Probabilistic adaptive model predictive power pinch analysis (PoPA) energy management approach to uncertainty

This paper proposes a probabilistic power pinch analysis (PoPA) approach based on Monte–Carlo simulation (MCS) for energy management of hybrid energy systems uncertainty. The systems power grand composite curve is formulated with the chance constraint method to consider load stochasticity. In a predictive control horizon, the power grand composite curve is shaped based on the pinch analysis approach. The robust energy management strategy effected in a control horizon is inferred from the likelihood of a bounded predicted power grand composite curve, violating the pinch. Furthermore, the response of the system using the energy management strategies (EMS) of the proposed method is evaluated against the day-ahead (DA) and adaptive power pinch strategy

Artificial intelligence-based speed control of DTC induction motor drives: A comparative study

The design of the speed controller greatly affects the performance of an electric drive. A common strategy to control an induction machine is to use direct torque control combined with a PI speed controller These schemes require proper and continuous tuning and therefore adaptive controllers are proposed to replace conventional PI controllers to improve the drive\u27s performance. This paper presents a comparison between four different speed controller design strategies based on artificial intelligence techniques: two are based on tuning of conventional PI controllers, the third makes use of a fuzzy logic controller and the last is based oil hybrid fuzzy sliding mode control theory. To provide a numerical comparison between different controllers, a performance index based on speed error is assigned. All methods are applied to the direct torque control scheme and each control strategy has been tested for its robustness and disturbance rejection ability. (C) 2008 Elsevier B.V. All rights reserved

A hybrid method based on logic predictive controller for flexible hybrid microgrid with plug-and-play capabilities

\ua9 2024 The Author(s). Controlling flexible hybrid microgrids (MGs) is difficult due to the system\u27s complexity, which includes multiple energy sources, storage devices, and loads. Although adding new components to the MG system through the plug-and-play (PnP) feature enables operating of the system in different modes, it adds to the system\u27s complexity, hence necessitates careful control system design. The most challenging aspect of designing the control system is ensuring that it can control the MG optimally in its various modes of operation. Previous methods based on logical control allow for synthesizing a controller capable of controlling the MG in its various operational modes. However, the resultant controller does not optimally operate the MG. Classical model predictive control allows optimal control of the MG only in specific operating modes. On the other hand, switched model predictive control (S-MPC) can optimally control the MG in its various modes. However, the design of S-MPC is complex, particularly for MGs with many operating modes or complex switching logic. Multiple factors contribute to the complexity, including model development, mode detection, and switching logic. This paper presents a hybrid method based on ɛ-variables and classical MPC for constructing the S-MPC for flexible hybrid MG with PnP capabilities. Our results show that the proposed controller synthesis approach provides an effective solution for optimally controlling flexible hybrid MGs with PnP capabilities as the proposed method enables: (i) an increase in the amount of energy export to the utility grid by 50.77% and (ii) a significant decrease in the amount of energy import from the grid by 46.7%

Sensorless Hybrid Control System for Boost Converter in Presence of Uncertain Dynamics

\ua9 2025 Department of Agribusiness, Universitas Muhammadiyah Yogyakarta. All rights reserved. This study presents a design method for a voltage regulation system for a Boost converter that can be used in a power distribution unit within a power generation system. The regulation system is based on a hybrid, sensorless control approach, the structure of the controller is built based on the combination of PI and LQR controllers. The role of the new structural controller in improving the transient and steady-state response as well as enhancing the stability of the Boost converter output signal is studied. The states of the converter are estimated by Luenberger observer system, which is designed using pole placement (PP) technique. Mathematical model of the Boost converter with the hybrid LQR-PI controller is formulated. The gain parameters of the LQR-PI controller are obtained effectively by using Grey Wolf Optimizer (GWO) algorithm. In optimization process the GWO with an effective fitness function is used to tune the state and input weighting matrices of LQR controller. To validate the proposed control system a comparison between the performance of the LQR-PI controller and LQR controller with integral action (I) is achieved. The Boost converter circuit with feedback LQR-I/PI controllers are simulated utilizing Simulink software and their responses are assessed based on rise time, settling time overshoot and steady state error performance parameters. To verify the robustness of the control system, the performance of the converter is evaluated in five working scenarios under hard uncertainties in source voltage, reference voltage and resistive load. The simulation results demonstrate the effectiveness of the presented LQR-I/PI controllers in rejecting the effect of disturbances in the system response. However, the LQR-PI controller showed more accurate and stable output voltage compared to the LQR-I controller

