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.

Gaussian PI Controller Network Classifier for Grid-Connected Renewable Energy System

Multi-port converters are considered as exceeding earlier period decade owing to function in a combination of different energy sources in a single processing unit.Renewable energy sources are playing a significant role in the modern energy system with rapid development.In renewable sources like fuel combustion and solar energy,the generated voltages change due to their environmental changes.To develop energy resources,electric power generation involved huge awareness.The power and output voltages are plays important role in our work but it not considered in the existing system.For considering the power and voltage,Gaussian PI Controller-Maxpooling Deep Convolutional Neural Network Classifier(GPIC-MDCNNC)Model is introduced for the grid-connected renewable energy system.The input information is collected from two input sources.After that,input layer transfer information to hidden layer 1 fuzzy PI is employed for controlling voltage in GPIC-MDCNNC Model.Hidden layer 1 is transferred to hidden layer 2.Gaussian activation is employed for determining the output voltage with help of the controller.At last,the output layer offers the last value in GPIC-MDCNNC Model.The designed method was confirmed using one and multiple sources by stable and unpredictable input voltages.GPIC-MDCNNC Model increases the performance of grid-connected renewable energy systems by enhanced voltage value compared with state-of-the-art works.The control technique using GPIC-MDCNNC Model increases the dynamics of hybrid energy systems connected to the grid.

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.

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.

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..

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.

Load Frequency Control of Multi-interconnected Renewable Energy Plants Using Multi-Verse Optimizer

A reliable approach based on a multi-verse optimization algorithm(MVO)for designing load frequency control incorporated in multi-interconnected power system comprising wind power and photovoltaic(PV)plants is presented in this paper.It has been applied for optimizing the control parameters of the load frequency controller(LFC)of the multi-source power system(MSPS).The MSPS includes thermal,gas,and hydro power plants for energy generation.Moreover,the MSPS is integrated with renewable energy sources(RES).The MVO algorithm is applied to acquire the ideal parameters of the controller for controlling a single area and a multi-area MSPS integrated with RES.HVDC link is utilized in shunt with AC multi-areas interconnection tie line.The proposed scheme has achieved robust performance against the disturbance in loading conditions,variation of system parameters,and size of step load perturbation(SLP).Meanwhile,the simulation outcomes showed a good dynamic performance of the proposed controller.

Our Daily Life Dependency Driven by Renewable and Nonrenewable Source of Energy

Our dependency on energy is so vital that it makes it difficult to imagine how humans can live on our planet earth without it.The demand for electricity,for example,is directly related to the growth of the population worldwide,and presently,to meet this demand,we need both renewable and nonrenewable energy.While nonrenewable energy has its shortcomings(negative impact on climate change,for example),renewable energy is not enough to address the ever-changing demand for energy.One way to address this need is to become more innovative,use technology more effectively,and be aware of the costs associated with different sources of renewable energy.In the case of nuclear power plants,new innovative centered around small modular reactors(SMRs)of generation 4th of these plants make them safer and less costly to own them as well as to protect them via means of cyber-security against any attack by smart malware.Of course,understanding the risks and how to address them is an integral part of the study.Natural sources of energy,such as wind and solar,are suggesting other innovating technical approaches.In this article,we are studying these factors holistically,and details have been laid out in a book by the authors’second volume of series title as Knowledge Is Power in Four Dimensions under Energy subtitle.

Transforming Waste Heat into“Renewable Heat”

Introduction:The current worldwide electric power&heat&cool production has a negative impact on the environment by emissions and enormous leaks of low-potential waste heat.Transformation of unused industrial low power heat into“renewable heat”useful to enhance the efficiency of the system is essential and actual innovation in the field of worldwide environmental protection.By introducing and defining the terminology of low-potential,“renewable”,“green heat”has created a new,parallel category of research in the energy sector.Traditional co-generation systems produce heat for space heating and hot water and generate electricity.Moving to tri-generation allows growing demand for air conditioning for homes,offices and commercial spaces such as server rooms and switchboards to be met simultaneously or on a seasonal basis.Tri-generation,or combined cooling,heat and power,is the process by which some of the heat produced by a co-generation plant is used to generate chilled water for air conditioning or refrigeration.Usually an absorption chiller is linked to the plant to provide this functionality.The technical solution is related to the new efficient manner and system of simultaneous generation of heat/cold from multiple heat sources,which has not yet been known,but in practice required.New system also enables advantageous utilization of solar power in supporting of the cooling output.The innovative system can be operated also within the existing central heating distribution systems.

