Regenerative Sources Research Articles

Multielectron Bifunctional Systems for Symmetric Nonaqueous Redox Flow Batteries

The introduction of renewable energy generation sources onto the electrical grid is critically dependent on the development of reliable, inexpensive energy storage technology. Redox flow batteries (RFBs) may offer a solution, but many issues remain. For example, aqueous systems are only capable of relatively low cell voltages owing to the limited accessible potential window of water. While other electrochemically useful solvents could provide a larger window, their cost and durability have been problematic. Moreover, the need for an ion-exchange membrane to prevent crossover further increases cost and adds significant cell resistance, especially in nonaqueous systems.We have previously reported the use of linked electron donor/acceptor compounds D-L-A (where L represents a simple alkyl or aryl linker) to allow the replacement of the expensive ion-exchange membrane with a simple porous separator. Such systems have at least three accessible stable redox states: the “parent” D-L-A state, an oxidized form D+-L-A (catholyte), and a reduced form D-L-A- (anolyte).Numerous systems of this type have now been prepared and characterized, yielding nominal cell potentials over 2 V, with promising stability. Several of these systems have the capability of undergoing a net 2e- oxidation as well as a net 2e- reduction, thus providing increased energy density. One such compound is shown below.The electrochemical properties of several representative linked electron donor/acceptor materials will be described, including progress toward the development of a 4e- system having 9 (nine!) accessible stable redox states. Preliminary data from a prototype RFB device employing such compounds as active materials will also be presented. Figure 1

A mobile wind turbine design for emergencies in rural areas

Electrical energy sources are one of the main needs after natural disasters such as earthquakes and tornadoes not only for emergency response teams but also for survivors’ use. In such cases, the use of renewable energy sources is not very common. Generally, generators that use fossil fuels are commonly used. One of the main reasons for preference is that the generators of renewable energy sources are generally of static structure. Another reason is that renewable energy sources are not stable. However, this reason changes in rural areas. Because there are certain areas with high wind intensity in rural areas. If it is possible to reach the windy place, the wind turbines to be installed will help meet the electricity needs such as, the illumination of tent cities. Furthermore, it can be used by search and rescue, health, and safety teams. The main aim of the study is to design a renewable energy source that can be easily transported to different places for the mentioned reasons. In this study, a small 4-bladed vertical wind turbine that can be mounted on a 4 wheel-drive skid-steering ground vehicle is designed for use in the mentioned situations.

Automation of control of electric generators from renewable energy sources in hybrid power supply systems

The article notes that due to the increasing number of electricity generating equipment based on renewable energy sources and consumers of electricity received from them, it becomes necessary to combine generating sources, consumers and control units into autonomous electric power systems. Due to the uneven generation and consumption of renewable energy sources under the influence of external conditions (wind, solar radiation, etc.), renewable energy sources should be reserved by means of traditional energy in the so-called hybrid mode, when traditional alternators must work together with renewable energy sources. In this case, the task of creating a tracking inverter that converts direct current (DC) to alternating current (AC) according to the characteristics of the AC generator arises. At Bauman Moscow State Technical University the experimental samples of a DC-to-AC inverter with its own logic and microcontroller have been developed and created. They control the conversion mode either by the signals of the reference AC network, or by the signal of the microcontroller. The proposed devices are designed to fully automate power generation processes and power consumption processes in hybrid power supply systems and are designed to manage input and output generating capacities and power consumers to ensure maximum efficiency of power generation from renewable energy sources.

Optimal control of flexible natural gas combined cycles with stress monitoring: Linear vs nonlinear model predictive control

In future energy markets, traditional thermal power plants are expected to cycle more to adapt their operation to the intermittent power generation of renewable energy sources. Gas turbine load ramps and stresses in thick-walled equipment of the steam cycle are arguably the main limitations in the flexible operation of natural gas combined cycles. This work proposes a control strategy based on model predictive control with stress monitoring to overcome both limitations and enhance the flexible operation of thermal power plants. The linear and nonlinear formulation of the problem included in the model predictive control strategy are described, and two different modelling approaches for the stresses in the high pressure drum and steam turbine rotor are presented. The results demonstrate that the proposed control strategy is capable of computing optimal control sequences without exceeding the maximum allowable stress in critical components and the ramp rates of the gas turbine. The comparison between the linear and nonlinear formulations shows the superior performance of linear model predictive control and suggests that the nonlinear formulation should only be used when the stress models can not be expressed as a linear system of equations.

