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.

Research on Equivalent Modeling Method of AC-DC Power Networks Integrating with Renewable Energy Generation

Along with the increasing integration of renewable energy generation in AC-DC power networks,investigating the dynamic behaviors of this complex system with a proper equivalent model is significant.This paper presents an equivalent modeling method for the AC-DC power networks with doubly-fed induction generator(DFIG)based wind farms to decrease the simulation scale and computational burden.For the AC-DC power networks,the equivalent modeling strategy in accordance with the physical structure simplification is stated.Regarding the DFIG-based wind farms,the equivalent modeling based on the sequential identification of multi-machine parameters using the improved chaotic cuckoo search algorithm(ICCSA)is conducted.In light of the MATLAB simulation platform,a two-zone four-DC interconnected power grid with wind farms is built to check the efficacy of the proposed equivalentmodelingmethod.Fromthe simulation analyses and comparative validation in different algorithms and cases,the proposed method can precisely reflect the steady and dynamic performance of the demonstrated system under N-1 and N-2 fault scenarios,and it can efficiently achieve the parameter identification of the wind farms and fulfill the equivalent modeling.Consequently,the proposed approach’s effectiveness and suitability are confirmed.

Optimal control and management of large-scale battery energy storage system to mitigate fluctuation and intermittence of renewable generations

Battery energy storage system(BESS)is one of the effective technologies to deal with power fluctuation and intermittence resulting from grid integration of large renewable generations.In this paper,the system configuration of a China’s national renewable generation demonstration project combining a large-scale BESS with wind farm and photovoltaic(PV)power station,all coupled to a power transmission system,is introduced,and the key technologies including optimal control and management as well as operational status of this BESS are presented.Additionally,the technical benefits of such a large-scale BESS in dealing with power fluctuation and intermittence issues resulting from grid connection of large-scale renewable generation,and for improvement of operation characteristics of transmission grid,are discussed with relevant case studies.

Distributionally Robust Co-optimization of Transmission Network Expansion Planning and Penetration Level of Renewable Generation

Transmission network expansion can significantly improve the penetration level of renewable generation.However,existing studies have not explicitly revealed and quantified the trade-off between the investment cost and penetration level of renewable generation.This paper proposes a distributionally robust optimization model to minimize the cost of transmission network expansion under uncertainty and maximize the penetration level of renewable generation.The proposed model includes distributionally robust joint chance constraints,which maximize the minimum expectation of the renewable utilization probability among a set of certain probability distributions within an ambiguity set.The proposed formulation yields a twostage robust optimization model with variable bounds of the uncertain sets,which is hard to solve.By applying the affine decision rule,second-order conic reformulation,and duality,we reformulate it into a single-stage standard robust optimization model and solve it efficiently via commercial solvers.Case studies are carried on the Garver 6-bus and IEEE 118-bus systems to illustrate the validity of the proposed method.

Renewable Generation Capacity and Reliability Assessments for Resilient Active Distribution Networks Based on Time-sequence Production Simulation

The penetration of renewable generation will affect the energy utilization efficiency,economic benefit and reliability of the active distribution network(ADN).This paper proposes a time-sequence production simulation(TSPS)method for re-newable generation capacity and reliability assessments in ADN considering two operational status:the normal status and the fault status.During normal operation,an optimal dispatch model is proposed to promote the renewable consumption and increase the economic benefit.When a failure occurs,the renewable generators are partitioned into islands for resilient power supply and reliability improvement.A novel dynamic island partition model is presented based on mixed integer second-order cone programming(MISOCP).The effectiveness of the proposed TSPS method is demonstrated in a standard network integrated with historical data of load and renewable generations.

Real-time Dispatchable Region of Renewable Generation Constrained by Reactive Power and Voltage Profiles in AC Power Networks

A large amount of renewable energy generation(REG)has been integrated into power systems,challenging the operational security of power networks.In a real-time dispatch,system operators need to estimate the ability of the power network to accommodate REG with a limited reserve capacity.The real-time dispatchable region(RTDR)is defined as the largest range of a power injection that the power network can accommodate in a certain dispatch interval for a given dispatch base point.State-of-the-art research on the RTDR adopts a DC power flow model regardless of the voltage profiles and reactive power,which can overlook potentially insecure operational states of the system.To address this issue,this paper proposes an AC power flow based RTDR model simultaneously considering the reactive power and voltage profiles constraints.The nonlinear constraints in our model are approximated using a linear power flow model together with a polytope approximation technique for quadratic constraints.An adaptive constraint generation algorithm is used to calculate the RTDR.Simulation results using the IEEE 5-bus and 30-bus systems illustrate the advantages of the proposed model.