Multi-port coordination: Unlocking flexibility and hydrogen opportunities in green energy networks

\ua9 2024Seaports are responsible for consuming a large amount of energy and producing a sizeable amount of environmental emissions. However, optimal coordination and cooperation present an opportunity to transform this challenge into an opportunity by enabling flexibility in their generation and load units. This paper introduces a coordination framework for exploiting flexibility across multiple ports. The proposed method fosters cooperation between ports in achieving lower environmental emissions while leveraging flexibility to increase their revenue. This platform allows ports to participate in providing flexibility for the energy grid through the introduction of a green port-to-grid concept while optimising their cooperation. Furthermore, the proximity to offshore wind farms is considered an opportunity for the ports to investigate their role in harnessing green hydrogen. The proposed method explores the hydrogen storage capability of ports as an opportunity for increasing the techno-economic benefits, particularly through coupling them with offshore wind farms. Compared to existing literature, the proposed method enjoys a comprehensive logistics-electric model for the ports, a novel coordination framework for multi-port flexibility, and the potentials of hydrogen storage for the ports. These unique features position this paper a valuable reference for research and industry by demonstrating realistic cooperation among ports in the energy network. The simulation results confirm the effectiveness of the proposed port flexibility coordination from both environmental and economic perspectives

A stochastic framework for secure reconfiguration of active distribution networks

Automatic reconfiguration is one of the key actions in self-healing distribution networks. In these networks, after detecting and isolating the faulted portion, an automatic reconfiguration procedure is performed to restore the maximum possible affected loads without further interruptions during repair operations. This procedure becomes more complicated in the networks with integrated distributed generation units as they can bring security challenges for the reconfigured network after a fault event. To overcome these challenges, a stochastic framework is proposed here. In this framework, the reconfiguration procedure is conducted with a fast and reliable method which is based on the graph theory. Besides, the security challenges of utilizing distributed generations after an event are highlighted. Then, since a faulted network is more prone to subsequent faults, different actions of changing the distribution generations output power, preventing the insecure increment of short circuit capacity, and also considering the loadability improvement are proposed in the reconfiguration framework. Then in the final stage, the vulnerability of the distribution system to the uncertainties of load demand is resolved through a chance-constrained programming-based approach. To see the performance of the proposed stochastic framework, it is tested on a standard test system and the results prove its goodness and applicability for real distribution networks

Guest Editorial: On the role of energy storage systems in the grid of the future: Selected papers from the 2019 UK Energy Storage Conference

This Special Issue is a collection of selected papers originatingfrom the 2019 UK Energy Storage Conference (UKES) takenplace on the 3rd–5th September 2019 in the FrederickDouglass Building at Newcastle Helix, Newcastle Universityand supported by the Supergen Energy Storage Network+, theSupergen Energy Networks Hub, the EPSRC National Centrefor Energy Systems Integration, the Energy Storage ResearchNetwork (ESRN), and the STFC Network in Battery Scienceand Technology. The papers have been selected based on theirquality and relevance to the areas covered in this journal, andinclude contributions from the Supergen Energy StorageNetwork + Early Career Researcher community. UKES is a bi‐annual international conference, bringing together researchersfrom academia, industry, and policymakers across the wholefield of energy storage and relevant themes, offering a uniqueopportunity for dissemination and collaboration through presentations, expert talks, and poster sessions to inspire futureresearch. All papers in this Special Issue have been expandedand further developed from their original form to meet thecriteria and high standards for inclusion in this journal

Closed-Form Critical Conditions of Saddle-Node Bifurcations for Buck Converters

A general and exact critical condition of saddle-node bifurcation is derived in closed form for the buck converter. The critical condition is helpful for the converter designers to predict or prevent some jump instabilities or coexistence of multiple solutions associated with the saddle-node bifurcation. Some previously known critical conditions become special cases in this generalized framework. Given an arbitrary control scheme, a systematic procedure is proposed to derive the critical condition for that control scheme.Comment: Submitted to IEEE Transactions on Automatic Control on Jan. 9, 2012. Seven of my arXiv manuscripts have a common reviewe