Enhancing Renewable Energy Integration:A Gaussian-Bare-Bones Levy Cheetah Optimization Approach to Optimal Power Flow in Electrical Networks

In the contemporary era,the global expansion of electrical grids is propelled by various renewable energy sources(RESs).Efficient integration of stochastic RESs and optimal power flow(OPF)management are critical for network optimization.This study introduces an innovative solution,the Gaussian Bare-Bones Levy Cheetah Optimizer(GBBLCO),addressing OPF challenges in power generation systems with stochastic RESs.The primary objective is to minimize the total operating costs of RESs,considering four functions:overall operating costs,voltage deviation management,emissions reduction,voltage stability index(VSI)and power loss mitigation.Additionally,a carbon tax is included in the objective function to reduce carbon emissions.Thorough scrutiny,using modified IEEE 30-bus and IEEE 118-bus systems,validates GBBLCO’s superior performance in achieving optimal solutions.Simulation results demonstrate GBBLCO’s efficacy in six optimization scenarios:total cost with valve point effects,total cost with emission and carbon tax,total cost with prohibited operating zones,active power loss optimization,voltage deviation optimization and enhancing voltage stability index(VSI).GBBLCO outperforms conventional techniques in each scenario,showcasing rapid convergence and superior solution quality.Notably,GBBLCO navigates complexities introduced by valve point effects,adapts to environmental constraints,optimizes costs while considering prohibited operating zones,minimizes active power losses,and optimizes voltage deviation by enhancing the voltage stability index(VSI)effectively.This research significantly contributes to advancing OPF,emphasizing GBBLCO’s improved global search capabilities and ability to address challenges related to local minima.GBBLCO emerges as a versatile and robust optimization tool for diverse challenges in power systems,offering a promising solution for the evolving needs of renewable energy-integrated power grids.

Predictive Multimodal Deep Learning-Based Sustainable Renewable and Non-Renewable Energy Utilization

Recently,renewable energy(RE)has become popular due to its benefits,such as being inexpensive,low-carbon,ecologically friendly,steady,and reliable.The RE sources are gradually combined with non-renewable energy(NRE)sources into electric grids to satisfy energy demands.Since energy utilization is highly related to national energy policy,energy prediction using artificial intelligence(AI)and deep learning(DL)based models can be employed for energy prediction on RE and NRE power resources.Predicting energy consumption of RE and NRE sources using effective models becomes necessary.With this motivation,this study presents a new multimodal fusionbased predictive tool for energy consumption prediction(MDLFM-ECP)of RE and NRE power sources.Actual data may influence the prediction performance of the results in prediction approaches.The proposed MDLFMECP technique involves pre-processing,fusion-based prediction,and hyperparameter optimization.In addition,the MDLFM-ECP technique involves the fusion of four deep learning(DL)models,namely long short-termmemory(LSTM),bidirectional LSTM(Bi-LSTM),deep belief network(DBN),and gated recurrent unit(GRU).Moreover,the chaotic cat swarm optimization(CCSO)algorithm is applied to tune the hyperparameters of the DL models.The design of the CCSO algorithm for optimal hyperparameter tuning of the DL models,showing the novelty of the work.A series of simulations took place to validate the superior performance of the proposed method,and the simulation outcome emphasized the improved results of the MDLFM-ECP technique over the recent approaches with minimum overall mean absolute percentage error of 3.58%.

Renewable Energy Seawater Desalination Technology and Application Analysis

This paper proposed a new technology way for seawater desalination which used renewable energy(wind energy and solar energy).The effects of practical application showed that remote islands and cage culture zones in the bay that lack electricity and water are very suitable for using small seawater desalination devices that do not require consumption of conventional energy.

Artificial Intelligence Integration with Energy Sources (Renewable and Non-renewable)

In the past decade or so,AI(artificial intelligence)technology has been growing with such a mesmerizing speed that today its presence in almost any industry that deals with any huge sheer volume of data is taking advantage of AI by integrating it into their day-to-day operation.Meanwhile,seven billion people worldwide shape the world’s energy system and directly impact the fundamental drivers of energy,both renewable and non-renewable sources,to meet the demand for electricity from them.These energy sources can be reached from nature such as solar,wind,etc.,and human-made such as NPPs(nuclear power plants)in the form of either fission as an old technology since the Manhattan project and in the near future as fusion in the form of magnetic or inertial confinements.Meanwhile,AI controlling nuclear reactors are about to happen.The basic idea is to apply AI with its two subset components as ML(machine learning),and DL(deep learning)techniques to go through the mountains of data that come from a reactor,spot patterns in it,and calling them to the unit’s human attention operators is not invadable either.Designers of such nuclear reactors will combine simulation and real-world data,comparing scenarios from each to develop“confidence[in]what they can predict and what is the range of uncertainty of their prediction”.Adding that,in the end,the operator will make the final decisions in order to keep these power plants safe while they are in operation and how to secure them against cyber-attack natural or human-made disasters.In this short communication article,we would like to see how we can prove some of these concepts;then a NPP manufacturer can pick it up and use it in their designs of a new generation of these reactors.

