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.

Assessing the techno-economic feasibility of hybrid solar-hydrogen systems: A review of recent studies

Transition toward a sustainable,low-carbon energy future requires innovative,integrated solutions.Hybrid solar-hydrogen systems(HSHSs),which combine solar energy harvesting and hydrogen production,have excellent prosepects to address challenges related to renewable energy generation,storage,and usage.This article presents an overview of the research on the technical and economic feasibility of HSHSs,aimed at comprehensively articulating their current state,notable advancements,and future research directions.It begins by elucidating solar energy principles and conversion methods and emphasizing the potential of solar energy for hydrogen production.This study then explores the definitions,components,and synergistic integration of HSHSs.Optimized energy conversion and storage methods for efficient hydrogen production and storage are also highlighted.This study reviews the techniques employed for techno-economic evaluations over the last six years,addressing challenges such as the intermittency of solar energy and the efficiency of hydrogen production technologies.This review of the ongoing research provides helpful insights into the technological and economic feasibility of HSHSs.This underscores the necessity of continuous research and development efforts to overcome existing challenges and unlock their full potential.These systems can play a vital role in achieving a cleaner and more resilient energy future by optimizing the system performance,reducing costs,and fostering supportive policy frameworks.

Smart Grids with Intelligent Periphery:An Architecture for the Energy Internet

A future smart grid must fulfill the vision of the Energy Internet in which millions of people produce their own energy from renewables in their homes, offices, and factories and share it with each other. Electric vehicles and local energy storage will be widely deployed. Internet technology will be utilized to transform the power grid into an energysharing inter-grid. To prepare for the future, a smart grid with intelligent periphery, or smart GRIP, is proposed. The building blocks of GRIP architecture are called clusters and include an energy-management system （EMS）-controlled transmission grid in the core and distribution grids, micro-grids, and smart buildings and homes on the periphery; all of which are hierarchically structured. The layered architecture of GRIP allows a seamless transition from the present to the future and plug-and-play interoperability. The basic functions of a cluster consist of （1） dispatch, （2） smoothing, and （3） mitigation. A risk-limiting dispatch methodology is presented; a new device, called the electric spring, is developed for smoothing out fluctuations in periphery clusters; and means to mitigate failures are discussed.

A distributed VSG control method for a battery energy storage system with a cascaded H-bridge in a grid-connected mode

With the high penetration of renewable energy,new challenges,such as power fluctuation suppression and inertial support capability,have arisen in the power sector.Battery energy storage systems play an essential role in renewable energy integration.In this paper,a distributed virtual synchronous generator(VSG)control method for a battery energy storage system(BESS)with a cascaded H-bridge converter in a grid-connected mode is proposed.The VSG is developed without communication dependence,and state-of-charge(SOC)balancing control is achieved using the distributed average algorithm.Owing to the low varying speed of SOC,the bandwidth of the distributed communication networks is extremely slow,which decreases the cost.Therefore,the proposed method can simultaneously provide inertial support and accurate SOC balancing.The stability is also proved using root locus analysis.Finally,simulations under different conditions are carried out to verify the effectiveness of the proposed method.

Engineering practices for the integration of large-scale renewable energy VSC-HVDC systems

With the continuous development of power electronic devices,intelligent control systems,and other technologies,the voltage level and transmission capacity of voltage source converter (VSC)-high-voltage direct current (HVDC) technology will continue to increase,while the system losses and costs will gradually decrease.Therefore,it can be foreseen that VSC-HVDC transmission technology will be more widely applied in future large-scale renewable energy development projects.Adopting VSC-HVDC transmission technology can be used to overcome issues encountered by large-scale renewable energy transmission and integration projects,such as a weak local power grid,lack of support for synchronous power supply,and insufficient accommodation capacity.However,this solution also faces many technical challenges because of the differences between renewable energy and traditional synchronous power generation systems.Based on actual engineering practices that are used worldwide,this article analyzes the technical challenges encountered by integrating large-scale renewable energy systems that adopt the use of VSC-HVDC technology,while aiming to provide support for future research and engineering projects related to VSC-HVDC-based large-scale renewable energy integration projects.

