Integration Of Intermittent Renewable Energy Research Articles

Impact of Artificial Intelligence on the Planning and Operation of Distributed Energy Systems in Smart Grids

This review paper thoroughly explores the impact of artificial intelligence on the planning and operation of distributed energy systems in smart grids. With the rapid advancement of artificial intelligence techniques such as machine learning, optimization, and cognitive computing, new opportunities are emerging to enhance the efficiency and reliability of electrical grids. From demand and generation prediction to energy flow optimization and load management, artificial intelligence is playing a pivotal role in the transformation of energy infrastructure. This paper delves deeply into the latest advancements in specific artificial intelligence applications within the context of distributed energy systems, including the coordination of distributed energy resources, the integration of intermittent renewable energies, and the enhancement of demand response. Furthermore, it discusses the technical, economic, and regulatory challenges associated with the implementation of artificial intelligence-based solutions, as well as the ethical considerations related to automation and autonomous decision-making in the energy sector. This comprehensive analysis provides a detailed insight into how artificial intelligence is reshaping the planning and operation of smart grids and highlights future research and development areas that are crucial for achieving a more efficient, sustainable, and resilient electrical system.

Situation-Aware Load Restoration Considering Uncertainty and Correlation

In order to minimize power supply interruption to customers, power system restoration needs to be performed rapidly after a blackout. With the integration of intermittent renewable energy and flexible loads, power system load patterns are becoming more uncertain. The goal of this paper is to tackle the challenging task of developing a secure yet speedy load restoration planning strategy considering load uncertainty. The key is to leverage the real-time measurements of the restored load blocks to refine the statistical knowledge about the unrestored load blocks derived from historical data, such that the load restoration plans can be less conservative without harming security. Specifically, as the restoration process rolls forward and more loads are restored, we use a Kalman filter to update the probability distribution of the unrestored loads using the newly available measurements from the restored loads. With the updated distribution, a rolling-horizon load restoration problem for load-pickup decision making is formulated with given specified confidence levels under frequency, voltage, and power flow constraints. The effectiveness of the proposed method is evaluated through case studies on the IEEE 39-bus test system and the NPCC 140-bus system. Results demonstrate that the proposed method can restore loads more quickly and securely than conventional methods under load uncertainty.

EnergyScope Pathway: An open-source model to optimise the energy transition pathways of a regional whole-energy system

Due to the imperative nature of addressing climate change, the energy transition is currently underway, prompting the recognition of its urgency. Energy system optimisation models have emerged as crucial tools to assist policymakers in formulating laws and regulations that facilitate the transition towards carbon neutrality. While numerous models have been developed to explore various scenarios and define long-term objectives, only a few models focus on optimising the specific pathway to achieve these objectives. Many existing models lack the necessary time resolution to capture the integration of intermittent renewable energies; or are not open-source, creating a challenge in terms of transparency and reproducibility.This paper introduces EnergyScope Pathway, an open-source and documented model that addresses these limitations. It specifically optimises investment strategies for the whole-energy system over a 30-year period, or more, and optimising its hourly operation. This approach allows for a comprehensive evaluation of the effective integration of intermittent renewable energy sources. The model has a concise and efficient formulation, enabling its execution on personal laptops within approximately 15 min. By applying the model to the case study of Belgium, which presents challenges due to limited potential for renewable energy, we illustrate the importance of four pillars: energy efficiency, renewable energies, sector coupling, electrification and imports. The result pave the way to a new and incremental tool to support decision makers. In comparison to non open-source models, we verified the model’s results with similar studies and found consistency in terms of technico-economic estimations.

Ultralow Ag-assisted carbon–carbon coupling mechanism on Cu-based catalysts for electrocatalytic CO2 reduction

Electrocatalytic CO2 reduction to C2H4 supplies an economically viable route for CO2 fixation with the integration of intermittent renewable energy. Cu-based catalysts are capable of catalyzing CO2 to C2H4, while suffering from the high overpotential and low Faradaic efficiency. In this joint experimental-computational work, an Ag-assisted carbon–carbon coupling is exploited on Cu-based catalysts. A systematic characterization analysis suggests that an ultralow quantity of Ag atoms in the Cu catalysts motivates electron transfer from Cu to Ag, regulating the electronic state of highly dispersed Ag. Meanwhile, the Ag incorporation provokes the formation of more oxygen defects on the catalyst surface, improving the adsorption and activation of CO2 molecules. Density functional theory studies prove the improvement effect of Ag for CO2 to COOH*. *CO hydrogenation is energetically more favorable than *CO dimerization pathway, and two *CHO dimerization produces *OCHCHO* key intermediates, which greatly reduces the energy barrier for C2H4 formation.

