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.

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.

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%.

水电富集区域电量送出能力提升的源储协同优化运行方法

针对可再生能源出力的强波动性、间歇性导致电力外送断面出现短时间尺度重过载、清洁能源送出消纳困难等问题,提出了水电富集区域电量送出能力提升的源储协同优化运行方法,该方法定义了衡量断面外送电量的量化指标,以系统发电成本最小、断面输出电量最大、储能消耗电量最小为目标,建立多目标优化模型,通过求解帕累托前沿,结合熵权双基点法,得到折中最优点。对我国某省级电网算例的仿真结果表明,该方法可有效通过水电、火电和储能的协同优化运行提升断面外送可再生能源的发电量,在保证系统安全稳定运行的前提下提升了可再生能源的消纳率。

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％。

电压源型风电比例影响区域电网频率调整研究

随着新能源大比例接入新型电力系统中,区域电网的频率稳定性问题凸显。为了研究风电在区域电网中对新能源系统稳定运行能力的影响,针对电压源型风电占比对区域电网频率调整的影响开展研究。对风电频率需求相应特性和电压源型风电机组控制进行分析,提出了在电压源型风电机组不同占比结构下的区域电网新能源场站容量分配评估方法。在Matlab/Simulink中对不同电压源型风电占比下的电网频率响应特性进行验证。结果表明,随着在混合风电场内配置一定比例的电压源型风电机组,可以有效地改善区域电网的频率稳定性。

绿氢内燃机及其在边无海岛地区的供电系统应用前瞻

氢内燃机实现依托内燃机完成零碳排放,其采用可再生能源制取的绿氢并结合储氢系统可以实现长期稳定能量输出。基于目前氢内燃机的关键技术和工作特性,该文创新提出将其应用于边远无人海岛地区(简称边无海岛)供电系统实现零碳发电。该系统通过氢内燃机替代柴油内燃机发电,制氢及储氢系统替代原有柴油和部分储能电池,达到充分利用边无海岛的可再生能源,实现海岛零碳可自身持续供能,摆脱外界输入能源依赖。该系统具备推广和应用前景,为未来边无海岛零碳自持供电系统建设提供参考。

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.

高比例电力电子电力系统过电压(三):直流故障下新能源暂时工频过电压机理

在高比例新能源和大容量直流输电工程大量投运的背景下,电力系统过电压问题日渐凸显,不仅制约直流输电能力,而且可能引发新能源大规模脱网。在新能源占比较高时,与交流设备相比,新能源的工频过电压耐受能力更低,该文针对直流故障引发的送端新能源机端过电压问题进行机理分析。首先,建立直流闭锁和直流多次换相失败后闭锁故障状态下新能源及传统同步机经特高压直流外送系统的等效电路分析模型,基于矢量关系,解析推导直流故障下的暂时工频过电压最大值。然后,分析直流输电功率水平、新能源并网功率、新能源低电压穿越控制参数、同步机至直流换流站电气距离以及新能源至直流换流站电气距离等因素对新能源机端电压最大值的影响。最后,通过PSD-BPA仿真软件在小算例系统和我国西北等值电网中验证理论分析的有效性。

基于可靠性的虚拟电厂微网源荷协同优化调度模型构建

为了确保虚拟电网微网的高效、可靠运行,构建虚拟电厂微网源荷协同优化调度模型。在正态分布概率模型的基础上建立光伏、风机概率模型和负荷概率模型,以此为依据展开虚拟电厂微网的场景构建。将运行成本、可再生能源消纳量和环境成本作为优化目标,建立源荷协同优化调度模型,通过萤火虫优化算法求解调度模型的最优解,以此实现虚拟电厂微网源荷协同优化调度。实验结果表明,构建模型的风电、光伏出力预测精度高、弃风电量低、风电利用率高,具有良好的协同优化调度能力。

基于改进DEAHP法的高比例可再生能源系统脆弱性评估

由于可再生能源间歇性和随机性的运行特点以及不稳定的输出特性与不可控的源动力,电网接入可再生能源时在结构和运行上不可避免地会出现某些难以预料的脆弱特性。通过建立系统多场景规划模型,综合多个角度共同评估电网元件的脆弱性,提出了带有不确定测度的脆弱性评估方法。此方法能够有效识别电网中存在的薄弱节点和支路,可为运行分析人员和调度人员提供电网安全预警信息。

A Novel Self Adaptive Modification Approach Based on Bat Algorithm for Optimal Management of Renewable MG

In the new competitive electricity market, the accurate operation management of Micro-Grid (MG) with various types of renewable power sources (RES) can be an effective approach to supply the electrical consumers more reliably and economically. In this regard, this paper proposes a novel solution methodology based on bat algorithm to solve the op- timal energy management of MG including several RESs with the back-up of Fuel Cell (FC), Wind Turbine (WT), Photovoltaics (PV), Micro Turbine (MT) as well as storage devices to meet the energy mismatch. The problem is formulated as a nonlinear constraint optimization problem to minimize the total cost of the grid and RESs, simultaneously. In addition, the problem considers the interactive effects of MG and utility in a 24 hour time interval which would in- crease the complexity of the problem from the optimization point of view more severely. The proposed optimization technique is consisted of a self adaptive modification method compromised of two modification methods based on bat algorithm to explore the total search space globally. The superiority of the proposed method over the other well-known algorithms is demonstrated through a typical renewable MG as the test system.

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.

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.

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.

Technical and Economic Aspects and Experience from 6 Years of Operating the Technology Using the Waste Heat from the Exhaust Gases of Heat Sources and 3 Years of Operating a Heating Plant in an Autonomous, Island Regime

This article is focused on technical and economic evaluation of more than 6-years experiences of operating the Waste Heat Recovery technology—the manner and system of flue gas processing generated in the combustion process in heat & power plants, cogeneration units, etc., which burn the gaseous fuel, primarily natural gas, or methane, biogas, geothermal gas, or other gaseous mixtures containing hydrogen. The solution proposes a more effective and non-traditional use of gaseous fuel for heating, the flue gases of which are processed in order to extract additional utilisable heat, with potential elimination of CO2 from them. Deploying of the heating plant in an island regime (OFF-GRID) enables definition of the benefits brought by the 3 years of operational experience and presents visions for the future offering the possibility to utilise the support energy services at the municipal as well as regional level.

新能源场站电网暂态电压支撑技术发展动态

含大规模新能源并网电力系统的暂态电压分析与控制已成为业界普遍关注的热点问题。针对该场景下的暂态电压支撑技术发展动态进行系统性综述。首先阐述新能源大规模发展过程中暂态电压问题发生的本质及带来的挑战,探讨了目前场站暂态电压支撑现状及其面临的问题。然后,给出典型单机无功源的电网暂态电压响应特性和控制技术现状,分析了适用于光伏/风电场站暂态电压支撑的聚合建模方法。然后论述了基于自律分散控制的多无功源协调控制思路及实现途径。接着,针对弱电网及直流送出等复杂场景,指出了暂态电压问题的特征及可能的控制手段。最后阐述了新能源电网暂态电压支撑技术需要进一步解决的关键问题,并对未来研究与开发工作进行了展望。