Impact of industrial virtual power plant on renewable energy integration

An industrial park is one of the typical en ergy con sumption schemes in power systems owing to the heavy in dustrial loads and their abilities to resp ond to electricity price cha nges.Therefore,en ergy in tegrati on in the industrial sector is significant.Accordingly,the concept of industrial virtual power plant(IVPP)has been proposed to deal with such problems.This study demonstrates an IVPP model to man age resources in an eco-i ndustrial park,including en ergy storage systems,dema nd resp onse(DR)resources,and distributed energies.In addition,fuzzy theory is used to cha nge the deterministic system constraints to fuzzy parameters,considering the uncertainty of renewable energy,and fuzzy chance constraints are then set based on the credibility theory.By maximizi ng the daily ben efits of the IVPP owners in day-ahead markets,DR and energy storage systems can be scheduled economically.Therefore,the energy between the grid and IVPP can flow in both directions:the surplus renewable electricity of IVPP can be sold in the market;when the electricity gen erated in side IVPP is not enough for its use,IVPP can also purchase power through the market.Case studies based on three win d-level scenarios dem on strate the efficie nt syn ergies betwee n IVPP resources.The validatio n results indicate that IVPP can optimize the supply and demand resources in in dustrial parks,thereby decarbonizing the power systems.

Structured Microgrids (SμGs) and Flexible Electronic Large Power Transformers (FeLPTs)

Structured microgrids(SμGs)and Flexible electronic large power transformers(FeLPTs)are emerging as two essential technologies for renewable energy integration,flexible power transmission,and active control.SμGs provide the integration of renewable energy and storage to balance the energy demand and supply as needed for a given system design.FeLPT’s flexibility for processing,control,and re-configurability offers the capability for flexible transmission for effective flow control and enable SμGs connectivity while still keeping multiscale system level control.Early adaptors for combined heat and power have demonstrated significant economic benefits while reducing environmental foot prints.They bring tremendous benefits to utility companies also.With storage and active control capabilities,a 300-percent increase in bulk transmission and distribution lines are possible without having to increase capacity.SμGs and FeLPTs will also enable the utility industry to be better prepared for the emerging large increase in base load demand from electric transportation and data centers.This is a win-win-win situation for the consumer,the utilities(grid operators),and the environment.SμGs and FeLPTs provide value in power substation,energy surety,reliability,resiliency,and security.It is also shown that the initial cost associated with SμG and FeLPTs deployment can be easily offset with reduced operating cost,which in turn reduces the total life-cycle cost by 33%to 67%.

Optimal Placement of Distribution Generation Sources in Hybrid Generation Network

The ideal places and size of the distribution generators were determined by reducing the loss of power in the distribution networks. The ideal positioning of various kinds of DGs has been suggested in the current job. In this job, the ideal power factor for DG supply has been acquired, both the active power as well as the reactive power. In the proposed approach, different types of distribution generation (DG) supply both reactive and real power. For the optimal placement of DG sources, particle swarm optimization techniques have been used in this job. Each of these innovations has its own strengths and drawbacks. Most of the methods that have been proposed so far to formulate DG’s optimum placement problem only consider Type-I DGs, Type-II and Type-III DGs that are considered for optimal position in the existing research. In the reference, artificial bee colony algorithm was used to determine sites of DGs and condenser combinations and optimal size. The author used PSO method in the reference to determine the appropriate positioning of the DG’s and to maximize the savings of power loss and voltage profile in the distribution network.

Agent-Based Simulation for Interconnection-Scale Renewable Integration and Demand Response Studies

This paper collects and synthesizes the technical requirements, implementation, and validation methods for quasi-steady agent-based simulations of interconnectionscale models with particular attention to the integration of renewable generation and controllable loads. Approaches for modeling aggregated controllable loads are presented and placed in the same control and economic modeling framework as generation resources for interconnection planning studies. Model performance is examined with system parameters that are typical for an interconnection approximately the size of the Western Electricity Coordinating Council(WECC) and a control area about 1/100 the size of the system. These results are used to demonstrate and validate the methods presented.

Impact of interconnections and renewable energy integration on the Philippine-Sabah Power Grid systems

This study presents a comprehensive impact analysis of the rotor angle stability of a proposed international connection between the Philippines and Sabah,Malaysia,as part of the Association of Southeast Asian Nations(ASEAN)Power Grid.This study focuses on modeling and evaluating the dynamic performance of the interconnected system,considering the high penetration of renewable sources.Power flow,small signal stability,and transient stability analyses were conducted to assess the ability of the proposed linked power system models to withstand small and large disturbances,utilizing the Power Systems Analysis Toolbox(PSAT)software in MATLAB.All components used in the model are documented in the PSAT library.Currently,there is a lack of publicly available studies regarding the implementation of this specific system.Additionally,the study investigates the behavior of a system with a high penetration of renewable energy sources.Based on the findings,this study concludes that a system is generally stable when interconnection is realized,given its appropriate location and dynamic component parameters.Furthermore,the critical eigenvalues of the system also exhibited improvement as the renewable energy sources were augmented.

