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The full utilization of solar energy is of great significance in reducing carbon emissions and alleviating environmental problems. Fast frequency regulation plays an important role in the power system with grid-connected two-stage photovoltaic (PV) plants. The presented fast frequency regulation method is composed of droop control, virtual inertia control and de-loading control. This work focuses on

This paper investigates a new wave energy converter (WEC) control problem, which is the energy maximization subject to sensor and actuator faults. Unexpected deviation of system variables from standard conditions, defined as a fault, degrades the control performance and even introduces damages breaking down the whole system. Fault detection for wave energy converters is therefore of great importance

Conventional global maximum power point tracking (GMPPT) algorithms show limited tracking speed and accuracy due to the unnecessary peak search considering the complexity of partial shading conditions (PSCs). This paper proposes a novel power incremental (PI) algorithm for photovoltaic GMPPT and partial shading detection with the aid of the reference voltage line (RVL), representing the voltage of

In this paper, we use a nonlinear model of a grid-connected Archimedes wave swing (AWS) to explore the actual generation potential of this wave energy conversion system. Our model has never been used before for a grid-connected AWS. The control system employs six proportional-integral (PI) controllers to maximize the energy harvest from waves, to minimize the generator power losses, and to maintain

This paper proposes a new energy management model for residential buildings to handle the uncertainties of demand and on-site PV generation. For this purpose, the building energy management system (BEMS) organizes a transactive energy (TE) market among plug-in electric vehicles (PEVs) to determine their charge/discharge scheduling. According to the proposed TE framework, the PEV owners get reimbursed

Solar power forecasting is a key task in modern power grid operation, which can be achieved by machine learning-based methods. Due to multiple practical issues, the data may be incomplete, making the existing machine learning models inaccurate or even ineffective. To counteract the missing data problem, this paper proposes a hybrid learning method. Firstly, a super-resolution perception convolutional

This paper proposes a hierarchical event-triggered model predictive control (HEMPC)-based voltage control strategy to coordinate the reactive power (Var) outputs among all WTs for improving the high-voltage ride-through (HVRT) and post-fault voltage restoration capability of the large-scale wind farms (WFs), while reducing the heavy computational task of the WF controller. The event-triggering condition

With the increasing integration of distributed generators (DGs), renewable energy sources (RESs), and energy storage systems (ESSs) in the hybrid AC/DC microgrid (HMG), the paralleled bidirectional interlinking converters (BILCs) play a significant role in the economic power interaction (EPI) between AC and DC subgrids. This paper proposes a distributed dynamic event-triggered control (ETC) strategy

Cyclorotor-based wave energy converters (WECs) present a relatively new and innovative paradigm for wave energy harvesting. Their operational principle is based on the generation of lift forces on the rotating hydrofoils due to their interaction with wave-induced circulation of water particles. As a result, relatively little is known about their optimal operation. To date, cyclorotor device performance

Sliding mode controller (SMC) based MPPT systems are less effective due to input LCin tank of boost converter. The LCin tank at PV node creates the sinusoidal waves of Vpv/Ipv, due to which phase angle (φ) occurs between triangular wave of inductor current (IL) and sinusoidal Vpv. This creates the adverse effects on SMC operation. In this research work, a series capacitor based boost converter is developed

The increasing concerns with adverse environmental issues have led to the proliferation of renewable energy resources (RESs), which have been expanded more recently to multi-energy systems (MESs) in various parts of the world. MES can improve energy efficiency and reduce carbon emission by co-optimizing multiple forms of energy, including electricity, natural gas, heating, cooling, etc., which provide

The output power fluctuations from the wave energy converters (WECs) with a high peak-to-average ratio need to be smoothed out before supplying power to electric loads or power grids. Usually, short-term energy storage is used to smooth out the output power fluctuations of WECs. In this article, a novel multi-filter-based dynamic power-sharing control is devised for a hybrid energy storage system (HESS)

Light-duty offshore wind power system has been a research hotspot in recent years. The diode rectifier based HVDC scheme is a promising solution and has attracted more and more attention. In this paper, a self-synchronizing control for offshore wind farms connected to diode rectifier based HVDC system is proposed. The active power of each wind turbine is controlled by regulating the amplitude of the

District heating networks (DHNs) can provide electrical power systems (EPSs) flexibility by utilizing heat storage abilities. There are three challenges to the real-time quantification of the flexibility offered by the DHN. First, the balance between the heat supply and consumption in the long term must be considered. Second, the robustness and economy of the quantified result must be guaranteed. Third

Direct-drive wave energy converter (WEC) and buoy control algorithms have shown great potential for renewable wave energy extraction in ideal conditions. However the actual power take-off (PTO) impacts are barely considered in the WEC design. This paper highlights the demands of designing the WEC wave-to-wire control from a global point of view by studying the actual PTO impacts. A permanent magnet

Accordingto recent grid codes, large-scale wind turbines (WTs) are required to provide fast frequency response (FFR). The existing stepwise inertial control methods suggest immediate incremental power injection by WTs, followed by the abrupt over-production termination to avoid over-deceleration of the rotor speed. These methods have a drawback that they impose severe secondary frequency drops (SFD)

