S. Lyden

A Simulated Annealing Global Maximum Power Point Tracking Approach for PV Modules Under Partial Shading Conditions

This paper proposes a simulated annealing (SA)-based global maximum power point tracking (GMPPT) technique designed for photovoltaic (PV) systems which experience partial shading conditions (PSC). The proposed technique is compared with the common perturb and observe MPPT technique and the particle swarm optimization method for GMPPT. The performance is assessed by considering the time taken to converge and the number of sample cases where the technique converges to the GMPP. Simulation results indicate the improved performance of the SA-based GMPPT algorithm, with arbitrarily selected parameters, in tracking to the global maxima in a multiple module PV system which experiences PSC. Experimental validation of the technique is presented based on PV modules that experience nonuniform environmental conditions. Additionally, studies regarding the influence of the key parameters of the SA-based algorithm are described. Simulation and experimental results verify the effectiveness of the proposed GMPPT method.

Review of Maximum Power Point Tracking approaches suitable for PV systems under Partial Shading Conditions

Maximum Power Point Tracking (MPPT) is an important consideration in Photovoltaic (PV) Systems, particularly as these systems increase in size and are exposed to non-uniform environmental conditions. Conventional MPPT techniques are designed to track the Maximum Power Point under uniform conditions where there is a single maximum power. Under non-uniform environmental conditions, with bypass diodes integrated into the circuit, the Power-Voltage characteristics become more complex resulting in multiple local maxima. Under such conditions, conventional MPPT techniques cannot track the global maxima and may result in considerable energy losses. This review paper explores the approaches designed to mitigate the complexities arising from non-uniform environmental conditions in PV system operation.

Attracting girls to civil engineering through hands-on activities that reveal the communal goals and values of the profession

In this paper we report on our work to develop hands-on activities for middle school classrooms that clearly reveal how civil engineers make a substantial societal impact. These activities and their accompanying messaging vividly show how, through their work, teams of civil engineers help people around the world have better quality of life in a sustainable way. All activities are easily reproducible with low-cost materials and represent a number of specialization areas within civil engineering—namely, structural, urban and community planning, and water resources. The messaging that is an integral part of the activities uses the latest available research on why girls are underrepresented in civil engineering in particular, and the science, technology, engineering, and mathematics (STEM) fields in general, to highlight the communal goals and values that civil engineers strive for. The results presented in this paper should allow civil engineers to more clearly show how their work enacts communal and altruistic goals that are known to be generally more highly endorsed by women than by men. Preliminary results on the implementation of these strategies in the context of an all-girls middle school show promise in enabling a better connection between the civil engineering profession and female students.

Comparison of the perturb and observe and simulated annealing approaches for maximum power point tracking in a photovoltaic system under partial shading conditions

Due to the low efficiency of Photovoltaic (PV) cells, it is essential that PV systems are operated optimally to ensure that maximum power is available from the system under changing conditions. Tracking of this Maximum Power Point (MPP) becomes more complicated when multiple PV modules connected in series and parallel arrangements experience Partial Shading Conditions (PSC). This paper proposes a Global Maximum Power Point Tracking (GMPPT) technique based on the optimization technique of Simulated Annealing (SA) to track the Global MPP (GMPP) of PV modules under PSC. The performance of the SA algorithm is compared against the Perturb and Observe technique to show its improved performance in tracking to the GMPP for a two module system.

A hybrid simulated annealing and perturb and observe method for maximum power point tracking in PV systems under partial shading conditions

This paper presents a hybrid method for Maximum Power Point Tracking (MPPT) of a Photovoltaic (PV) system which experiences non-uniform environmental conditions or partial shading conditions. The hybrid method combines two simple techniques with complementary strengths in achieving Global MPPT. Simulated Annealing (SA) has only recently been applied to PV MPPT and is very effective at locating global maxima with limited implementation complexity. Perturb and Observe (P&O) is a very common technique which provides continuous tracking of the MPP in a simple and easy to implement manner. The P&O method is generally incapable of locating global maxima, and the SA based method is unable to perform continuous searching. By merging these techniques in a hybrid MPPT method consisting of a global searching stage and a local searching stage, the tracking performance is improved compared to what each technique could achieve independently. Simulation results are presented to demonstrate the effectiveness of the proposed hybrid technique.