CALL FOR PAPERS Dec.2018 Special Issue on Large Scale Renewable Energy Integration

Guest Editor in Chief:Professor Xiao-Ping Zhang, University of Birmingham The potential for renewable energy to make contributions to mitigating the impact of climate change is expected to increase significantly in the longer term. Renewable energy generation technologies including onshore wind, offshore wind, wave,tidal, marine current, and ocean thermal energy generation as well as PV power generation, which are considered

Optimal allocation method of energy storage for integrated renewable generation plants based on power market simulation

This study designs and proposes a method for evaluating the configuration of energy storage for integrated re-newable generation plants in the power spot market,which adopts a two-level optimization model of“system simulation+plant optimization”.The first step is“system simulation”which is using the power market simu-lation model to obtain the initial nodal marginal price and curtailment of the integrated renewable generation plant.The second step is“plant optimization”which is using the operation optimization model of the integrated renewable generation plant to optimize the charge-discharge operation of energy storage.In the third step,“sys-tem simulation”is conducted again,and the combined power of renewable and energy storage inside the plant is brought into the system model and simulated again for 8,760 h of power market year-round to quantify and compare the power generation and revenue of the integrated renewable generation plant after applying energy storage.In the case analysis of the provincial power spot market,an empirical analysis of a 1 GW wind-solar-storage integrated generation plant was conducted.The results show that the economic benefit of energy storage is approximately proportional to its capacity and that there is a slowdown in the growth of economic benefits when the capacity is too large.In the case that the investment benefit of energy storage only considers the in-come of electric energy-related incomes and does not consider the income of capacity mechanism and auxiliary services,the income of energy storage cannot fulfill the economic requirements of energy storage investment.

Two-time-scale Congestion Management Scheme for Microgrid Integrated Distribution Networks

Microgrids(MGs)with high penetration of dis-tributed generators may cause congestion in the distribution net-work during operation.To address this issue,this paper proposes a two-time-scale congestion management scheme for multiple MGs integrated distribution networks.Day-ahead hourly-scale dynamic congestion management(DCM)is formulated as a con-strained optimization problem,which can be solved by utilizing the proposed alternating iterative method,with the privacy of both the distribution network and MGs being preserved.The sub-hourly-scale contract energy tracking aims at fully utilizing the controllable resources of the MGs to minimize the difference of the contract and actual exchanged energy between the MG and distribution network.Through coordination of the proposed two timescales of management schemes,the MGs integrated distribution networks can operate economically while avoiding the probable congestion predicament with high penetration of renewable energy.Simulation studies with a i3-bus system MGs integrated distribution network demonstrated this proposed approach is effective to manage the congestion problem in the distribution network,while the energy tracking approach can improve the welfare of the MGs engaged in energy contracts execution.IndexTerms-Alternating giterativemethod,congestion management,microgrids,renewable energy integration.

Ensemble Wind Power Prediction Interval with Optimal Reserve Requirement

Wind power prediction interval(WPPI)models in the literature have predominantly been developed for and tested on specific case studies.However,wind behavior and characteristics can vary significantly across regions.Thus,a prediction model that performs well in one case might underperform in another.To address this shortcoming,this paper proposes an ensemble WPPI framework that integrates multiple WPPI models with distinct characteristics to improve robustness.Another important and often overlooked factor is the role of probabilistic wind power prediction(WPP)in quantifying wind power uncertainty,which should be handled by operating reserve.Operating reserve in WPPI frameworks enhances the efficacy of WPP.In this regard,the proposed framework employs a novel bi-layer optimization approach that takes both WPPI quality and reserve requirements into account.Comprehensive analysis with different real-world datasets and various benchmark models validates the quality of the obtained WPPIs while resulting in more optimal reserve requirements.

Intelligent Energy Management Strategy and Sizing Methodology for Hybrid Systems in Isolated Regions

In this study,a comprehensive approach is presented for the sizing and management of hybrid renewable energy systems(HRESs)that incorporate a variety of energy sources,while emphasizing the role of artificial neural networks(ANNs)in system management.For optimal sizing of an HRES,the monthly average method wherein historical weather data are used to calculate the monthly averages of solar irradiance and wind speed,offering a well-balanced strategy for system sizing.This ensures that the HRES is appropriately scaled to meet the actual energy requirements of the specified location,avoiding the pitfalls of over-and under-sizing,and thereby enhancing the operational efficiency.Furthermore,the study details a cutting-edge strategy that employs ANNs for managing the inherent complexities of HRESs.It elaborates on the design,modeling,and control strategies for the HRES components by utilizing Matlab/Simulink for implementation.The findings demonstrate the proficiency of the ANN-based power manager in determining the operational modes guided by a specifically designed flowchart.By integrating ANN-driven energy management strategies into an HRES,the proposed approach marks a significant advancement in system adaptability,precision control,and efficiency,thereby maximizing the effective utilization of renewable resources.