Coordinated energy management for commercial prosumers integrated with distributed stationary storages and EV fleets

The integration of intermittent renewable energy and stochastic electric vehicle (EV) loads in buildings and power systems poses new challenges such as increased peak demands and grid instability. Regarding multi-directional interactions among heterogeneous loads, generation, storages, and power grid, the synergy between prosumers, stationary storages and electromobility is crucial for future energy systems. In this study, coordinated energy management was investigated for a neighborhood involving commercial buildings with distributed renewables and stationary batteries, and plug-in EVs. Compared to the collaborative control of EV and stationary storages at single prosumers, the energy sharing system with centralized control of mobile and stationary storages achieved superior techno-economic performance. Case studies demonstrated that the renewables-storage sharing with centralized storage scheduling decreased annual energy costs for both buildings and EV owners by over 15%, and the cycle aging cost of stationary storage by 25%. While the performance under day-ahead scheduling of EV and stationary storages depends more on the prediction accuracy, the real-time renewables-storage sharing strategy integrated with pre-scheduled EV charging provides an effective alternative solution for the stakeholders. The study explores potential coordinated approaches for communities with low-carbon buildings, flexible storages, and intelligent infrastructure to maximize the operational value and improve the grid stability.

The development of battery storage co-located with renewable energy in China: A policy-driven system dynamics approach

Battery storage is widely regarded as an indispensable solution to the large-scale integration of intermittent renewable energy into the power grid. Being still too expensive by itself, battery storage is currently promoted in China for utility-scale grid-parity wind/solar projects with compulsive technical standards or voluntary allocation requirements for those additional renewable projects beyond grid integration capacity. Under mandatory policies, part of the revenue from renewable energy is used to pay for battery storage. Without a mature electricity market, the development of battery storage co-located with renewable energy would be largely dependent on policy design. This paper conducts a policy-driven system dynamics simulation on the development mechanism of battery storage co-located with renewable energy in China. The results show that the installed capacity growth of battery storage will mainly be driven by mandatory policies before 2024 and mandatory policies will become almost ineffective after 2028. However, mandatory policies may still dominate the development of battery storage after 2030 if the cost reduction is restrained. The conclusions provide theoretical support for the development of battery storage co-located with renewable energy in China. To minimize the adverse effect of mandatory policy, policymakers should keep close eyes on the advance in technology and power market and adjust the policy accordingly.

Redox Flow Batteries: Electrolyte Chemistries Unlock the Thermodynamic Limits.

Redox flow batteries (RFBs) represent a promising approach to enabling the widespread integration of intermittent renewable energy. Rapid developments in RFB materials and electrolyte chemistries are needed to meet the cost and performance targets. In this review, special emphasis is given to the recent advances how electrolyte design could circumvent the main thermodynamic restrictions of aqueous electrolytes. The recent success of aqueous electrolyte chemistries has been demonstrated by extending the electrochemical stability window of water beyond the thermodynamic limit, the operating temperature window beyond the thermodynamic freezing temperature of water and crystallization of redox-active materials, and the aqueous solubility beyond the thermodynamic solubility limit. They would open new avenues towards enhanced energy storage and all-climate adaptability. Depending on the constituent, concentration and condition of electrolytes, the performance gain has been correlated to the specific solvation environment, interactions among species and ion association at a molecular level.