The development of optimal control strategies for cyclorotor wave energy converters (WECs) is at an early stage. In this paper, we present new methods and solutions for optimal pitch and/or rotational velocity control strategies for different configurations of cyclorotor-based WECs, in both monochromatic and panchromatic waves. The cyclorotor is modelled with the use of an approximate two-dimensional

To date, wind and solar power plants have mainly provided energy. Going forward, with the application of appropriate controls, they can offer additional grid services, such as regulating reserves. Additional grid services can present an opportunity for additional value streams to wind and solar power plants. However, the additional value might not be realized when operator-determined performance targets

In practical AC/DC hybrid grids, the uncertainty sources such as wind speeds and loads are massive and bounded intrinsically, the latter feature of which is neglected in most probabilistic power flow (PPF) analyses unfortunately. In this paper, a scaled unscented transformation (SUT)-based PPF on the large AC/DC hybrid grids, in particular for addressing the boundary issue of these high-dimensional

In recent years, the doubly fed induction generator (DFIG)-based wind power generation and high-voltage direct-current (HVDC) transmission are widely utilized in practice. The stability issues of sending AC grid, which is composed of line-commutated converter (LCC)-based HVDC and DFIG system, is worthy of attention. Commutation is an important factor in the impedance model of LCC-HVDC rectifier, due

The proliferation of renewable generation brings challenges to the power supply-demand balance. To relieve the power fluctuations caused by photovoltaic (PV) generation variability, a multi-timescale allocation algorithm that considers the allocation of available energy and power is proposed. Contracted demand response energy (CDRE) refers to the regulation energy, which is specified in contracts in

In order to smoothly connect to permanently disturbed grids, DFIG-based wind turbines must precisely synchronize the voltage induced at their open stator with that of the grid. Hence, aiming at addressing the still unpublished task of synchronizing DFIGs to simultaneously unbalanced and harmonically distorted grids, a phase-locked loop (PLL)-less and naturally chatter-free sliding-mode control (SMC)

The limitation of theDC protection device confines the development of MV/LVDC grids. This paper presents a DC dynamic voltage restorer to exploit DC custom power devices for DC distribution networks in principle. It is based on an improved AC/DC dual active bridge and battery energy storage to maintain the voltage profile of sensitive loads in DC networks. The principle of the improved DC-DVR has been

A high proportion of wind power systems with correct as set weak network connections may suffer from cascading trip faults due to the lack of conventional power plants and voltage/var support, which brings about great challenges to secure wind farm operations. To accurately and efficiently evaluate the dynamic var margin for an online field application within large-scale integrated wind areas, the

In this paper, we investigate the control of inverter-based resources (IBRs) for optimal voltage unbalance attenuation (OVUA). This problem is formulated as an optimization program under a tailored dq-frame, which minimizes the negative-sequence voltage at the point of common coupling (PCC) subject to the current, active power, synchronization stability, and feasibility constraints. The program is

Due to the attack signal injection on the DC microgrid system, voltage regulation and current sharing cannot be guaranteed and the overall system may even be destabilized. To solve this problem, a generalized extended state observer (GESO)-based distributed attack-resilient control method is proposed for DC microgrids in this paper. The presented control scheme can detect and mitigate the unknown

In order to maximize utilitarianism and fairness in allocating energy to electric vehicles (EVs) during outages, this study proposes an optimization method based on modified division rules. The idea of essential energy demand is introduced in this paper to maximize the number of EVs that are served during power contingencies. For EVs carrying out the time-critical task(s), the essential energy demand

The production of renewable hydrogen using water electrolysis has emerged with the increasing penetration of renewable energy sources. The energy management system (EMS) plays a key role in the production of renewable hydrogen by controlling electrolyzer’s operating point to achieve operational and economical benefits. In this regard, this article introduces the optimal scheduling for an EMS model

We propose a power-based unit commitment formulation with capacity and intra-hour ramp reserves for dealing with intra-hour wind power variability and uncertainty. Although the formulation has an hourly resolution, the intra-hour ramp requirements capture wind power ramp excursions with a time duration below one hour, and thus allows the formulation to consider intra-hourly wind variability and uncertainty

Despite the ample research on computing power grid flexibility envelopes, how to analytically monetize their points on a one-to-one (1-1) basis remains elusive, due to nonlinear grid constraints. Our methodology renders the 1-1 flexibility-to-cost mapping reachable, but in the context of grid-friendly smart sustainable buildings (GF-SSBs). We explore how different types of device power factor ($pf$)

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The papers in this special section focus on advances in renewable energy forecasting, predictability, business models, and applications in the power industry. During the last 25 years, research has been conducted for developing renewable energy source (RES) forecasting algorithms, especially for wind and solar energy, seeking an improvement of predictability and uncertainty forecasting products. Research

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These instructions give guidelines for preparing papers for this publication. Presents information for authors publishing in this journal.