Geothermal Energy--Network of Geoplutonic Power Plants

The article presents the concept of a network of geoplutonic power plants,the total capacity of which would correspond to the general energy needs of the entire region.A scenario of a regional economy is presented,provided with electricity produced from a clean source,without pollutant emissions.Thus,a vision of solving the energy crisis resulting from the planned elimination of fossil energy sources is presented.Such an opportunity appeared after solving the technological problems of deep drilling,exceeding 10 km.The new technology involves extracting heat from HDRs(Hot Dry Rocks)and heating the fluid circulating in a pipe in a closed circuit.The temperature at a depth of 10 km is determined by the regional geothermal gradient.Temperature is in the range of 200-400°C.This is already a zone of degassing magmatic solutions and exothermic chemical reactions.In general,it can be argued that the heat flux density is a function of the distance from magmatic intrusions.

Impact of Renewable Energy Sources on Steady-state Stability of Weak AC/DC Systems

In recent years,the penetration of renewable resources into AC power systems has increased tremendously,creating a significantly impact on the latter’s operations and stability.In this respect,it is also important to gain a basic analytical understanding of such impact on the steady-state stability of power systems with electrically weak AC/DC interconnections,but such works are not very evident in the literature.Therefore,a classical analytic model of the single and multi-infeed HVDC system which now incorporates renewable resources is proposed.Then the well-established concept of voltage sensitivity of the AC/DC interconnection is applied to analyze the impact of the renewable resources on the steady-state stability of these composite system models,as well as on the influence of system conditions and parameters.This impact is also compared with that arising from other types of shunt devices alternatively connected at the same AC/DC interconnection,therefore their relative beneficial or negative impacts will also be benchmarked.

Application of Life-Cycle Assessment for the Study of Carbon and Water Footprints of the 16.5 MWe Wind Farm in Villonaco, Loja, Ecuador

Wind technology is considered to be among the most promising types of renewable energy sources, and due to high oil prices and growing concerns about climate change and energy security, it has been the subject of extensive considerations in recent years, including questions related to the relative sustainability of electricity production when the manufacturing, assembly, transportation and dismantling processes of these facilities are taken into account. The present article evaluates the environmental impacts, carbon emissions and water consumption, derived from the production of electric energy of the Villonaco wind farm, located in Loja, Ecuador, during its entire life cycle, using the Life Cycle Analysis for this purpose. Finally, it is concluded that wind energy has greater environmental advantages since it has lower values of carbon and water footprints than other energy sources. Additionally, with the techniques Cumulative Energy Demand and Energy Return on Investment, sustainability in the production of electricity from wind power in Ecuador is demonstrated;and, that due to issues of vulnerability to climate change, the diversification of its energy mix is essential considering the inclusion of non-conventional renewable sources such as solar or wind, this being the only way to reduce both the carbon footprint and the water from the energy supply.

Protection Challenges Under Bulk Penetration of Renewable Energy Resources in Power Systems:A Review

Among different sources of alternate energy,wind and solar are two prominent and promising alternatives to meet the future electricity needs for mankind.Generally,these sources are integrated at the distribution utilities to supply the local distribution customers.If the power generated by these sources is bulk,then they are either integrated at the distribution/transmission level or may be operated in an island mode if feasible.The integration of these renewables in the power network will change the fault level and network topologies.These fault levels are intermittent in nature and existing protection schemes may fail to operate because of their pre-set condition.Therefore,the design and selection of a proper protection scheme is very much essential for reliable control and operation of renewable integrated power systems.Depending upon the level of infeed and location of the renewable integration,the protection requirements are different.For low renewable infeed at the distribution level,the existing relay settings are immune from any small change in the network fault current from new incoming renewables.However,bulk renewable infeed requires modification in the existing protection schemes to accommodate the fault current variation from the incoming renewables.For bulk penetration of the renewable,the requirement of modified/additional protection schemes is unavoidable.Adaptive relaying and non-adaptive relaying schemes are discussed in the literature for protection of power networks,which are experiencing dynamic fault currents and frequent changing network topologies.This article presents a detailed review of protection schemes for renewable integrated power networks which includes distribution,transmission and microgrid systems.The merits and demerits of these protection schemes are also identified in this article for the added interest of the readers.The visible scope of advance protection schemes which may be suitable for providing reliable protection for dynamic fault current networks is also explored.