Prospects of ocean-based renewable energy for West Africa’s sustainable energy future

PurposeThe limited supply of fossil fuels, constant rise in the demand of energy and the importance of reducing greenhouse emissions have brought the adoption of renewable energy sources for generation of electrical power. One of these sources that has the potential to supply the world’s energy needs is the ocean. Currently, ocean in West African region is mostly utilized for the extraction of oil and gas from the continental shelf. However, this resource is depleting, and the adaptation of ocean energy could be of major importance. The purpose of this paper is to discuss the possibilities of ocean-based renewable energy (OBRE) and analyze the economic impact of adapting an ocean energy using a thermal gradient (OTEC) approach for energy generation.Design/methodology/approachThe analysis is conducted from the perspective of cost, energy security and environmental protection.FindingsThis study shows that adapting ocean energy in the West Africa region can significantly produce the energy needed to match the rising energy demands for sustainable development of Nigeria. Although the transition toward using OBRE will incur high capital cost at the initial stage, eventually, it will lead to a cost-effective generation, transmission, environmental improvement and stable energy supply to match demand when compared with the conventional mode of generation in West Africa.Practical implicationsThis study will be helpful in determining the feasibility, performance, issues and environmental effects related to the generation and transmission of OBRE in the West Africa region.Originality/valueThe study will contribute toward analysis of the opportunities for adopting renewable energy sources and increasing energy sustainability for the West Africa coast regions.

Приоритетные направления развития российского программного обеспечения для электроэнергетики

The paper presents the technological trends in the electric power industry in Russia for the period up to 2035. The interaction platform for the subjects of the energy market, the operational production management system (MES/MOM), the enterprise asset management system (EAM/APM), including software for predictive analytics, and software for predicting the generation of renewable energy sources and for integrating them into the power system are identified as priority areas for the development of specialized software in Russia according to the results of the survey of the industry community. The article outlines the priority stages of the creation and implementation of domestic software in the industry: the establishment of mechanisms for prioritizing Russian developments in procurement procedures, margin for error mechanism and accelerated depreciation for imported software and hardware appliances, subject to the obligatory condition of replacing them with domestic software. The results of the paper can be used by the companies in the energy and fuel complex and academia involved in the development of local software products for the needs of the electric power industry.

Using Dynamic Thermal Rating and Energy Storage Systems Technologies Simultaneously for Optimal Integration and Utilization of Renewable Energy Sources

Nowadays, optimal integration and utilization of renewable energy sources (RES) are of the most challenging issues in power systems. The wind and solar generation units' maximum production may or may not occur at peak consumption times resulting in non-optimal utilization of these resources. As a solution to this problem, energy storage systems (ESS) are embedded in networks. However, the power transfer from RES to ESS may lead to network congestion. In this paper, the simultaneous application of dynamic thermal rating (DTR) technology and ESS devices is proposed. The DTR is used to overcome the problem of transmission lines limited capacity and ESS is responsible for mitigating curtailment of RESs energy production by saving their generated energy in non-peak hours. The RESs generation and lines’ ratings are calculated based on hourly actual weather elements. For evaluating the proposed method, a linearized formulation of DC-OPF is used in the problem definition and also simulated on a modified IEEE 30-bus test system including a wind farm, solar park, and ESS devices by using MATLAB software. In addition, different comparisons are performed demonstrating the remarkable and better performance of the proposed method compared to previously introduced methods.

Dynamic Economic Dispatch With Maximal Renewable Penetration Under Renewable Obligation

This paper presents a multi-objective dynamic economic dispatch model with renewable obligation requirements. The two objective functions that are presented in this paper aim to increase the level of renewable energy sources in the grid while minimising the total operating cost and respecting the spinning reserves required to maintain continuity of supply. The proposed model incorporates thermal power plants, photovoltaic and wind power plants into the grid. The paper presents a Pareto optimal solution which is a compromise between maximising the renewable energy source generation while minimising the operating costs. A renewable obligation policy is implemented in the proposed model to ensure that renewable energy source generators are utilised and any failure to attain the required renewable obligation is penalised in line with the renewable obligation framework. The proposed model is modified into a single objective optimisation problem and numerical tests are performed on the modified IEEE 24 RTS system and IEEE 118 bus system to test the effectiveness of the model. A comparative study evaluates the impact of the proposed model on the traditional dynamic economic dispatch in terms of the achieved renewable energy source penetration level and economic performance. The numerical simulations show that the proposed model is robust and can attain high renewable energy source penetration levels.

