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Electricity imbalance pricing provides the ultimate incentive for generators and suppliers to contract with one another ahead of time and deliver against their obligations. As delivery time approaches, traders must judge whether to trade-out a position or settle it in the balancing market at the as-yet-unknown imbalance price. Forecasting the imbalance price (and related volumes) is therefore a necessity in short-term markets. However, this topic has received surprisingly little attention in the academic literature despite clear need by practitioners. Furthermore, the emergence of algorithmic trading demands automated forecasting and decision-making, with those best able to extract predictive information from available data gaining a competitive advantage. Here we present the case for developing imbalance price forecasting methods and provide motivating examples from the Great Britain’s balancing market, demonstrating forecast skill and value.

The global climate protection policy aimed at achieving a zero greenhouse gas emissions target has led to the fast incorporation of large-scale photovoltaics into the power network. The conventional AC grid was not modeled to be incorporated with large-scale non-synchronous inverter-based energy resources (IBR). Incorporating inertia-free IBR into the grid leads to technical issues such as the degradation of system strength and inertia, therefore affecting the safety and reliability of the electrical power system. This research introduced a new solution to incorporate a flywheel in the rotor of a synchronous machine to improve the dynamic inertia control during a system disruption and to maintain the constancy of the system. The objective of this work is to enhance large-scale photovoltaic systems in such a way that they can avoid failures during a fault. A model of transient constancy with two synchronous generators and a LSPV is established in PowerWorld modeling software. A line-to-ground and three-phase fault are simulated in a system with up to 50% IBR penetration. The outcomes showed that the power network was able to ride through faults (RTFs) and that the stability of frequency and voltage are enhanced because of a flywheel that improved grid inertia and strength.

The accurate prediction of the performance output of photovoltaic (PV) installations is becoming ever more prominent. Its success can provide a considerable economic benefit, which can be adopted in maintenance, installation, and when calculating levelized cost. However, modelling the long-term performance output of PV modules is quite complex, particularly because multiple factors are involved. This article investigates the available literature relevant to the modelling of PV module performance drop and failure. A particular focus is placed on cracks and hotspots, as these are deemed to be the most influential. Thus, the key aspects affecting the accuracy of performance simulations were identified and the perceived relevant gaps in the literature were outlined. One of the findings demonstrates that microcrack position, orientation, and the severity of a microcrack determines its impact on the PV cell’s performance. Therefore, this aspect needs to be categorized and considered accordingly, for achieving accurate predictions. Additionally, it has been identified that physical modelling of microcracks is currently a considerable challenge that can provide beneficial results if executed appropriately. As a result, suggestions have been made towards achieving this, through the use of methods and software such as XFEM and Griddler.

This work focuses on preparing TiO2, CdS, and composite TiO2:CdS thin films for photovoltaic applications by thermal evaporation. The suggested materials exhibit very good optical and electrical properties and can play a significant role in enhancing the efficiency of the device. Various microscopy and spectroscopy techniques were considered to investigate the optical, morphological, photoluminescence, and electrical properties. FTIR confirms the material identification by displaying some peaks in the fingerprint region. UV Vis spectroscopy yields high transmission (80–90%) and low absorbance (5–10%) within the spectral region from 500 nm to 800 nm for the composite thin films. The optical band gap values for CdS, TiO2, and TiO2:CdS thin films are 2.42 eV, 3.72 eV, and 3.6 eV. XRD was utilized to analyze the amorphous nature of the thin films, while optical and SEM microscopy were employed to examine the morphological changes caused by the addition of CdS to TiO2. The decrease in the bandgap of the composite thin films was determined by the Tauc plot, which is endorsed due to the band tailing effects. Photoluminescence spectroscopy depicts several emission peaks in the visible region when they are excited at different wavelengths, and the electrical measurement enhances the material conductivity. Furthermore, the proposed electron transport materials (TiO2, CdS, TiO2:CdS) were simulated with different perovskite materials to validate their design by employing the SCAPS-1D program and assess their performance in commercial implementation. The observed results suggest that TiO2:CdS is a promising candidate to be used as an ETM in PSC with enhanced productivity.

This paper outlines a study undertaken to determine if the electrical performance of Nickel Cobalt Aluminum Oxide (NCA) 3.1 Ah 18650 battery cells can be degraded by road induced vibration typical of an electric vehicle (EV) application. This study investigates if a particular cell orientation within the battery assembly can result in different levels of cell degradation. The 18650 cells were evaluated in accordance with Society of Automotive Engineers (SAE) J2380 standard. This vibration test is synthesized to represent 100,000 miles of North American customer operation at the 90th percentile. This study identified that both the electrical performance and the mechanical properties of the NCA lithium-ion cells were relatively unaffected when exposed to vibration energy that is commensurate with a typical vehicle life. Minor changes observed in the cell’s electrical characteristics were deemed not to be statistically significant and more likely attributable to laboratory conditions during cell testing and storage. The same conclusion was found, irrespective of cell orientation during the test.

This paper proposes a buffered microgrid with a modular grid interface consisting of a modular back-to-back converter. The proposed method provides a flexible strategy that enables both the load and generation expansion of the microgrid, with no sizing constraints on the initial stage. The method maintains the physical separation of the buffered microgrid from the grid by using back-to-back converters, which ensures a safe, secure and seamless operation in both islanded and grid-connected operation modes. The proposed modular structure allows an energy exchange prioritization either between the energy storage systems and the grid or between the energy storage units themselves, depending on the recommended/desired operational strategy. The prioritizations are achieved by using sets of dead zones in the control of the interfacing converters. In order to control the voltage and frequency, an inverse-droop-based dq-frame current control method was implemented in PSCAD/EMTDC to substantiate the proposed method. The simulation results of different scenarios show the operational flexibility, control simplicity and communication-free operation of the microgrid with different types of sources.

This paper proposes an approach for the accurate and efficient parameter identification of lithium-ion battery packs using only drive cycle data obtained from hybrid or electric vehicles. The approach was experimentally validated using data collected from a BMW i8 hybrid vehicle. The dual polarization model was used, and a new open circuit voltage equation was proposed based on a simplification of the combined model, with the aim of reducing the number of parameters to be identified. The parameter identification was performed using NEDC data collected on a rolling road dynamometer; the results showed that the proposed model improved the accuracy of terminal voltage estimation, reducing the peak voltage error from 2.16% using the Nernst model to 1.28%. Furthermore, the robustness of these models in maintaining accuracy when new drive cycles were used was evaluated by comparing WLTC simulations with experimental measurements. The proposed model showed improved robustness, with a reduction in RMS error of more than 50% compared to the Nernst model. These findings are significant because they will improve the accuracy of model-based battery management systems used in electric vehicles, allowing for improved performance prediction without the requirement of recharacterization for different drive cycles or individual cell characterization.

This paper examines the specifications of lithium battery cells, which are considered one of the most vital sources for electrical energy storage units. The specifications have been covered to associate battery performance with its usage for electrically powered motor vehicles. With the motivation of rapid deployment of electric vehicles (EVs) around the world, the key contribution of this study is to provide a comparative investigation of well-known commercially available Li-ion battery cells used as a pack for electric race car. Five lithium cells from different manufacturers were analyzed for start voltage, end voltage, current, and the use of active cooling under different test conditions. Thermal imaging was used to provide more comprehensive analysis of tested battery packs. The outcomes of this experimental investigation are described in the sections below in the order in which the analyses were conducted. The key findings of this study are presented in the conclusion section.