Power Loss Minimization for Distribution Networks with Load Tap Changing Using Genetic Algorithm and Environmental Impact Analysis

This paper presents an investigation of the IEEE 34 bus test system benefits with deployment of distribution static compensator (DSTATCOM) and distributed generation (DG) in the aspect of power loss minimization, bus voltage stability and greenhouse gas emission mitigation. Power loss minimization is carried out by adjusting tap changer positions of the load tap changing transformer with one of the well-known metaheuristic algorithms, Genetic Algorithm (GA). To check the voltage stability of the system after minimization, bus voltage profile index is developed. Similarly, environmental profile is evaluated by three different indices. The behaviour of the system is analysed for four different cases as follows. In Case 1, voltage and reactive power control is provided by capacitor banks. In Case 2, capacitor banks are replaced with DSTATCOM. In Case 3 and Case 4, Case 1 and Case 2 are reinvestigated in the presence of additional DG. All cases are evaluated with both traditional Newton- Raphson optimization algorithm and evolutionary-based GA optimization algorithm. The results indicate that GA optimization provides more energy savings than traditional optimization in all cases with bus voltage index within the allowed range. Besides voltage profile of the system in all cases with two algorithms supports the fact that evolutionary-based metaheuristics offer the best choices for a non-linear optimization problem in comparison with the traditional optimization methods. The overall results reveal that Case 4, test system with DSTATCOM and DG, is the best case which provides minimum power losses and a significant amount of emission savings with greenhouse payback time (GPBT) of 0.458 years

Mitigation of Power System Oscillation in a DFIG-Wind Integrated Grid: A Review

The continuous rise in demand for power supply has made researchers and power system engineers seek alternatives through renewable energy sources to complement the power supply in the power system grid. Wind energy conversion system (WECS) which is the means of harnessing power generation through wind is reportedly one of the most widely installed renewable alternative sources globally. Integrating WECS into the conventional power system grid results in a complex power system grid. Thus, during a disturbance or a fault period on the grid, if proper control measures are not put in place, power system instability due to power system oscillations arises. One such control measure is the damping controller which is coupled to the generating plant through its excitation system. Damping controllers help to dampen power system oscillations, but due to the dynamic nature of the power system and uncertainties inherent in a wind-integrated power grid system, fixed damping controller parameters cannot effectively dampen power system oscillations. Hence, damping controller design becomes an optimization problem. This research reviews damping controller design in a wind-integrated system using optimization techniques

Optimisation, Optimal Control and Nonlinear Dynamics in Electrical Power, Energy Storage and Renewable Energy Systems

The electrical power system is undergoing a revolution enabled by advances in telecommunications, computer hardware and software, measurement, metering systems, IoT, and power electronics. Furthermore, the increasing integration of intermittent renewable energy sources, energy storage devices, and electric vehicles and the drive for energy efficiency have pushed power systems to modernise and adopt new technologies. The resulting smart grid is characterised, in part, by a bi-directional flow of energy and information. The evolution of the power grid, as well as its interconnection with energy storage systems and renewable energy sources, has created new opportunities for optimising not only their techno-economic aspects at the planning stages but also their control and operation. However, new challenges emerge in the optimization of these systems due to their complexity and nonlinear dynamic behaviour as well as the uncertainties involved.This volume is a selection of 20 papers carefully made by the editors from the MDPI topic “Optimisation, Optimal Control and Nonlinear Dynamics in Electrical Power, Energy Storage and Renewable Energy Systems”, which was closed in April 2022. The selected papers address the above challenges and exemplify the significant benefits that optimisation and nonlinear control techniques can bring to modern power and energy systems

Efficiency and Sustainability of the Distributed Renewable Hybrid Power Systems Based on the Energy Internet, Blockchain Technology and Smart Contracts-Volume II

The climate changes that are becoming visible today are a challenge for the global research community. In this context, renewable energy sources, fuel cell systems, and other energy generating sources must be optimally combined and connected to the grid system using advanced energy transaction methods. As this reprint presents the latest solutions in the implementation of fuel cell and renewable energy in mobile and stationary applications, such as hybrid and microgrid power systems based on the Energy Internet, Blockchain technology, and smart contracts, we hope that they will be of interest to readers working in the related fields mentioned above