Deep Reinforcement Learning for Cybersecurity Assessment of Wind Integrated Power Systems

The integration of renewable energy sources (RES) is rapidly increasing in electric power systems (EPS). While the inclusion of intermittent RES coupled with the wide-scale deployment of communication and sensing devices is important towards a fully smart grid, it has also expanded the cyber-threat landscape, effectively making power systems vulnerable to cyberattacks. This article proposes a cybersecurity assessment approach designed to assess the cyberphysical security of EPS. The work takes into consideration the intermittent generation of RES, vulnerabilities introduced by microprocessor-based electronic information and operational technology (IT/OT) devices, and contingency analysis results. The proposed approach utilizes deep reinforcement learning (DRL) and an adapted Common Vulnerability Scoring System (CVSS) score tailored to assess vulnerabilities in EPS in order to identify the optimal attack transition policy based on $N-2$ contingency results, i.e., the simultaneous failure of two system elements. The effectiveness of the work is validated via numerical and real-time simulation experiments performed on literature-based power grid test cases. The results demonstrate how the proposed method based on deep $Q$ -network ($\text{D}Q\text{N}$ ) performs closely to a graph-search approach in terms of the number of transitions needed to find the optimal attack policy, without the need for full observation of the system. In addition, the experiments present the method's scalability by showcasing the number of transitions needed to find the optimal attack transition policy in a large system such as the Polish 2383 bus test system. The results exhibit how the proposed approach requires one order of magnitude fewer transitions when compared to a random transition policy.

MAPCAST: an Adaptive Control Approach using Predictive Analytics for Energy Balance in Micro-Grid Systems

Control approaches for micro-grid (MG) systems are recently developed for efficient energy management in distributed systems. The aim is to increase the integration of renewable energy sources (RES) in buildings while keeping optimal operational conditions of storage devices. However, the variability and the unpredictable behavior of the power produced by RESs require the use of energy management systems and adaptive control strategies for their seamless integration within the traditional electric grid. In this paper, a model predictive control (MPC) strategy is developed, named MAPCAST, for measuring, analyzing, predicting, and forecasting actions in order to ensure efficient and optimal operation of MG systems. The control strategy is based on machine-learning algorithms to predict main parameter inputs, which are used for forecasting suitable actions. Its main objective is to manage the batteries' charge/discharge (C/D) currents, and consequently, the battery state of charge (SoC), taking into consideration the variable nature of RES generation and loads demand satisfaction. A real data-set was gathered from our actual MG system using an IoT/Big-Data platform, which was deployed to measure the different input control parameters. Simulation results are presented to show the utility of the proposed control strategy for efficient operation and optimal energy balance in MG systems.

SMART energy communities: a case study for Greece

In this study, the authors investigate the economic feasibility of an energy community investing in renewable energy sources (RES). The estimation is based on the optimisation of the total annual average electricity costs of a typical study case that uses historical load and RES generation data and follows the directives of the Greek recent legislation for energy communities. The operation of a local energy market is compared with other available RES pricing mechanisms, such as self-consumption, feed-in-tariff and net metering.

Balancing Generation from Renewable Energy Sources: Profitability of an Energy Trader

Motivated by a practical problem faced by an energy trading company in Poland, we investigate the profitability of balancing intermittent generation from renewable energy sources (RES). We consider a company that buys electricity generated by a pool of wind farms and pays their owners the day-ahead system price minus a commission, then sells the actually generated volume in the day-ahead and balancing markets. We evaluate the profitability (measured by the Sharpe ratio) and market risk faced by the energy trader as a function of the commission charged and the adopted trading strategy. We show that publicly available, country-wide RES generation forecasts can be significantly improved using a relatively simple regression model and that trading on this information yields significantly higher profits for the company. Moreover, we address the issue of contract design as a key performance driver. We argue that by offering tolerance range contracts, which transfer some of the risk to wind farm owners, both parties can bilaterally agree on a suitable framework that meets individual risk appetite and profitability expectations.

