The design algorithm ensures battery protection against high-frequency transients that reduce lifespan, and provides compatibility with low-cost microcontrollers. Moreover, the continuous output current of the Zeta converter does not introduce current harmonics to the battery, the microgrid, or the load. The proposed solution is validated through an application example using PSIM electrical simulation software (version 2024.0), demonstrating superior performance in comparison with a classical cascade PI structure. Full article

Dynamic reconfiguration, the monitoring of power production, and the fault diagnosis of photovoltaic arrays, among other applications, require fast and accurate models of photovoltaic arrays. In the literature, some models use the Lambert-W function to represent each module of the array, which increases the calculation time. Other models that use implicit equations to avoid the Lambert-W function do not use the inflection voltages to simplify the system of nonlinear equations that represent the array, increasing the computational burden. Therefore, this paper proposes mathematical models for series-parallel (SP) and total-cross-tied (TCT) photovoltaic arrays based on the implicit equations of the single-diode model and the inflection points of the current–voltage curves. These models decrease the calculation time by reducing the complexity of the nonlinear equation systems that represent each string of SP arrays and the whole TCT. Consequently, the calculation process that solves the model speeds up in comparison with processes that solve traditional explicit models based on the Lambert-W function. The results of several simulation scenarios using the proposed SP model with different array sizes show a reduction in the computation time by $82.97\%$ in contrast with the traditional solution. Additionally, when the proposed TCT model for arrays larger than $2\times 2$ is used, the reduction in the computation time is between $47.71\%$ and $92.28\%$. In dynamic reconfiguration, the results demonstrate that the proposed SP model provides the same optimal configuration but 7 times faster than traditional solutions, and the TCT model is solved at least 4 times faster than classical solutions. Full article

The growing use of DC/DC power converters has resulted in the requirement that their complex controllers be cheaper and smaller, thus using cost-effective implementations. For this purpose, it is necessary to decrease the computational burden in controller implementation to minimize the hardware requirements. This manuscript presents two methods for tuning an adaptive linear–quadratic–Gaussian voltage controller for a battery charger/discharger, implemented with a Sepic/Zeta converter, to work at any operating point. The first method is based on a lookup table to select, using the nearest method, both the state feedback vector and the observer gain vector, solving the Riccati’s differential equation offline for each practical operating point. The second method defines a polynomial function for each controller element that is based on the previous data corresponding to the system operating points. The adaptability of the two controllers to fixed voltage regulation and reference tracking was validated using simulations and experimental tests. The overshoot and settling time results were lower than 11% and 3.7 ms, which are in the same orders of magnitude of a control approach in which the equations are solved online. Likewise, three indices were evaluated: central processing unit capacity, cost, and performance. This evaluation confirms that the controller based on polynomial interpolation is the best option of the two examined methods due to the satisfactory balance between dynamic performance and cost. Despite the advantages of the controllers in being based on a lookup table and polynomial interpolation, the adaptive linear–quadratic–Gaussian has the benefit of not requiring an offline training campaign; however, the cost saving obtained with the lookup table controllers and polynomial interpolation controllers, due to the possible implementation on small-size microcontrollers with development tool simple and easy maintenance, will surely be desirable for a large number of deployed units, ensuring that those solutions are highly cost-effective. Full article

Low-voltage photovoltaic systems are being widely used around the world, including their introduction into the power grid. The development of these systems requires the adaptation of several power converters, their static and dynamic modeling, the design of passive elements, and the design of the controller parameters, among other actions. Today, power converters are key elements in the development of photovoltaic systems, and classical power converters such as buck converters produce discontinuous input and output currents, requiring a high input capacitance and impacting the output power quality of these systems. This paper presents a proposal for a low-voltage photovoltaic system that uses a continuous input/output current buck converter, which enhances the operation of the classical buck converter in photovoltaic systems. The methodology describes the proposed photovoltaic system, including the power converter, its detailed operation, and the analysis of its waveforms. Moreover, the methodology includes a mathematical model of the photovoltaic system’s dynamic behavior and the design of a sliding-mode controller for maximum power extraction and perturbation rejection. The photovoltaic system is validated in two ways: first, a comparison with the classical buck converter highlighting the advantages of continuous input/output currents is presented; then, an application example using commercial devices is described in detail. The application example uses a flowchart to design the power converter and the sliding-mode controller, and a circuit simulation confirms the advantages of the continuous input/output current buck converter with its controller. In the circuit simulation, the control strategy is formed by a perturb and observe algorithm that generates the voltage reference for the sliding-mode controller, which guarantees the system stability, tracks the maximum power point, and rejects the double-frequency oscillations generated by an intended microinverter. Full article