Capacity optimization of pumped storage hydropower and its impact on an integrated conventional hydropower plant operation

The energy sector contributes to around 60% of total greenhouse gas emissions. To limit climate change, the world is going through an energy transition to clean and affordable energy, therefore the share of variable renewable energy is increasing day by day. Power systems require significant flexibility to operate reliably. Pumped storage hydropower allows load balancing and stable integration of intermittent renewable energy in the electrical grid. All energy storage technologies, including pumped storage hydropower, are considered a net negative contributor to the grid since they draw more energy than they deliver. This paper uniquely investigates the true potential of pumped storage hydropower and its optimum operation along with existing conventional hydropower. It considers power, energy production, and utilization for both installations to determine an equilibrium condition for a net positive energy balance. The case study of the 300 MW Balakot conventional hydropower plant in Khyber Pakhtunkhwa, Pakistan indicates that the pumped storage hydropower sites, where additional water streams reach the upper storage reservoir, can reduce pumping energy consumption by up to 166 GWh/year. Accordingly, a pumped storage hydropower facility is proposed at Paras, Pakistan, modeled, and optimized in an integrated manner with the Balakot conventional hydropower plant for a net positive annual energy generation and profitability. The integrated power and energy modeling and capacity optimization of the hydropower complex highlight the importance of suitable site selection for pumped storage hydropower near existing conventional hydropower reservoirs. Value-added contribution of this configuration is that it can enhance annual energy generation from integrated conventional hydropower, reduce the upfront capital cost of the project by 10–15%, squeeze the project implementation schedule and result in a smaller carbon footprint to meet the ultimate objective of limiting climate change. Additionally, it unlocks huge untapped pumped storage hydropower potential besides existing conventional hydropower. Furthermore, the study guides the scientific and engineering organizations on optimum capacity utilization without impeding energy generation from conventional hydropower facilities.

Sustainable power systems operations under renewable energy induced disjunctive uncertainties via machine learning-based robust optimization

For sustainable and reliable power systems operations integrating variable renewable energy, it is essential to incorporate the uncertain intermittent power outputs. A novel robust unit commitment framework with data-driven disjunctive uncertainty sets is proposed for sustainable energy systems with volatile renewable wind power, assisted by machine learning. The approach can flexibly identify the uncertainty space based on renewable power forecast error data with disjunctive structures. Specifically, the uncertainty data are grouped using K-means and density-based spatial clustering of applications with noise (DBSCAN) following the optimal cluster number determined by the Calinski-Harabasz index. Disjunctive uncertainty sets are constructed accordingly as the union of multiple basic uncertainty sets, including conventional box and budget uncertainty sets, and data-driven uncertainty sets using Dirichlet process mixture model, principal component analysis coupled with kernel density estimation, and support vector clustering. Subsequently, the problem is formulated into a two-stage adaptive robust unit commitment model with data-driven disjunctive uncertainty sets and with a multi-level optimization structure. To facilitate the solution process, a tailored decomposition-based optimization algorithm is developed. The effectiveness and scalability of the proposed framework are illustrated with two case studies investigating sustainable operations scheduling based on IEEE 39-bus and 118-bus systems, considering the integration of intermittent renewable energy. Results show that the proposed framework can reduce the price of robustness by 8–48% compared to the conventional “one-set-fits-all” robust optimization approaches. Benchmarking with stochastic programming indicates that the proposed framework can achieve the same or better economic performance for sustainable operations with over 75% less computational time.

Degradation of electrochemical active compounds in aqueous organic redox flow batteries

Aqueous organic redox flow batteries (AORFBs) represent a promising energy storage technology that may enable the grid-scale integration of intermittent renewable energy. The water-soluble, redox-active organic species that are utilized to reversibly store electricity are the most critical performance-determining components in AORFBs. To ensure affordability and competitiveness in practical installations, it is of vital importance to enhance the structural stability and long-term durability of organic electrolytes, ultimately decreasing their levelized cost. Herein, we summarize the proposed decomposition mechanisms for representative organic electrolytes, including quinones, viologens, nitroxide radicals, and ferrocene derivatives. By reviewing the influence of molecular engineering on the side reactions of electrolytes, we intend to provide a better understanding of the decisive factors and inspire further attempts to design structurally robust and cycling-stable electrolytes for AORFB. Finally, we provide possible directions and prospects for future AORFB research.