Frequency-based control of islanded microgrid with renewable energy sources and energy storage

When a microgrid is mainly supplied by renewable energy sources(RESs), the frequency deviations may deteriorate significantly the power quality delivered to the loads. This paper proposes a frequency-based control strategy, ensuring the frequency among the strict limits imposed by the Standard EN 50160. The frequency of the microgrid common AC bus is determined by the energy storage converter, implementing a proposed droop curve among the state of charge(SoC) of the battery and the frequency. Therefore, the information of the SoC becomes known to every distributed energy resource(DER) of the microgrid and determines the active power injection of the converter-interfaced DERs. The active power injection of the rotating generators remains unaffected, while any mismatch among the power generation and consumption is absorbed by the energy storage system. Finally, in case of a solid short-circuit within the microgrid, the energy storage system detects the severe voltage decrease and injects a large current in order to clear the fault by activating the protection device closer to the fault. The proposed control methodology is applied in a microgrid with PVs, wind generators and a battery, while its effectiveness is evaluated by detailed simulation tests.

Distributed generator-based distribution system service restoration strategy and model-free control methods

The rapid growth of distributed generator(DG)capacities has introduced additional controllable assets to improve the performance of distribution systems in terms of service restoration.Renewable DGs are of particular interest to utility companies,but the stochastic nature of intermittent renewable DGs could have a negative impact on the electric grid if they are not properly handled.In this study,we investigate distribution system service restoration using DGs as the primary power source,and we develop an effective approach to handle the uncertainty of renewable DGs under extreme conditions.The distribution system service restoration problem can be described as a mixed-integer second-order cone programming model by modifying the radial topology constraints and power flow equations.The uncertainty of renewable DGs will be modeled using a chance-constrained approach.Furthermore,the forecast errors and noises in real-time operation are solved using a novel model-free control algorithm that can automatically track the trajectory of real-time DG output.The proposed service restoration strategy and model-free control algorithm are validated using an IEEE 123-bus test system.

KPI-based Real-time Situational Awareness for Power Systems with a High Proportion of Renewable Energy Sources

With the increasing complexity of power systems and the widespread penetration of renewable energy sources(RES),real-time situational awareness for power systems is of great significance for operational scheduling.Considering the impact of RES on power system operations,a situational awareness key performance index(KPI)system for power systems with a high proportion of RES is proposed in this paper,which consists of reserve capacity abundance,ramp resource abundance,center of inertia(COI)frequency deviation,interface power flow margin,synthesized voltage stability,and angle stability margin.Then,the KPIs are synthesized and visualized by the decision tree method and radar chart method,respectively,for monitoring the operation states(i.e,normal,alert,and emergency states)of power systems with a high proportion of RES.Numerical simulations are conducted in a revised New England 16-machine 68-bus power system and an actual CEPRI-RE power system in the northwest region of China with a high proportion of RES.The results show that the proposed KPI-based situational awareness method is able to accurately monitor the real-time state of power systems with a high proportion of RES,and can assist power dispatchers to make effective decisions.

Research on power-supply cost of regional power system under carbon-peak target

With the establishment of the carbon-peak target by 2030,the direction of carbon emission reduction in China’s energy system has been further clarified.As the industry with the largest proportion of carbon emissions in China,the lowcarbon transformation of the electric power industry is critical to realize the carbon-peak target.Current research mostly focuses on technical analysis or system cost accounting of the carbon-peak realization path at the national level.There is a lack of targeted research on regional power systems with complex inter-regional power flow exchange and limited energy resource development.Simultaneously,the calculation of the system cost lacks the perspective of the life cycle and ignores the inertia of the stock and change inertia of incremental disturbance.From the perspective of the life cycle,this study proposes a calculation model of power supply cost for regional power systems according to the carbon-peak target,analyzes the realization path of the carbon target from an economic perspective,and provides references for the path selection and policy formulation of system transformation.