In a DC microgrid that involves a battery storage system, the primary energy management is performed by a battery charger/discharger based on a dc/dc power converter. Moreover, the battery charger/discharger is also used to regulate the voltage of the dc bus. One of the challenges at the control level is to regulate the DC bus voltage under battery charge and discharge conditions but also under different relations between the battery and bus voltages. For this reason, this paper proposes a battery charger/discharger based on the Sepic/Zeta converter and an adaptive controller, which provides bidirectional current flow, stable bus voltage, and satisfactory electrical characteristics. The main advantage of the proposed control system is the capability to adapt the controller parameters to any operation condition, which provides a general solution to interface any battery to any bus voltage. This study is focused on the design procedure of both the power converter and the controller, where a detailed mathematical analysis is performed to ensure the system performance and stability. Finally, the proposed solution is validated using an experimental prototype and a practical application case. Full article

Power generation using small wind turbines connected to AC grids has been gaining attention and contributions in recent years. As small wind turbines are connected to remote areas as support energy systems, there are not extensive contributions connecting those small turbines to AC grids. This paper presents the integration of a small wind generation system which is AC-grid-connected. The system is composed of a 160 W commercial small wind turbine with a permanent magnet synchronous generator and a 140 W Texas Instruments (Dallas, TX, USA) development kit devoted to connecting photovoltaic panels to AC grids. Several experimental tests were developed to characterize the devices, e.g., to obtain the power–current curves of the synchronous generator. Moreover, a mathematical model of the flyback converter is developed in detail in order to design a new converter controller. All the control capacity of the development kit is used to extract the maximum power of the synchronous generator, to reject the oscillation produced by the inverter and to connect the system to the AC grid. Experimental results show that is possible to integrate these devices to provide energy to power systems with some achievable adaptations. Full article

Due to the need to include renewable energy resources in electrical grids as well as the development and high implementation of PV generation and DC grids worldwide, it is necessary to propose effective optimization methodologies that guarantee that PV generators are located and sized on the DC electrical network. This will reduce the operation costs and cover the investment and maintenance cost related to the new technologies (PV distributed generators), thus satisfying all technical and operative constraints of the distribution grid. It is important to propose solution methodologies that require short processing times, with the aim of exploring a large number of scenarios while planning energy projects that are to be presented in public and private contracts, as well as offering solutions to technical problems of electrical distribution companies within short periods of time. Based on these needs, this paper proposes the implementation of a Discrete–Continuous Parallel version of the Particle Swarm Optimization algorithm (DCPPSO) to solve the problem regarding the integration of photovoltaic (PV) distributed generators (DGs) in Direct Current (DC) grids, with the purpose of reducing the annual costs related to energy purchasing as well as the investment and maintenance cost associated with PV sources in a scenario of variable power demand and generation. In order to evaluate the effectiveness, repeatability, and robustness of the proposed methodology, four comparison methods were employed, i.e., a commercial software and three discrete–continuous methodologies, as well as two test systems of 33 and 69 buses. In analyzing the results obtained in terms of solution quality, it was possible to identify that the DCPPSO proposed obtained the best performance in relation to the comparison methods used, with excellent results in relation to the processing times and standard deviation. The main contribution of the proposed methodology is the implementation of a discrete–continuous codification with a parallel processing tool for the evaluation of the fitness function. The results obtained and the reports in the literature for alternating current networks demonstrate that the DCPPSO is the optimization methodology with the best performance in solving the problem of the optimal integration of PV sources in economic terms and for any kind of electrical system and size. Full article