Artificial Photosynthesis with Titania Photocatalysts

Increasing energy demand and global warming due to extensive use of fossil fuels will soon force mankind to use clean and sustainable fuels and artificial photosynthesis is being considered as a promising solution to both problems. Photocatalysis is a light induced process involved in artificial photosynthesis and it will make a great contribution to the solution of environmental problems and generation of renewable energy sources. Titania based photocatalytic materials are one of the widely used materials in artificial photosynthesis research due to their unique chemical and optical properties. Recent research have shown that the activity of titania phases can be improved in the visible light region by several modification techniques. This paper aims to present a brief review based on the last 2 decades of global research on the preparation and modification of titania based photocatalysts, their application and importance in artificial photosynthesis and its effect on reducing global warming by generating a sustainable energy source. This review is mostly based on the PhD thesis of the corresponding author (Yurtsever, 2015).

Kilka uwag o Internetowej Platformie Aukcyjnej umożliwiającej uzyskanie wsparcia w zakresie odnawialnych źródeł energii w kontekście podpisów elektronicznych

The paper describes certain basic principles of the new system of supporting renewable energy sources (RES) introduced in Poland. The amended Polish Act on Renewable Energy Sources (Polish RES Act) has introduced an auction system which is a new legal instrument enabling the selection of RES generators with adequate fi nancial support. Each Renewable Energy Sources project (RES plant project) to generate and sell electricity must go offi cially through an auction. The Internet Auction Platform is an IT tool used in the process. It en ables to conduct the pre-qualifi cation procedure as well as to prepare the auction off er. This new solution has entailed certain legal issues that must be addressed such as the access to the IT system, electronic submission of tenders or the use of an electronic signature to confi rm the statements made in the electronic procedure. All these issues have been discussed in this paper. The paper also contains an analysis of the diff erences between two possible forms of electronic signature that may be used in the process, and identifi es the main advantages and disadvantages of either. It is then concluded that although the online RES auction could be more competitive, in the version as it is it allows to carry out an eff ective auction.

Independent Component Analysis and Sophisticated Distribution Control Algorithmsbased Improving the Efficecny of Solar Power Generation

Today, people are increasingly worried about environmental problems due to fuel shortage and generation of renewable energy sources. Among the renewable resources, wind generators and photovoltaic panels are primary competitors. For most of their applications, they have the advantages of having a load interface with different power converter circuits for maintenance and free of contamination, but their installation costs are high. Normally Photovoltaic modules also have relatively low conversion efficiency and Overall system cost of PV using Maximum Power Point Tracking (MPPT) techniques are high. The volume can be reduced by the use of high-performance power conditioners that allow for maximum energy consumption. Existing solar power generation systems have some disadvantages of being all day as a result of less direct exposure to true sunlight. This work is aimed at exploring the functions of a MPPT system that includes installations of sophisticated distribution control (SDC) and Independent Component Analysis (ICA) methods. The duty cycle of power converter is significantly controlled using proposed SDC and ICA algorithms and guarantee MPPT operation at its highest efficiency. The function of proposed ICA and SDC has been compared with widely used in traditional algorithms in the MATLAB Simulink environment. Over 97% of capacity is achieved through the respective SDC and ICA methods.

Network partitioning in coherent areas of static voltage stability applied to security region enhancement

The increasing penetration of variable renewable energy sources (RESs) is introducing critical challenges to the power system operation. In this perspective, this paper proposes a novel method for the improvement of the static security region (SSR) based on a new network partitioning algorithm. The proposed algorithm focuses on modern power systems with high penetration of variable RESs generation. It divides the power system in coherence areas according to its criticality mapping. To this end, each bus is assigned a criticality index from the potential energy function, whereas this calculation is based on the data of the wide-area measurement system (WAMS) using phasor measurement unit (PMU). Afterwards, the obtained coherence areas are employed to adaptively determine the generators groups applied to the system SSR assessment in the short-term horizon. To validate the proposed approach, several cases studies are conducted on the IEEE 118-bus system. The results demonstrate the potential of the proposed methodology in the SSR improvement.