Heterogeneity in the Mo doped La0.55Sr0.45FeO3 cathode for direct CO2 electrolysis

• Mo-doping in La 0.55 Sr 0.45 FeO 3 prevents the production of SrCO 3 in CO 2 electrolysis. • Mo 6+ accelerates the adsorption/dissociation process of CO 2 /CO. • Heterogeneous regions were found to enhance the CO 2 electrolysis. • Initial performance dropping during CO 2 electrolysis is related to adsorption of CO. The large-scale integration of intermittent renewable energies into the power grid could reduce the CO 2 emission from the combustion of fossil fuel, but it requires energy storage techniques to balance the energy production and demand. The electrolysis of CO 2 that converting electricity into chemicals/fuels provides a sustainable way of energy storage and CO 2 reduction. Solid oxide electrolysis cell (SOEC) operating at around 800 °C was able to provide highly efficient transformation of CO 2 because the high temperature was able to decrease the energy demand and increase the activation of CO 2 than room temperature electrolysis. In this study, Mo-doped ferrite perovskite, La 0.55 Sr 0.45 Fe 0.85 Mo 0.15 O 3 , was studied as the cathode of an SOEC for the direct electrolysis of CO 2 at 800 °C. Cell with La 0.55 Sr 0.45 Fe 0.85 Mo 0.15 O 3 cathode showed a significantly higher current density during CO 2 electrolysis than the one with La 0.55 Sr 0.45 FeO 3 cathode. Compared with the parent La 0.55 Sr 0.45 FeO 3 cathode that will subject to a superficial decomposition into Fe 0 and SrO or SrCO 3 at an elongated cathodic bias of − 1.4 V, Mo-doping will induce the production of Ruddlesden-Popper phase ( e.g. (La,Sr) 2 (Mo,Fe)O 4 , Fe-Mo-O oxides and Fe 0 ). La 0.55 Sr 0.45 Fe 0.85 Mo 0.15 O 3 cathode was found to an unobvious current decrease at − 1.1 V, but a cell degradation was found under a high bias of − 1.4 V. During the 97 h’ aging under a cathodic bias (−1.4 V), the reduced molybdenum cation in La 0.55 Sr 0.45 Fe 0.85 Mo 0.15 O 3 was found to be less mobile than Fe 3+/2+ , La 3+ or Sr 2+ , and the perovskite with Fe-deficit region were also found to be important for the activation of CO 2 and dissociation of CO in the electrochemical process.

Smart Distribution Network Situation Awareness for High-Quality Operation and Maintenance: A Brief Review

In order to meet the requirements of high-tech enterprises for high power quality, high-quality operation and maintenance (O&M) in smart distribution networks (SDN) is becoming increasingly important. As a significant element in enhancing the high-quality O&M of SDN, situation awareness (SA) began to excite the significant interest of scholars and managers, especially after the integration of intermittent renewable energy into SDN. Specific to high-quality O&M, the paper decomposes SA into three stages: detection, comprehension, and projection. In this paper, the state-of-the-art knowledge of SND SA is discussed, a review of critical technologies is presented, and a five-layer visualization framework of the SDN SA is constructed. SA detection aims to improve the SDN observability, SA comprehension is associated with the SDN operating status, and SA projection pertains to the analysis of the future SDN situation. The paper can provide researchers and utility engineers with insights into the technical achievements, barriers, and future research directions of SDN SA.

Effects of Plant Scale on Flexible Operation of Amine-based CO2 Capture Processes

The transition of energy systems to meet net-zero targets for CO2 emissions will require increased integration of intermittent renewable energy. Thermal power plants with carbon capture and storage (CCS) will have the important role of providing affordable dispatchable low carbon capacity, maintaining security of supply and enabling the expansion of other low-carbon sources. Whilst the flexibility of power plants is relatively well characterised, the flexibility of the CO2 capture plant is not well understood, particularly in terms of the overall CO2 emissions, process dynamics, operatbility and the energy requirements. Pilot plant and demonstration studies provide valuable insight on the key characteristics and factors that impact process flexibility. This study investigates the impact of plant scale and key process factors on the performance of amine-based CO2 capture during flexible operation. These insights will be applied to a case study that investigates dynamic performance during the start-up and shut down of CO2 capture plants.