Application of a Simulated Annealing technique for global maximum power point tracking of PV modules experiencing partial shading

This paper proposes a Simulated Annealing based Global Maximum Power Point Tracking (GMPPT) technique designed for photovoltaic (PV) systems which experience partial shading conditions (PSC). The proposed technique is compared with the common Perturb and Observe MPPT technique and the Particle Swarm Optimization approach to GMPPT. The performance is assessed by considering the time taken to converge and the number of cases where the technique converges to the GMPP Simulation results indicate the improve performance of the Simulated Annealing based GMPPT algorithm in tracking to the Global maxima in a multiple module system experiencing PSC.

A decentralized control strategy for multiple distributed generation in islanded mode

A technical challenge is designing a controller to control multiple distributed generation (DG) and its local loads by voltage-sourced converter (VSC) to operate in an islanded mode under the load parameters uncertainty, and unbalanced and transient conditions. Model predictive control (MPC) for the autonomous operation of multiple DG is proposed. The MPC is designed for multiple inputs and multiple outputs (MIMO) systems, and takes into consideration constraints, and nonlinearities. In this paper, the MPC-based voltage controller is combined with a fast current controller using a discrete time sliding mode controller (DSMC) for limiting the inverter currents under overload condition. The proposed control strategy provides fast tracking, robustness, fast transient recovery, less distortion, and minimal overshoots in voltage and current under 1) the short circuit conditions, 2) load transients and 3) unbalanced loads. Various scenarios including the reference signal tracking and robustness against the load perturbations are considered.

Control strategies for combined photovoltaic — Energy storage systems connected to the grid

There are two distinct motivations for combining a photovoltaic (PV) system with an energy storage system (ESS). The first is motivated by a prosumer, who desires the highest return on their investment by carefully managing when they charge the ESS, use energy within the household and export to the grid to maximize favorable export tariffs. The second is motivated by the grid operator, where a smoother output power from a combined PV-ESS residential system is desirable to minimize fluctuating power on the distribution grid and the corresponding issues this causes. This paper will develop and implement two control strategies for combined PV-ESS based on these two motivations. Simulation results based on real irradiance data will be presented and comments provided on the usefulness of each strategy. Ultimately the results show that it is possible to achieve the motivations of either the prosumer or utility, but not both simultaneously. With increasing penetration of PV systems into the utility grid, that may or may not be integrated with ESS, developing ways to manage this intermittent energy resource becomes important.

Using engineering activities to engage middle school students in physics and biology

Abstract It is well documented that female students show greater engagement with the biological sciences whilst male students gravitate towards the physical sciences. In this study, it is proposed that implementing learning programmes that utilise the engineering process has the potential to influence middle school students’ interest in academic disciplines where their gender is under-represented. To foster boys’ and girls’ curiosity for and engagement with biology and physics, respectively, middle school students worked through a series of engineering tasks delivered by a science, technology, engineering and mathematics (STEM) Education and Outreach Team. The activities included a series of hands-on workshops that focused on biomedical technology and the physics of human hearing and speech. The research included an analysis of data collected through student surveys. The survey included an adapted Draw-A-Scientist Test. The learning programme’s outcomes are discussed in terms of influence on student engagement and the way in which students identify with physics and biology careers and occupations.

Optimization of Tremblay's battery model parameters for plug-in hybrid electric vehicle applications

Accurate modeling of batteries for plug-in hybrid vehicle applications is of fundamental importance to optimize the operation strategy, extend battery life and improve vehicle performance. Tremblays battery model has been specifically designed and validated for electric vehicle applications. Tremblays parameter identification method is based on evaluating the three remarkable points manually picked from a manufacturers discharge curve. This method is error prone and the resultant discharge curve may deviate significantly from the experimental curve as reported in previous studies. This paper proposes to use a novel quantum-behaved particle swarm optimization (QPSO) parameter estimation technique to estimate the model parameters. The performance of QPSO is compared to that of genetic algorithm (GA) and particle swarm optimization (PSO) approaches. The QPSO technique needs less tuning effort than other techniques since it only uses one tuning parameter. Reducing the number of iterations should be a welcome development in most applications areas. Results show that the QPSO parameter estimation technique converges to acceptable solutions with fewer iterations than that obtained by the GA and the PSO approaches.