Renewable energy power generation projects started construction in Tibet

On March 19, the construction of a 10-MW photovoltaic power plant and a 1 000-kW new type geothermal power generation project were started by Guodian Longyuan Group in Yanbajing Town, Dangxiong County of Tibet.

Optimal Configuration for Distributed Generations in Micro-grid System Considering Diesel as the Main Control Source

This paper proposes an optimal configuration of the distributed hybrid renewable generations based on the stand-alone micro-grid system, considering the diesel as the main control source. Due to the natural sources and load of user changes randomly and the non-tinearity of the power output by renewable generations, an intelligent optimization method based on the improvement of the genetic algorithm and the control strategy are discussed. The instance analysis is compared with the optimization result of the hybrid system based on HOMER （hybrid optimization of multiple energy resources） and GA （genetic algorithm） method on Matlab software. The simulation result of the optimal configuration showed the new hybrid renewable system and would improve the power supply situation which decreased the cost of energy greatly compared with the conventional form of power supply system which was operated only by diesel. The conclusion of the comparing result between HOMER and GA method shows the advantages of the strategy for the diesel as main control sources.

Large-Scale Renewable Energy Transmission by HVDC: Challenges and Proposals

Renewable energy transmission by high-voltage direct current(HVDC)has attracted increasing attention for the development and utilization of large-scale renewable energy under the Carbon Peak and Carbon Neutrality Strategy in China.High-penetration power electronic systems(HPPESs)have gradually formed at the sending end of HVDC transmission.The operation of such systems has undergone profound changes compared with traditional power systems dominated by synchronous generators.New stability issues,such as broadband oscillation and transient over-voltage,have emerged,causing tripping accidents in large-scale renewable energy plants.The analysis methods and design principles of traditional power systems are no longer suitable for HPPESs.In this paper,the mechanisms of broadband oscillation and transient over-voltage are revealed,and analytical methods are proposed for HPPESs,including small-signal impedance analysis and electromagnetic transient simulation.Validation of the theoretical research has been accomplished through its application in several practical projects in north,northwest,and northeast region of China.Finally,suggestions for the construction and operation of the future renewable-energy-dominated power system are put forward.

Control and Stability of Large-scale Power System with Highly Distributed Renewable Energy Generation:Viewpoints from Six Aspects

Power systems are moving toward a low-carbon or carbon-neutral future where high penetration of renewables is expected.With conventional fossil-fueled synchronous generators in the transmission network being replaced by renewable energy generation which is highly distributed across the entire grid,new challenges are emerging to the control and stability of large-scale power systems.New analysis and control methods are needed for power systems to cope with the ongoing transformation.In the CSEE JPES forum,six leading experts were invited to deliver keynote speeches,and the participating researchers and professionals had extensive exchanges and discussions on the control and stability of power systems.Specifically,potential changes and challenges of power systems with high penetration of renewable energy generation were introduced and explained,and advanced control methods were proposed and analyzed for the transient stability enhancement of power grids.

Energy Flexibility in the Power System： Challenges and Opportunites in Philippines

Energy flexibility can address the challenges of large scale integration of renewable energy resources and thereby increasing imbalance in the power system. Flexible power system can provide reliable supply, low electricity cost and sustainability. Various situations and factors influence the adoption of the flexibility solutions, such as flexible electricity generation, demand-response, and electricity storage. This paper tries to analyze the current energy flexibility solutions and the factors that can influence the energy flexibility adoption. This paper takes Philippines as case study to provide an overview of the current condition of the Philippines＇ power system and discuss the energy flexibility in the Philippines＇ power system. A further discussion and recommendation is conducted in the end of the paper.

Enabling Hybrid Projects through Appropriate Market Design

Large-scale hybrid power plants, composed of two or more generation sources and with the participation of energy storage systems, have driven important electricity Market Design regulation discussions worldwide. Regulatory framework ought to be adapted to support technical particularities of these new generation arranges. This paper presents an assessment of the main requirements to be met by Market Design to enable hybrid power plants by means of assertive market incentives. Assessing regulatory adjustments promoted in Australia, United States, India, China, and Brazil, emphasizing the latter one, the authors presents a case study by applying specific computational simulation and optimization model to a hybrid Hydro-Solar plant, that supports the findings for the necessary evolution needed in the national regulatory framework in order to enable hybrid projects. The evaluation of international experiences indicates that the insertion of hybrid projects is associated with the design of the market they belong to and demand regulatory adjustments so that their attributes can be properly valued for the benefit of all stakeholders, especially for the electricity consumer.