Potential of GSHP coupled with PV systems for retrofitting urban areas in different European climates based on archetypes definition

According to the recent policies regarding energy use in buildings and the need of retrofit strategies,the aim of this work is to support policies concerning the installation of ground source heat exchangers in urban and historical areas,raising the awareness on the potential energy saving achievable with optimal sizing and limited impact on the urban environment.Archetypes have been developed distinguishing among existing and historic buildings,focusing on single-family terrace houses,which are the typical residential buildings in European historic centres.A methodology for the optimal sizing of ground source heat pumps,eventually considering dual-source system or air system has been developed combining simulations of a photovoltaic system to estimate the self-sufficiency and the self-consumption for five orientations of the building.Extreme results have been obtained for warm cli-mates,with negligible heating energy demand and possibly free cooling systems rather than traditional cooling systems needed in wintertime.Penalty temperature was acceptable despite unbalanced energy demands.With proper inclination,photovoltaic systems could provide up to 40%of self-sufficiency share also in northern cli-mates.An energy-economic analysis was carried out obtaining a variety of cases representing a general overview of the European building stock and the potential benefits achievable in terms of renewable energy share,energy savings and economic investments needed to be extended to simulations at urban scale.

Multi-terminal DC grids: challenges and prospects

A few multi-terminal direct current(MTDC)systems are in operation around the world today. However,MTDC grids overlaying their AC counterpart might a reality in a near future. The main drivers for constructing such direct current grids are the large-scale integration of remote renewable energy resources into the existing alternative current(AC) grids, and the promotion and development of international energy markets through the socalled supergrids. This paper presents the most critical challenges and prospects for such emerging MTDC grids,along with a foreseeable technology development roadmap,with a particular focus on crucial control and operational issues that are associated with MTDC systems and grids.

Recent advances on smart grid technology and renewable energy integration

With the integration of renewable energy generations and other related changes,the smart grid,or the future electric power system,is confronted with new challenges and opportunities.Therefore,it is a promising subject in electrical engineering and much work has been done on it.This paper reviews the recent advances on the technologies of smart grid and renewable energy integration,from the aspects of modeling,simulation,protection and control,stability,operation,and planning.

Towards Fully Renewable Energy Systems:Experience and Trends in Denmark

Deployment of renewable energy generation capacities and integration of their power production into existing power systems has become a global trend,with a common set of operational challenges stemming from variability and limited predictability of power generation from,e.g.,wind and solar.Denmark is a country that invested early in wind energy,rapidly proposing very ambitious goals for the future of its energy system and global energy usage.While the case of Denmark is specific due to its limited size and good interconnections,there may still be a lot to learn from the way operational practice has evolved,also from shifting towards a liberalized electricity market environment,and more generally from going along with other technological and societal evolution.The aim of this paper is to give an overview of recent and current initiatives in Denmark that contributes towards a goal of reaching a fully renewable energy system.

A Chance-Constrained Wind Range Quantification Approach to Robust SCUC by Determining Dynamic Uncertainty Intervals

With increasing penetration of wind energy,the variability and uncertainty of wind resources have become important factors for power systems operation.In particular,an effective method is required for identifying the stochastic range of wind power output,in order to better guide the operational security of power systems.This paper proposes a metric to determine accurate wind power output ranges so that the probability of actual wind power outputs being out of the range would be less than a small pre-defined value.A mixed-integer linear programming(MILP)based chance-constrained optimization model is proposed for efficiently determining optimal wind power output ranges,which are quantified via maximum and the minimum wind generation levels with respect to a certain time interval.The derived wind power range is then used to construct dynamic uncertainty intervals for the robust securityconstrained unit commitment(SCUC)model.A comparison with the deterministic SCUC model and the traditional robust SCUC model with presumed static uncertainty interval demonstrates that the proposed approach can offer more accurate wind power variabilities(i.e.,different variability degrees with respect to different wind power output levels at different time periods).The proposed approach is also shown to offer more effective and robust SCUC solutions,guaranteeing operational security and economics of power systems.Numerical case studies on a 6-bus system and the modified IEEE 118-bus system with realworld wind power data illustrate the effectiveness of the proposed approach.