Study on Ecological Compensation Policy among the Micro Subjects on Water Energy Resources Development

The subjects of ecological compensation involve the nation, society, development enterprises of wa-ter-energy resources, as well as the location of resource itself. This paper systematically studies on how to make “water energy sources market compensation policy”, “the economic compensation policy for relevant interest subjects” and “the ecological compensation policy of basin ecological water.” So, it is necessary to exert the complementary function between market compensation and government compensation by the means of economic compensation and to establish the ecological compensation policy of basin ecological water, which is beneficial to coordinating the stakeholders’ interests of cross-region or inter-basin. And it is important and significant to establish constantly perfected ecological compensation policy among the micro subjects on water energy resources development, so as to coordinate interest relationships among various subjects and finally reach the aim of sustainable use of water energy resources and environmental protection as possible.

Energy Storage Systems Technologies, Evolution and Applications

Energy in its varied forms and applications has become the main driver of today’s modern society. However, recent changes in power demand and climatic changes (decarbonization policy) has awakened the need to rethink through the current energy generating and distribution system. This led to the exploration of other energy sources of which renewable energy (like thermal, solar and wind energy) is fast becoming an integral part of most energy system. However, this innovative and promising energy source is highly unreliable in maintaining a constant peak power that matches demand. Energy storage systems have thus been highlighted as a solution in managing such imbalances and maintaining the stability of supply. Energy storage technologies absorb and store energy, and release it on demand. This includes gravitational potential energy (pumped hydroelectric), chemical energy (batteries), kinetic energy (flywheels or compressed air), and energy in the form of electrical (capacitors) and magnetic fields. This paper provides a detailed and comprehensive overview of some of the state-of-the-art energy storage technologies, its evolution, classification, and comparison along with various area of applications. Also highlighted in this paper is a plethora of power electronic Interface technologies that plays a significant role in enabling optimum performance and utilization of energy storage systems in different areas of application.

Method for Determination of Optimal Installed Capacity of Renewable Sources of Energy by the Criterion of Minimum Losses of Active Power in Distribution System

New method for determination of optimal placement and value of installed capacity of renewable source of energy (RES) by the criterion of minimum losses of active power, that allows taking into consideration the dependence of RES on natural conditions of region, schedule of energy supply, parameters and configuration of distribution network is suggested in the paper. Results of computations of test scheme confirm the efficiency of the proposed method and its simplicity as compared with the methods considered in literature sources.

An Approach for Cost-Efficient Grid Integration of Distributed Renewable Energy Sources

We describe a specific approach to capacity man a ge ment for distribution grids. Based on simulations, it has been found that by curtailing a maximum of 5% of the yearly energy production on a per-generator basis, distribution grid connection capacity can be doubled. We also present the setting and fi rst results of a fi eld test for validating the approach in a rural distribution grid in northern Germany.

Cost Optimization Modeling of Renewable Energy Sources in Smart-Grid Using SCADA

In recent times, renewable energy production from renewable energy sources is an alternative way to fulfill the increased energy demands. However, the increasing energy demand rate places more pressure, leading to the termination of conventional energy resources. However, the cost of power generation from coal-fired plants is higher than the power generation’s price from renewable energy sources. This experiment is focused on cost optimization during power generation through pumped storage power plant and wind power plant. The entire modeling of cost optimization has been conducted in two parts. The mathematical modeling was done using MATLAB simulation while the hydro and wind power plant’s emulation was performed using SCADA (Supervisory control and data acquisition) designer implementation. The experiment was conducted using ranges of generated power from both power sources. The optimum combination of output power and cost from both generators is determined via MATLAB simulation within the assumed generated output power range. Secondly, the hydro-generator and wind generator’s emulation were executed individually through synchronizing the grid to determine each generator’s specification using SCADA designer, which provided the optimum power generation from both generators with the specific speed, aligning with results generated through MATLAB. Finally, the operational power cost (with no losses consideration) from MATLAB was compared with the local energy provider to determine the cost-efficiency. This experiment has provided the operational cost optimization of the hydro-wind combined power system with stable wind power generation using SCADA, which will ultimately assist in operations of large-scale power systems, remotely minimizing multi-area dynamic issues while maximizing the system efficiency.