Renewable Scenario Generation Using Controllable Generative Adversarial Networks with Transparent Latent Space

With the growing penetration of renewable energysources in power systems, it becomes increasingly important tocharacterize their inherent variability and uncertainty. Scenariogeneration is a key approach to provide a series of possible powerscenarios in the future for the system planner and operator tomake decisions. In this paper, a data-driven method is presentedfor renewable scenario generation using stable and controllablegenerative adversarial networks with transparent latent space(ctrl-GANs). The machine learning based algorithm can capturethe nonlinear and dynamic renewable patterns without the needfor modeling assumptions and complicated sampling techniques.The orthogonal regularization and spectral normalization areadopted to improve the training stabilization of the GAN model.To control the generation process, a relationship is built betweenfeatures of the generated scenarios and latent vectors on themanifold. Moreover, several new metrics for GANs are used toevaluate the quality of the scenarios. The proposed approachis applied to generate realistic time series data of wind andphotovoltaic power. The results demonstrate that our methodhas a better performance on numerical stabilization and is ableto control the generation process with latent space.

Load Shedding and Restoration for Intentional Island with Renewable Distributed Generation

Due to the high penetration of renewable distributed generation(RDG),many issues have become conspicuous during the intentional island operation such as the power mismatch of load shedding during the transition process and the power imbalance during the restoration process.In this paper,a phase measurement unit(PMU)based online load shedding strategy and a conservation voltage reduction(CVR)based multi-period restoration strategy are proposed for the intentional island with RDG.The proposed load shedding strategy,which is driven by the blackout event,consists of the load shedding optimization and correction table.Before the occurrence of the large-scale blackout,the load shedding optimization is solved periodically to obtain the optimal load shedding plan,which meets the dynamic and steady constraints.When the blackout occurs,the correction table updated in real time based on the PMU data is used to modify the load shedding plan to eliminate the power mismatch caused by the fluctuation of RDG.After the system transits to the intentional island seamlessly,multi-period restoration plans are generated to optimize the restoration performance while maintaining power balance until the main grid is repaired.Besides,CVR technology is implemented to restore more loads by regulating load demand.The proposed load shedding optimization and restoration optimization are linearized to mixed-integer quadratic constraint programming(MIQCP)models.The effectiveness of the proposed strategies is verified with the modified IEEE 33-node system on the real-time digital simulation(RTDS)platform.

Assessment of Sustainable Energy Strategy with Long-Term Global Energy Model Incorporating Nuclear Fuel Cycle

This paper investigates long-term energy strategy compatible with significant reduction of world carbon dioxide （CO2） emissions, employing a long-term global energy model, Dynamic New Earth 21 （called DNE21）. The model seeks the optimal energy mix from 2000 to 2100 that minimizes the world total energy system cost under various kinds of energy and technological constraints, such as energy resource constraints, energy supply and demand balance constraints, and CO2 emissions constraints. This paper discusses the results of primary energy supply, power generation mix, CO2 emission, CCS （carbon capture and storage） and total system costs for six regions including world as a whole. To evaluate viable pathways forward for implementation of sustainable energy strategies, nuclear power generation is a viable source of clean and green energy to mitigate the CO2 emissions. Present research shows simulation results in two cases consisting of no CO2 regulation case （base case） and CO2 REG case （regulation case） which halves the world CO2 emissions by the year 2050. Main findings of this research describe that renewable and nuclear power generation will contribute significantly to mitigate the CO2 emission worldwide.

Photovoltaic,thermoelectric and electromagnetic generation technologies applied in power systems for mobile unmanned systems

Unmanned systems are increasingly adopted in various fields,becoming an indispensable technology in daily life.Power systems are the lifeblood of unmanned systems,and affect the working time and task complexity.However,traditional power systems,such as batteries and fuels have a fixed capacity.Therefore,once the power supply is exhausted and cannot be replenished in time,the unmanned systems will stop working.Hence,researchers have increasingly begun paying attention to renewable energy generation technologies.The principles,advantages,and limitations of renewable energy generation technologies are different,and their application effects in different unmanned systems are also uneven.This paper presents a comprehensive study of the application and development status of photovoltaic,thermoelectric,and magnetoelectric generation technologies in four kinds of unmanned systems,including space,aviation,ground,and water,and then summarizes the adaptability and limitations of the three technologies to different systems.Moreover,future development directions are predicted to enhance the reliability of renewable energy generation technologies in unmanned systems.This is the first study to conduct a comprehensive and detailed study of renewable energy generation technologies applied in unmanned systems.The present work is critical for the development of renewable energy generation technologies and power systems for unmanned systems.