The problem of optimally integrating PV DGs into electrical networks to reduce annual costs (which include energy purchase and investment costs) was addressed in this research by presenting a new solution methodology. For such purpose, we used a Discrete–Continuous Parallel Particle Swarm Optimization method (DCPPSO), which considers both the discrete and continuous variables associated with the location and sizing of DGs in an electrical network and employs a parallel processing tool to reduce processing times. The optimization parameters of the proposed solution methodology were tuned using an external optimization algorithm. To validate the performance of DCPPSO, we employed the 33- and 69-bus test systems and compared it with five other solution methods: the BONMIN solver of the General Algebraic Modeling System (GAMS) and other four discrete–continuous methodologies that have been recently proposed. According to the findings, the DCPPSO produced the best results in terms of quality of the solution, processing time, and repeatability in electrical networks of any size, since it showed a better performance as the size of the electrical system increased. Full article

This paper presents a methodology used to estimate the energy generated during one year by a photovoltaic module (PVM) operating under partial shading conditions. The methodology starts by calculating the solar paths and contours of nearby objects that produce shadows. Then, a method was proposed to estimate the shading factors of each submodule. Afterwards, the solar resource data and the calculated shading factors were used to feed a detailed PVM model to calculate the power–voltage curves for each hour, which were used to obtain a power profile and estimate the energy generated by the PVM in one year. The procedure was validated through simulation and experimental results. The simulation results consider a case study available in the literature, which was simulated to evaluate the effect on the PVM energy estimation considering and disregarding the partial shading conditions. The experimental results illustrate the capacity of the proposed methodology to predict the shaded and unshaded submodules and the module power–voltage curve. The results show that the proposed method avoids the energy overestimation introduced by classical estimation methods, which affects the sizing of a photovoltaic generator. Full article

This paper presents a photovoltaic (PV) system designed to reduce the DC-link capacitance present in double-stage PV microinverters without increasing the capacitor interfacing the PV source. This solution is based on a modified boost topology, which exhibits continuous current in both input and output ports. Such a characteristic enables the implementation of PV microinverters without electrolytic capacitors, which improves the reliability in comparison with solutions based on classical converters with discontinuous output current and electrolytic capacitors. However, the modified boost converter exhibits different dynamic behavior in comparison with the classical boost converter; thus, design processes and controllers developed for the classical boost converter are not applicable. This paper also introduces a sliding-mode controller designed to ensure the stable operation of the PV microinverter around the maximum power point. Moreover, this solution also rejects the voltage oscillations at double the grid frequency generated by the grid-connection. The global stability of the complete PV system is formally demonstrated using mathematical analyses, and a step-by-step design process for both the power stage and control system is proposed. Finally, the design process is illustrated using a representative application example, and the correct operation of the PV system is validated using realistic circuital simulations. The results validate the accuracy of the theoretical equations proposed for both the design and control of the novel PV system, where errors below 4.5% were obtained for the ripple prediction, and below 1% for the prediction of the dynamic behavior. Full article

This paper proposes a new solution methodology based on a mixed-integer conic formulation to locate and size photovoltaic (PV) generation units in AC distribution networks with a radial structure. The objective function comprises the annual expected energy costs of the conventional substation in addition to the investment and operating costs of PV sources. The original optimization model that represents this problem belongs to the family of mixed-integer nonlinear programming (MINLP); however, the complexity of the power balance constraints make it difficult to find the global optimum. In order to improve the quality of the optimization model, a mixed-integer conic (MIC) formulation is proposed in this research in order to represent the studied problem. Numerical results in two test feeders composed of 33 and 69 nodes demonstrate the effectiveness of the proposed MIC model when compared to multiple metaheuristic optimizers such as the Chu and Beasley Genetic Algorithm, the Newton Metaheuristic Algorithm, the Vortex Search Algorithm, the Gradient-Based Metaheuristic Optimization Algorithm, and the Arithmetic Optimization Algorithm, among others. The final results obtained with the MIC model show improvements greater than USD 100,000 per year of operation. All simulations were run in the MATLAB programming environment, using its own scripts for all the metaheuristic algorithms and the disciplined convex tool known as CVX with the Gurobi solver in order to solve the proposed MIC model. Full article

Energy storage systems are essential for multiple applications like renewable energy systems, electric vehicles, microgrids, among others. Those systems are responsible of regulating the dc bus voltage using charging-discharging systems which are mainly formed by a power converter and a control system. This work focuses on the control system of a flyback converter. A detailed design procedure of an adaptive sliding-mode controller (SMC) and its parameters is presented. The proposed procedure was validated through simulations which allow to confirm its good performance in terms of global stability providing the desired dynamic of the dc bus voltage regulation. Full article