Economic Factors in the Use of Renewable Energy Sources in Kazakhstan

The purpose of this research was to study economic incentives to use renewable energy sources in the Republic of Kazakhstan and to give suggestions for production and circulation of the ＂green＂ certificates as a new financial instrument. The author analyzed European Union and Kazakhstani experience of economic incentives to reduce emissions and introduction of renewable energy sources. As a result of conducted research, the proposal to produce and circulate new financial instruments in Kazakhstan is made; as well as economic and environmental factors of renewable energy sources in the Republic of Kazakhstan are defined.

Renewable Energy Sources A Promising Opportunity for Remote Mine Sites

Mining industry is a substantial consumer of the energy indispensable to power mining and mineral processing equipment and processes. As more and more mine operations move to remote locations, the access to reliable, secure and environment friendly energy sources becomes a key concern. At present, a great majority of remote mines relies heavily on diesel fuel that has to be transported over long distances. In this context, some of the renewable energy sources such as wind power or solar energy seem to provide potentially interesting and viable alternatives. Mine operations, however, have a very particular character, much different from other industries and from other potential applications of renewable power sources. This paper presents operational conditions of some mining operations, particularly those in remote regions, in the context of their energy needs. The authors analyse current and future capacities to decrease a reliance of remote mines on conventional fuels and energy. The paper also analyses and discusses the conditions to be met by alternative energy sources so that they might become a viable alternative for remote mining operations.

Challenges of Tomorrowm——Fire Hazards of Systems Using Renewable Sources of Energy

Dramatic climate change, caused by over consumption of coal, oil and other traditional energy sources, as well as exhaustion of their reserves, imposed technological need to look for their substitution with new, renewable energy sources. The exploitation of these new forms of energy, solar, wind, earth and bio-fuels, initiated the development and application of new technologies, so far unused in practice. Rapid development and wide application of installations for use of renewable energy in many households and companies opened a whole new risk and danger in the fire protection field. With the purpose of introducing this problem to engineers in the area of fire protection, health and safety at work, this paper systematically presents various types of facilities for exploitation of renewable energy sources as well as potential dangers, risks and issues related to their safe operation.

An Optimization Approach for Unit Commitment of a Power System Integrated with Renewable Energy Sources： A Case Study of Afghanistan

This paper focused on generation scheduling problem with consideration of wind, solar and PHES （pumped hydro energy storage） system. Wind, solar and PHES are being considered in the NEPS （northeast power system） of Afghanistan to schedule all units power output so as to minimize the total operation cost of thermal units plus aggregate imported power tariffs during the scheduling horizon, subject to the system and unit operation constraints. Apart from determining the optimal output power of each unit, this research also involves in deciding the on/off status of thermal units. In order to find the optimal values of the variables, GA （genetic algorithm） is proposed. The algorithm performs efficiently in various sized thermal power system with equivalent wind, solar and PHES and can produce a high-quality solution. Simulation results reveal that with wind, solar and PHES the system is the most-cost effective than the other combinations.

Accelerated Particle Swarm Optimization for Controlling Virtual Power Plant Consisting of Renewable Energy Sources

RES （renewable energy sources）, such as wind and photovoltaic power plants, suffer from their stochastic nature that is why their behavior on market is very delicate. In order to diversify risk, a concept of VPP （virtual power plant） has been developed. The VPP is composed of several RES, from which at least one of them is fully controllable. Because the production of noncontrollable RES can not be forecasted perfectly, therefore an optimal dispatch schedule within VPP is needed. To address this problem, an APSO （accelerated particle swarm optimization） is used to solve the constrained optimal dispatch problem within VPP. The experimental results show that the proposed optimization method provides high quality solutions while meeting constraints.

Finite Set-Model Predictive Current Control of Three-Phase Voltage Source Inverter for RES （Renewable Energy Systems） Applications

This paper focuses on a combination of three-phase VSI （voltage source inverter） with a predictive current control to provide an optimized system for three-phase inverters that control the load current. A FS-MPC （finite set-model predictive control） strategy for a three-phase VSI for RES （renewable energy systems） applications is implemented. The renewable energy systems model is used in this paper to investigate the system performance when power is supplied to resistive-inductive load. With three different cases, the evaluation of the system is done. Firstly, the robustness of control strategy under variable DC-Link is done in terms of the THD （total harmonic distortion）. Secondly, with one prediction step, the system performance is tested using different sampling time, and lastly, the dynamic response of the system with step change in the amplitude of the reference is investigated. The simulations and result analyses are carried out using Matlab/Simulink to test the effectiveness and robustness of FS-MPC for two-level VSI with AC filter for resistive-inductive load supplied by a renewable energy system.