Data Centers as Active Multi-Energy Systems for Power Grid Decarbonization: A Technical and Economic Analysis

Power system decarbonization will be one of the main challenges confronting society over the next twenty to thirty years. Renewable energy sources (RES), such as wind and solar, will be the main resources supplying the power grid. Given their volatility, their integration into the grid necessitates planning and utilizing new flexibility options. Energy storage systems (ESS), multi-energy systems and active consumer involvement are three solutions attracting the scientific community’s attention. Data centers (DCs) provide a very high degree of flexibility for consumers. They can be utilized to support system operators or integrate power generated by locally installed renewable energy source generators in the DC’s network. This study is intended to contribute by developing a methodology for planning new flexibility options in DCs. The methodology developed treats DCs as active multi-energy systems. Control strategies were also developed. The technical and economic performance of the solutions implemented was evaluated.

Optimization of a multiple-scale renewable energy-based virtual power plant in the UK

Commercial Virtual Power Plants (CVPPs) have recently emerged as one of the most promising solutions for enabling intermittent renewable energy generation sources to efficiently trade the energy they generate in the electricity market. In this study, we develop several optimization and forecasting methods, and apply them to model the operation of multiple renewable generators across Scotland, trading energy as a single CVPP. The aim of the techniques developed is to optimize the scheduling of the CVPP, such as to maximize revenues and reduce the penalties resulting from forecasting errors, while considering operational and market constraints, such as variable costs, ramping rates, start-up costs, day-ahead and imbalance prices. The practical application is based on a case study of operational renewable energy plants in Scotland, and optimizes the CVPP operation for 3 months in winter and summer of 2017, respectively. Renewable generation output, day-ahead prices and imbalance prices are obtained from historical data for the same year. The numerical results show a profit increase of around 12% for the CVPP compared to standalone operation of renewable plants. This increase is observed for different market and imbalance settlement strategies.

From Rio to Paris via Kyoto: How the Efforts to Protect the Global Climate Affect the World Energy Development

The aims of this work are to analyze the changes in the world power industry during the time after the adoption of the United Nations Framework Convention on Climate Change of 1992 and to assess the extent to which the commitments of the Kyoto Protocol of 1997 have been met and evaluate the prospects of implementing the tasks of the Paris Agreement of 2015. Based on data on the production and consumption of various kinds of energy and the emissions of greenhouse gases, primarily carbon dioxide, in 1990–2017, changes in the structure of the global energy consumption, trends in electric power generation, and the influence of different factors on the carbon dioxide emissions in power-generating enterprises are investigated. It is shown that the power industry, which is the main source of anthropogenic greenhouse gases (GHGs), is the most inertial branch of the economy in terms of its contribution to the reduction in GHG emissions. Thus, in the first 2008–2012 commitment period of the Kyoto Protocol, GHG emissions in the state parties to the protocol decreased by 7.6% compared the base year, while other GHG sources reduced the emission by 18%. The corresponding figures for the following 2013–2017 commitment period were 10.6 and 17.1%, respectively. The maximum reduction in the carbon dioxide emissions in the power industry resulted from an increase in the global average efficiency of the thermal power stations from 32% in 1990 to 36% in 2017; as a consequence, the cumulative decrease in the CO2 emissions in the world during the 1990–2017 period was approximately 22 billion t. The increase in the electric power generation at HPPs and NPPs resulted in a reduction in GHG emissions by 16.7 and 10.7 billion t, respectively. The substitution of coal and fuel oil by gas at thermal power stations facilitated reducing the emissions by 5.2 billion t, while the use of renewable energy sources for generation of electric energy resulted in a reduction of 1.1 billion t. The contribution of the carbon capture and storage technologies amounting to only 0.2 billion t is not noticeable so far.

Guest Editorial Introduction to the Special Section on Transactive Approaches to Integration of Flexible Demand and Distributed Generation

The papers in this special section examine transactive approaches to the integration of flexible demand and distributed generation. Electricity as a sustainable energy carrier plays a central role in themost effective transition scenarios towards a sustainable energy system. To harness this potential, the current electricity infrastructure needs to be rigorously reengineered into an integrated and intelligent electricity system: the smart grid. In the future grid, demand response and response from distributed generation and storage is expected to be used on a large scale to perform active management of distribution grids and to balance the fluctuating power generation of renewable energy sources. Key elements of the smart grid vision are the coordination mechanisms. Through these, vast numbers of devices, currently just passively connected to the grid, will become actively involved in system-wide and local coordination tasks. In this light, market-based, transactive approaches are emerging as strong contenders for orchestrating the coordinated operation of so many devices.