These instructions give guidelines for preparing papers for this publication. Presents information for authors publishing in this journal.

The changing energy landscape due to the large scale integration of renewable energy and shutting down of conventional thermal plants has opened up the potential of alternate sources in the blackstart services market. Grid forming wind turbines can do controlled islanded operation independent of an external grid voltage and thus participate in network restoration from the start. However, it is necessary

The wind turbines (WTs) present in a wind farm (WF) are subjected to varying wind speeds owing to the wake effect. Additionally, the response of a WF is also affected by the low voltage ride-through (LVRT) characteristic imbibed in each doubly-fed induction generator (DFIG) of WF. Consequently, for deriving an equivalent of a large WF, consideration of wake effect and LVRT are crucial. In this paper

The Gaussian mixture model (GMM) is a powerful tool to establish the probability distributions of random variables in power system analyses. GMM can model arbitrary probability distributions by increasing the number of its Gaussian components, but the commonly used expectation-maximization (EM) algorithm fails to obtain accurate GMM for large component numbers, which limits the application of GMM to

This paper presents a weak grid coupled single stage photovoltaic (PV) system. The system incorporates a battery energy storage (BES) via a bi-directional DC-DC converter (BDDC). The system does not allow the grid power quality to be deteriorated at nonlinear loading conditions, as well as when the grid voltages are unbalanced or distorted. Moreover, the control scheme is resilient to DC offset in

Maritime transportationis currently responsible for about 90% of the worldwide trade and contributes about 2.7% of the global carbon emission. To establish a sustainable maritime system, transportation electrification is an inevitable trend. Under this context, cold ironing technology for all-electric ships (AESs) emerges. In this paper, we propose a tri-level pricing framework of cold ironing services

Virtual inertia and damping control (VIDC) improves the stability of DC microgrid (DC-MG). However, the potential positive feedback aggravates low-frequency oscillation induced by the interaction insides control loops, which is explained and solved in this paper. The multi-timescale impedance modelling framework is established to clarify stability mechanism of VIDC and the low-frequency oscillation

A reliable approach to forecasting solar energy generation using deep learning (DL) models is presented. The approach relies on a prediction-correction (PC) framework. It is composed of a primary model that performs preliminary prediction, followed by a secondary model that is charged with the task of dynamic error compensation (DEC), based on hierarchical residual (HR) learning and Choquet fuzzy integral

In this paper, an autonomous power management strategy is proposed for distributed energy storage units deployed in islanded microgrids with photovoltaic (PV) and droop controlled units. The proposed strategy offers controlled and selective prioritization of the charging/discharging actions while coordinating with PV and droop units to maintain power balance in the microgrid. The selective priority

The uncertainty of wind power and electricityprice restrict the profitability of wind-storage integrated system (WSS) participating in real-time market (RTM). This paper presents a self-dispatch model for WSS based on deep reinforcement learning (DRL). The designed model is able to learn the integrated bidding and charging policy of WSS from the historical data. Besides, the maximum entropy and distributed

Local Energy Communities (LECs) can facilitate the transition towards sustainable and clean energy system infrastructure. In this work, we construct a novel hierarchical energy management framework for an LEC equipped with a community energy storage (CES) installation. The proposed two-stage approach involves end-users making self-driven, cost-optimal decisions (first stage) and said decisions being

The operation of energy storage systems (ESSs) in power systems where variable renewable energy sources (VRESs) and ESSs must contribute to securing the supply, can be considered as an arbitrage against scarcity. The value of using stored energy instantly must be balanced against its potential future value and future risk of scarcity. This paper proposes a multi-stage stochastic programming model for

Jointly managing water and energy systems, rather than treating each system independently, is recognised as an approach that can lead to a more cost-effective and reliable supply, which is particularly critical in water-rich and developing countries. This has motivated the development of various integrated water-energy simulators, each one catering for specific modelling needs through the use of specific

The large-scale integration of renewable generation and the gradual decommissioning of conventional power plants has led to decreased availability of resources for providing services and support to the bulk transmission grid. This paper presents a novel methodology for providing support to the bulk transmission system through the control of thousands of small distributed energy resources (DERs), located

This paper proposes a real-time schedule model of a microgrid (MG) for maximizing battery energy storage (BES) utilization. To this end, a BES life model is linearized using piece-wise linearization and big-M method to assess the BES life loss (BLL) in a real-time manner. The cost-effective schedule model of the MG with multiple energy resources aims to maximize BES utilization while ensuring its sufficient

Increasing renewable generation can lead to significant spatial and temporal changes to the rotor angle stability boundary, such that critical contingencies may drastically change. Additionally, the inherent variability of renewables increases the number of operational scenarios that require stability assessment. This paper presents a methodology whereby a series of location-specific Decision Tree

The COVID-19 has slowed down global economic growth. Meanwhile, it also significantly cuts the global carbon emission, which provides a golden opportunity for the whole world to combat the climate change together. While the former policies (e.g., the CAFE standards, renewable portfolio standards, etc.) have reduced certain level of fossil fuel consumption, the most effective measures (such as carbon