Sizing of Energy Storage Systems for Output Smoothing of Renewable Energy Systems

光伏、风力发电等可再生能源（renewable energysources，RESs）具有随机性、间歇性等特点。为了抑制RESs输出波动对电网的不利影响，提出了用于平滑RESs发电系统功率输出的储能系统（energy storage system，ESS）容量优化确定方法。利用离散傅里叶变换（discrete Fouriertransform，DFT）对RESs输出功率进行频谱分析，基于频谱分析结果，考虑ESS充放电效率、荷电状态（stateofcharge，soc）及RESs发电系统目标功率输出波动率的约束，确定所需ESS最小容量。采用美国华盛顿州实际观测风速数据及日本东北电力公司风电场接入电网20rnin有功功率波动规范（最大波动率为10％），在一风力发电系统中对该方法进行了验证。算例结果表明采用该方法能够以较小的容量将风机输出最大波动率由61．7％降到9．9％。

Exact Box-Constrained Economic Operating Region for Power Grids Considering Renewable Energy Sources

The growing integration of renewable energy sources manifests as an effective strategy for reducing carbon emissions. This paper strives to efficiently approximate the set of optimal scheduling plans(OSPs) to enhance the performance of the steady-state adaptive cruise method(SACM) of power grid, improving the ability of dealing with operational uncertainties. Initially, we provide a mathematical definition of the exact boxconstrained economic operating region(EBC-EOR) for the power grid and its dispatchable components. Following this, we introduce an EBC-EOR formulation algorithm and the corresponding bi-level optimization models designed to explore the economic operating boundaries. In addition, we propose an enhanced big-M method to expedite the computation of the EBCEOR. Finally, the effectiveness of the EBC-EOR formulation, its economic attributes, correlation with the scheduling plan underpinned by model predictive control, and the significant improvement in computational efficiency(over twelvefold) are verified through case studies conducted on two test systems..

Recent Progress and Approaches on Carbon-Free Energy from Water Splitting

Sunlight is the most abundant renewable energy resource,providing the earth with enough power that is capable of taking care of all of humanity’s desires-a hundred times over.However,as it is at times diffuse and intermittent,it raises issues concerning how best to reap this energy and store it for times when the Sun is not shining.With increasing population in the world and modern economic development,there will be an additional increase in energy demand.Devices that use daylight to separate water into individual chemical elements may well be the answer to this issue,as water splitting produces an ideal fuel.If such devices that generate fuel were to become widely adopted,they must be low in cost,both for supplying and operation.Therefore,it is essential to research for cheap technologies for water ripping.This review summarizes the progress made toward such development,the open challenges existing,and the approaches undertaken to generate carbon-free energy through water splitting.

Optimal capacity planning of combined renewable energy source-pumped storage and seawater desalination systems

As water scarcity is becoming a growing threat to human development, finding effective solutions has become an urgent need. To make better use of water resources, seawater desalination and storage systems using renewable energy sources(RES) are designed and implemented around the world. In this paper, an optimal capacity planning method for RES-pumped storage-seawater desalination(RES-PS-D) system is introduced. The configuration of the RES-PS-D system is clarified first, after which a cost-benefit analysis is performed using all cost and benefit components. A function for determining maximum economic benefits of the RES-PS-D system is then established, and the constraints are proposed based on various limitations. The mixed-integer linear programming algorithm is applied to solve the optimal function. A case study is introduced to validate the feasibility and effectiveness of the method. The conclusion shows that the strategy is suitable for solving the configuration optimization problem, and finally both merits and defects of the method are discussed.

Optimal Energy Management for Virtual Power Plant with Renewable Generation

The nature of variable and uncertainty from renewable energy sources (RESs) makes them challenging to be integrated into the main grid separately. A Virtual Power Plant (VPP) is proposed to aggregate the capacities of RESs and facilitate the integration and management in a decentralized manner. In this paper, a novel framework for optimal energy management of VPP considering key features such as handling uncertainties with RESs, reducing operating costs and regulating system voltage levels is proposed, and a two-stage stochastic simulation is formulated to address the uncertainties of RESs generation and electricity prices. Simulation result show that the framework can benefit from ensuring the energy balance and system security, as well as reducing the operation costs.