Simultaneous allocation of renewable energy sources and custom power quality devices in electrical distribution networks using artificial rabbits optimization

This study suggests an optimal renewable energy source(RES)allocation and distribution-static synchronous compensator(D-STATCOM)and passive power filters(PPFs)for an electrical distribution network(EDN)to improve its performance and power quality(PQ).First,the latest metaheuristic artificial rabbits optimization(ARO)is used to locate and size solar photovoltaic(PV),wind turbine(WT)and D-STATCOM units.In the second stage,ratings of single-tuned PPFs and D-STATCOMs at the RESs are determined,considering non-linear loads in the network.The multi-objective function reduces power loss,improves the voltage stability index(VSI)and limits total harmonic distortion.Simulations using the IEEE 33-bus EDN compared the ARO results with those of previous studies.In the first scenario,ideally integrated D-STATCOMs,PVs and WTs reduced losses by 34.79%,64.74%and 94.15%,respectively.VSI increases from 0.6965 to 0.7749,0.8804 and 0.967.The optimal WT integration of the first scenario outperformed the PVs and D-STATCOMs.The second step optimizes the WTs and PQ devices for non-linear loads.WTs and D-STATCOMs reduce the maximum total harmonic distortion of the voltage waveform by 5.21%with non-linear loads to 3.23%,while WTs and PPFs reduce it to 4.39%.These scenarios demonstrate how WTs and D-STATCOMs can improve network performance and PQ.The computational efficiency of ARO is compared to that of the pathfinder algorithm,future search algorithm,butterfly optimization algorithm and coyote optimization algorithm.ARO speeds up convergence and improves solution quality and comprehension.

A VAE-Bayesian deep learning scheme for solar power generation forecasting based on dimensionality reduction

The advancements in distributed generation(DG)technologies such as solar panels have led to a widespread integration of renewable power generation in modern power systems.However,the intermittent nature of renewable energy poses new challenges to the network operational planning with underlying uncertainties.This paper proposes a novel probabilistic scheme for renewable solar power generation forecasting by addressing data and model parameter uncertainties using Bayesian bidirectional long short-term memory(BiLSTM)neural networks,while handling the high dimensionality in weight parameters using variational auto-encoders(VAE).The forecasting performance of the proposed method is evaluated using various deterministic and probabilistic evaluation metrics such as root-mean square error(RMSE),Pinball loss,etc.Furthermore,reconstruction error and computational time are also monitored to evaluate the dimensionality reduction using the VAE component.When compared with benchmark methods,the proposed method leads to significant improvements in weight reduction,i.e.,from 76,4224 to 2,022 number of weight parameters,quantifying to 97.35%improvement in weight parameters reduction and 37.93%improvement in computational time for 6 months of solar power generation data.

Transmission Network Expansion Planning Considering Uncertainties in Loads and Renewable Energy Resources

This paper proposes a novel method for transmission network expansion planning(TNEP)that take into account uncertainties in loads and renewable energy resources.The goal of TNEP is to minimize the expansion cost of candidate lines without any load curtailment.A robust linear optimization algorithm is adopted to minimize the load curtailment with uncertainties considered under feasible expansion costs.Hence,the optimal planning scheme obtained through an iterative process would be to serve loads and provide a sufficient margin for renewable energy integration.In this paper,two uncertainty budget parameters are introduced in the optimization process to limit the considered variation ranges for both the load and the renewable generation.Simulation results obtained from two test systems indicate that the uncertainty budget parameters used to describe uncertainties are essential to arrive at a compromise for the robustness and optimality,and hence,offer a range of preferences to power system planners and decision makers.

Small-signal Stability Criteria in Power Electronics-dominated Power Systems:A Comparative Review

To tackle emerging power system small-signal stability problems such as wideband oscillations induced by the large-scale integration of renewable energy and power electronics,it is crucial to review and compare existing small-signal stability analysis methods.On this basis,guidance can be provided on determining suitable analysis methods to solve relevant small-signal stability problems in power electronics-dominated power systems(PEDPSs).Various mature methods have been developed to analyze the small-signal stability of PEDPSs,including eigenvalue-based methods,Routh stability criterion,Nyquist/Bode plot based methods,passivity-based methods,positive-net-damping method,lumped impedance-based methods,bifurcation-based methods,etc.In this paper,the application conditions,advantages,and limitations of these criteria in identifying oscillation frequencies and stability margins are reviewed and compared to reveal and explain connections and discrepancies among them.Especially,efforts are devoted to mathematically proving the equivalence between these small-signal stability criteria.Finally,the performance of these criteria is demonstrated and compared in a 4-machine 2-area power system with a wind farm and an IEEE 39-bus power system with 3 wind farms.