Online distributed neurodynamic optimization for energy management of renewable energy grids

An online distributed neurodynamic optimization-based energy management method is proposed to accommodate the integration of intermittent renewable energy in smart grids. The proposed approach takes advantage of the online prediction method to deal with uncertainties from renewable energy generators, the distributed consensus algorithm for information exchange, and neurodynamic optimization to manage coupling constraints. The proposed distributed optimization neurodynamic approach utilizes a one-layer neural recurrent network without auxiliary variables and enables parallel computation, significantly alleviating the data calculation burden compared with the traditional centralized methods and requiring no auxiliary variables, in contrast to most of the existing distributed methods. The convergence, optimality and robustness to communication failures of the proposed method are verified by various case studies with a modified IEEE 33-bus distribution system and a modified IEEE 123-bus distribution system.

A Stacked Denoising Sparse Autoencoder Based Fault Early Warning Method for Feedwater Heater Performance Degradation

Power grid operation faces severe challenges with the increasing integration of intermittent renewable energies. Hence the steam turbine, which mainly undertakes the task of frequency regulation and peak shaving, always operates under off-design conditions to meet the accommodation demand. This would affect the operation economy and exacerbate the ullage of equipment. The feedwater heater (FWH) plays an important role in unit, whose timely fault early warning is significant in improving the operational reliability of unit. Therefore, this paper proposes a stacked denoising sparse autoencoder (SDSAE) based fault early warning method for FWH. Firstly, the concept of a frequent pattern model is proposed as an indicator of FWH performance evaluation. Then, an SDSAE- back-propagation (BP) based method is introduced to achieve self-adaptive feature reduction and depict nonlinear properties of frequent pattern modeling. By experimenting with actual data, the feasibility and validity of the proposed method are verified. Its detection accuracy reaches 99.58% and 100% for normal and fault data, respectively. Finally, competitive experiments prove the necessity of feature reduction and the superiority of SDSAE based feature reduction compared with traditional methods. This paper puts forward a precise and effective method to serve for FWH fault early warning and refines the key issues to inspire later researchers.

Electrochemistry to Power out-Earth Basecamps for Space Exploration

In a decade or so, the International Space Station will be done with. The $150bn outpost will plunge back to Earth in a fireball above the Pacific Ocean leaving astronauts with nowhere to go. If humans want to maintain a presence in space, they need a new plan, and soon. Future of human space exploration is then the perspective of building space villages stepping space exploration. While NASA remains fixated on sending people to Mars, ESA sees the moon as the next venture for a long time to come. In any case one major challenge similar to earth is powering those space planet habitats. With the recent focus on human missions to the moon and eventually Mars, hydrogen will continue to be innovatively stored, measured, processed and employed. Beyond use as a rocket propellant, hydrogen may be derived from local water or soil to supply fuel for transportation, electrical power and crewmember breathable oxygen. For instance, on the International Space Station, water is split into oxygen for breathing and hydrogen. In the former space programs (GEMINI, APOLLO, space shuttle), fuel cells were already used to power the different space ships. In the future, hydrogen will be recombined with exhaled carbon dioxide for water renewal. Generating and recycling hydrogen in space will decrease the cost and complexity of remote missions by reducing the need for supplies delivered from Earth. By the way, Fuel Cells are also alternative power sources for mobility of various aerospace vehicles complementary to primary or secondary batteries. On earth, Power-to-gas—which offers the advantage of being able to store surplus energy as gas—is expected to play a role in facilitating the integration of intermittent renewable energy into our grids. Surplus electricity is used to produce hydrogen via a water electrolysis process. The hydrogen then reacts with CO2 in a methanation reactor, producing synthetic methane. The methane can either be injected back into the grid or used to fuel gas-powered vehicles. Today earth demonstrators unit are built on technology developed by the CEA, which leverages a compact milli-structured plate reactor developed by LITEN, a CEA Tech institute. Therefore today CEA-LITEN is pursuing a variety of alternative power sources, for terrestrial and aerospace vehicles. In a global approach also pursuing power generation and electrolysis systems offering a global autonomous energy solution. Those alternatives include primary and secondary batteries with a disruptive approach to increase performance and safety (“Post Lithium-ion” batteries), Fuel Cells with significant advances in the development of Proton Exchange Membrane (PEM) fuel cells using hydrogen and air or pure oxygen as the fuel and oxidant for land, air or water mobility applications. LITEN is also involved in developing reversible Solid Oxide Fuel Cells (SOFC) / Solid Oxide Electrolysis Cells (SOEC) for ground-based power generation. CEA is today building upon these PEM and SOFC developments advance technologies, providing reliable, compact and high-energy renewable power sources for terrestrial applications similar to those foreseen by NASA for aerospace. Batteries, Fuel Cells, Electrolysis… All those systems usually covered at system or components level in the aerospace field have one common thread: they are all made thanks to Electrochemistry fundamentals highlighting the many ways in which electrochemistry enables so many space-related activities. In this work we will discuss how recent terrestrial advances and current challenges are creating more and more opportunities for electrochemistry in space while having to face space harsh conditions.