Controlled Islanding Strategy Considering Uncertainty of Renewable Energy Sources Based on Chance-constrained Model

Controlled islanding plays an essential role in preventing the blackout of power systems.Although there are several studies on this topic in the past,no enough attention is paid to the uncertainty brought by renewable energy sources(RESs)that may cause unpredictable unbalanced power and the observabilit>T of power systems after islanding that is essential for back-up black-start measures.Therefore,a novel controlled islanding model based on mixed-integer second-order cone and chance-constrained programming(MISOCCP)is proposed to address these issues.First,the uncertainty of RESs is characterized by their possibility distribution models with chance constraints,and the requirements,e.g.,system observability,for rapid back-up black-start measures are also considered.Then,a law of large numbers(LLN)based method is em-ployed for converting the chance constraints into deterministic ones and reformulating the non-convex model into convex one.Finally,case studies on the revised IEEE 39-bus and 118-bus power systems as well as the comparisons among different models are given to demonstrate the effectiveness of the proposed model.The results show that the proposed model can result in less unbalanced power and better observability after islanding compared with other models.

Adaptive coordination control strategy of renewable energy sources,hydrogen production unit,and fuel celi for frequency regulation of a hybrid distributed power system

Owing to the significant number of hybrid generation systems(HGSs)containing various energy sources,coordina-tion between these sources plays a vital role in preserving frequency stability.In this paper,an adaptive coordination control strategy for renewable energy sources(RESs),an aqua electrolyzer(AE)for hydrogen production,and a fuel cell(FC)-based energy storage system(ESS)is proposed to enhance the frequency stability of an HGS.In the proposed system,the excess energy from RESs is used to power electrolysis via an AE for hydrogen energy storage in FCs.The proposed method is based on a proportional-integral(Pl)controller,which is optimally designed using a grey wolf optimization(GWO)algorithm to estimate the surplus energy from RESs(ie,a proportion of total power generation of RESs:Kn).The studied HGS contains various types of generation systems including a diesel generator,wind tur-bines,photovoltaic(PV)systems,AE with FCs,and ESSs(e.g.,battery and flywheel).The proposed method varies Kn with varying frequency deviation values to obtain the best benefits from RESs,while damping the frequency fluc-tuations.The proposed method is validated by considering different loading conditions and comparing with other existing studies that consider Kn as a constant value.The simulation results demonstrate that the proposed method,which changes Kn value and subsequently stores the power extracted from the RESs in hydrogen energy storage according to frequency deviation changes,performs better than those that use constant Kn.The statistical analysis for frequency deviation of HGS with the proposed method has the best values and achieves large improvements for minimum,maximum,difference between maximum and minimum,mean,and standard deviation compared to the existing method.

Jaya Learning-Based Optimization for Optimal Sizing of Stand-Alone Photovoltaic,Wind Turbine,and Battery Systems

Renewable energy sources(RESs)are considered to be reliable and green electric power generation sources.Photovoltaics(PVs)and wind turbines(WTs)are used to provide electricity in remote areas.Optimal sizing of hybrid RESs is a vital challenge in a stand-alone environment.The meta-heuristic algorithms proposed in the past are dependent on algorithm-specific parameters for achieving an optimal solution.This paper proposes a hybrid algorithm of Jaya and a teaching–learning-based optimization(TLBO)named the JLBO algorithm for the optimal unit sizing of a PV–WT–battery hybrid system to satisfy the consumer’s load at minimal total annual cost(TAC).The reliability of the system is considered by a maximum allowable loss of power supply probability(LPSPmax)concept.The results obtained from the JLBO algorithm are compared with the original Jaya,TLBO,and genetic algorithms.The JLBO results show superior performance in terms of TAC,and the PV–WT–battery hybrid system is found to be the most economical scenario.This system provides a cost-effective solution for all proposed LPSPmax values as compared with PV–battery and WT–battery systems.