Advances in Theoretical and Computational Energy Optimization Processes

The paradigm in the design of all human activity that requires energy for its development must change from the past. We must change the processes of product manufacturing and functional services. This is necessary in order to mitigate the ecological footprint of man on the Earth, which cannot be considered as a resource with infinite capacities. To do this, every single process must be analyzed and modified, with the aim of decarbonising each production sector. This collection of articles has been assembled to provide ideas and new broad-spectrum contributions for these purposes

Advances in Condition Monitoring, Optimization and Control for Complex Industrial Processes

The book documents 25 papers collected from the Special Issue “Advances in Condition Monitoring, Optimization and Control for Complex Industrial Processes”, highlighting recent research trends in complex industrial processes. The book aims to stimulate the research field and be of benefit to readers from both academic institutes and industrial sectors

Automation and Robotics: Latest Achievements, Challenges and Prospects

This SI presents the latest achievements, challenges and prospects for drives, actuators, sensors, controls and robot navigation with reverse validation and applications in the field of industrial automation and robotics. Automation, supported by robotics, can effectively speed up and improve production. The industrialization of complex mechatronic components, especially robots, requires a large number of special processes already in the pre-production stage provided by modelling and simulation. This area of research from the very beginning includes drives, process technology, actuators, sensors, control systems and all connections in mechatronic systems. Automation and robotics form broad-spectrum areas of research, which are tightly interconnected. To reduce costs in the pre-production stage and to reduce production preparation time, it is necessary to solve complex tasks in the form of simulation with the use of standard software products and new technologies that allow, for example, machine vision and other imaging tools to examine new physical contexts, dependencies and connections

Perturbation Observer based Adaptive Passive Control and Applications for VSC-HVDC Systems and FACTS Devices

The technology of voltage source converter based high voltage direct current (VSC-HVDC) system and devices used in flexible AC transmission systems (FACTS) has evolved significantly over the past two decades. It is used to effectively enhance power system stability. One of the important issues is how to design an applicable nonlinear adaptive controller for these devices to effectively handle the system nonlinearities and uncertainties. Passive control (PC) has been proposed for the control of nonlinear systems based on Lyapunov theory, which has the potential to improve the system damping as the beneficial system nonlinearities are remained instead of being fully cancelled. However, PC is not applicable in practice as it requires an accurate system model. Adaptive passive control (APC) and robust passive control (RPC) have been developed to handle some specific type of system uncertainties based on strict assumptions on system structure and uncertainty. However, their applications are limited as various system uncertainties exist. This thesis aims to develop a perturbation observer based adaptive passive control (POAPC) to make PC applicable in practice. The combinatorial effect of system nonlinearities, parameter uncertainties, unmodelled dynamics and time-varying external disturbances is aggregated into a perturbation, which is estimated by a perturbation observer (PO). The proposed approach does not require an accurate system model and can handle various system uncertainties. POAPC is applied to two-terminal VSC-HVDC systems to handle various system uncertainties. The VSC-HVDC system model is firstly developed, the proposed controller can inject an extra system damping and only the measurement of direct current (DC) voltage, active and reactive power is needed. The effectiveness ofPOAPC is verified by simulation in comparison with that of passive control (PC) and proportional-integral (PI) control. Moreover, a hardware experiment is carried out to verify its implementation feasibility and applicability. A passive controller is designed for multi-terminal VSC-HVDC (VSC-MTDC) systems via energy shaping, in which the dynamics related to the active power, reactive power, and DC cable voltage is transformed into an output strictly passive form. Then the remained internal dynamics related to DC cable current and common DC voltage is proved to be asymptotically stable in the context of Lyapunov criterion. PC is applied on a four-terminal VSC-MTDC system under eight cases to evaluate its control performance. POAPC is developed on the VSC-MTDC system to maintain a consistent control performance under different operating points and provide a significant robustness to parameter uncertainties, together with other unmodelled dynamics and time-varying external disturbances. Simulation results are provided to evaluate the control performance of POAPC in comparison to that of PI control and PC. Perturbation observer based coordinated adaptive passive control (POCAPC) is proposed for excitation controller (EC) and FACTS controller on both single machine infinite bus (SMIB) systems and multi-machine power systems. Only the range of control Lyapunov function (CLF) is needed and the dependence of an accurate system model can be partially reduced, thus POCAPC can be easily applied to multi-machine power systems. Its control performance is compared with that of conventional proportional-integral-derivative and lead-lag (PID+LL) control, coordinated passive control (CPC) and coordinated adaptive passive control (CAPC) on both an SMIB system and a three-machine power system by simulation. Then a hardware-in-the-loop (HIL) test is undertaken to verify the implementation feasibility of the proposed controller