Pumped energy storage system technology and its AC–DC interface topology, modelling and control analysis: a review

Pumped-storage hydropower plants can contribute to a better integration of intermittent renewable energy and to balance generation and demand in real time by providing rapid response generation. The utilisation of variable-speed pump-turbine units with a doubly fed induction machine is being progressively applied due to its overall efficiency and high level of operating flexibility. This study presents state-of-the-art pumped energy storage system technology and its AC–DC interface topology, modelling, simulation and control analysis. It also provides information on the existing global capacities, technological development, topologies and control strategies of the pumped-storage system. This report also outlines the analysis of dynamic performances of the system. It also attempts to recommend the future works in this area. This study concludes that pumped storage is the most suitable technology for small autonomous island grids and massive energy storage, where the energy efficiency of pumped storage varies in practice. Around the world, the size of the pumped-storage plant mostly lies in the range of a small size to 3060 MW. The back-to-back voltage source converter topology is mostly conducted due to its significant features. Due to its imperative features, the vector control strategy is widely used. The pumped-storage plant is dedicated to power management and stability regulation of grid and isolated power systems.

V2G—An Economic Gamechanger in E-Mobility?

The Vehicle-2-grid (V2G) technology enabling bidirectional charging between electric vehicles and the energy grid system for frequency regulation and load balancing has the potential of significantly improving the financial viability of electric mobility. This paper has identified that the introduction of V2G offers a plethora of potentially beneficial business models, which primarily focus on providing stability services to the energy grid and optimizing the economic benefits of owning an EV. Within these overarching categories, it is likely that several niche business models will emerge, as the current V2G concepts include the integration of intermittent renewable energy into the grid, reduction of peak load, charging optimization, and regulation of participating capacity. Most important is the balancing of the five market factors in order to create a profitable business case, as this is what makes V2G move from a potential revenue generator to a profitable business.

Coal power flexibility, energy efficiency and pollutant emissions implications in China: A plant-level analysis based on case units

Integration of intermittent renewable energy in the power systems requires balancing service of conventional fossil fuel power plants, which is mainly provided by coal power in China. However, flexible operation of coal power units will incur energy efficiency penalty, and output additional CO2 and pollutant emissions. In this paper, we use a high-resolution operation dataset collected from two typical coal power units to evaluate environmental impacts of flexible operation of coal power in China. To address this, we examine the generation mechanisms of CO2 and three atmospheric pollutants by coal power units, and then calculate the emissions. We also outline the potential of coal power units to perform flexible operation and discuss retrofit options for more efficient flexible operation. In addition, we use plant-level operation data from typical-sized coal power units to estimate emission levels during processes of start-up, deep cycling and regular operations. In the case 300 MW and 600 MW unit respectively, deep cycling operation would incur an increase of 17.5% and 11.3% in heat rate and CO2 emissions factor, 10.2% and 108.4% in NOx factor, and 41% in dust factor, compared with full load operation. The NOx emissions of a cold start-up in the case 300 MW and 600 MW unit are roughly the amount of 8 hours and 12.3 hours of regular full load operation, respectively. This paper has implication on employing flexible operation of coal power to integrate renewable energy in China’s coal-dominated power systems.

Hybrid Hydro Renewable Energy Storage Model

This paper aims at presenting wind & tidal turbine pumped-storage solutions for improving the energy efficiency and economic sustainability of renewable energy systems. Indicated a viable option to solve problems of energy production, as well as in the integration of intermittent renewable energies, providing system flexibility due to energy load’s fluctuation, as long as the storage of energy from intermittent sources. Sea water storage energy is one of the best and most efficient options in terms of renewable resources as an integrated solution allowing the improvement of the energy system elasticity and the global system efficiency.