Optimal dispatch approach for rural multi-energy supply systems considering virtual energy storage

In response to the underutilization of energy and insufficient flexible operation capability of rural energy supply systems in China,this study proposes an optimal dispatch approach for a rural multi-energy supply system(RMESS)considering virtual energy storage(VES).First,to enable the flexible utilization of rural biomass resources and the thermal inertia of residential building envelopes,this study constructed VES-I and VES-II models that describe electrical-thermal and electrical-gas coupling from an electrical viewpoint.Subsequently,an RMESS model encompassing these two types of VES was formulated.This model delineates the intricate interplay of multi-energy components within the RMESS framework and facilitates the precise assessment of the adjustable potential for optimizing RMESS operations.Based on the above models,a day-ahead optimal dispatch model for an RMESS considering a VES is proposed to achieve optimal economic performance while ensuring efficient energy allocation.Comparative simulations validated the effectiveness of the VES modeling and the day-ahead optimal dispatch approach for the RMESS.

The Static Stability Region of an Integrated Electricity-Gas System Considering Voltage and Gas Pressure

In an integrated electricity-gas system(IEGS),load fluctuations affect not only the voltage in the power system but also the gas pressure in the natural gas system.The static voltage stability region(SVSR)method is a tool for analyzing the overall static voltage stability in a power system.However,in an IEGS,the SVSR boundary may be overly optimistic because the gas pressure may collapse before the voltage collapses.Thus,the SVSR method cannot be directly applied to an IEGS.In this paper,the concept of the SVSR is extended to the IEGS-static stability region(SSR)while considering voltage and gas pressure.First,criteria for static gas pressure stability in a natural gas system are proposed,based on the static voltage stability criteria in a power system.Then,the IEGS-SSR is defined as a set of active power injections that satisfies multi-energy flow(MEF)equations and static voltage and gas pressure stability constraints in the active power injection space of natural gas-fired generator units(NGUs).To determine the IEGSSSR,a continuation MEF(CMEF)method is employed to trace the boundary point in one specific NGU scheduling direction.A multidimensional hyperplane sampling method is also proposed to sample the NGU scheduling directions evenly.The obtained boundary points are further used to form the IEGSSSR in three-dimensional(3D)space via a Delaunay triangulation hypersurface fitting method.Finally,the numerical results of typical case studies are presented to demonstrate that the proposed method can effectively form the IEGS-SSR,providing a tool for IEGS online monitoring and dispatching.

Adaptive Predefined-Time Backstepping Control for Grid Connected Photovoltaic Inverter

The system performance of grid-connected photovoltaic(PV)has a serious impact on the grid stability.To improve the control performance and shorten the convergence time,a predefined-time controller based on backstepping technology and dynamic surface control is formulated for the inverter in the grid-connected photovoltaic.The time-varying tuning functions are introduced into state-tracking errors to realize the predefined-time control effect.To address the“computational explosion problem”in the design process of backstepping control,dynamic surface control is adopted to avoid the analytical calculations of virtual control.The disturbances of the PV system are estimated and compensated by adaptive laws.The control parameters are chosen and the global stability of the closed-loop is ensured by Lyapunov conditions.Simulation results confirm the effectiveness of the proposed controller and ensure the predefined time control in the photovoltaic inverter.

Multi-objective microgrid optimal dispatching based on improved bird swarm algorithm

Multi-objective optimal dispatching schemes with intelligent algorithms are recognized as effective measures to promote the economics and environmental friendliness of microgrid applications.However,the low accuracy and poor convergence of these algorithms have been challenging for system operators.The bird swarm algorithm(BSA),a new bio-heuristic cluster intelligent algorithm,can potentially address these challenges;however,its computational iterative process may fall into a local optimum and result in premature convergence when optimizing small portions of multi-extremum functions.To analyze the impact of a multi-objective economic-environmental dispatching of a microgrid and overcome the aforementioned problems of the BSA,a self-adaptive levy flight strategy-based BSA(LF-BSA)was proposed.It can solve the dispatching problems of microgrid and enhance its dispatching convergence accuracy,stability,and speed,thereby improving its optimization performance.Six typical test functions were used to compare the LF-BSA with three commonly accepted algorithms to verify its excellence.Finally,a typical summer-time daily microgrid scenario under grid-connected operational conditions was simulated.The results proved the feasibility of the proposed LF-BSA,effectiveness of the multi-objective optimization,and necessity of using renewable energy and energy storage in microgrid dispatching optimization.

Research on Source Maintenance Key Technology of the Smart Substation

The source maintenance technology of the smart substation offers the base for the models, data and graphs sharing between the substation and the dispatch center. This paper researches on the conversion technology between SCD model in IEC 61850 Ed. 2 and the CIM model in IEC 61970. The substation provides SVG and SCD documents to the dispatch center, which includes primary equipment information and the network topology. The dispatch center’s automation system completes the conversion between the two models. This paper researches on the smart remote technology, which uses IEC 61850 as communication protocol. It can filter and restructure communication data based on the needs of different dispatch center. At the same time, it can provide quality control of communication link, to ensure that the important data be sent in real time.

Battery Energy Storage System Information Modeling Based on IEC 61850

This paper discourses the typical ways to access system of the battery energy storage system. To realize the battery energy storage system based on IEC 61850, hierarchical information architecture for battery energy storage system is presented, the general design and implementation methods for device information model are elaborated, and the communication methods of the architecture are proposed. Example of battery energy storage system information model based on IEC 61850 tests that the battery energy storage system information architecture established is feasible.

Distributionally robust optimization configuration method for island microgrid considering extreme scenarios

The marine climate conditions are intricate and variable. In scenarios characterized by high proportions of wind and solar energy access, the uncertainty regarding the energy sources for island microgrid is significantly exacerbated, presenting challenges to both the economic viability and reliability of the capacity configuration for island microgrids. To address this issue, this paper proposes a distributionally robust optimization (DRO) method for island microgrids, considering extreme scenarios of wind and solar conditions. Firstly, to address the challenge of determining the probability distribution functions of wind and solar in complex island climates, a conditional generative adversarial network (CGAN) is employed to generate a scenario set for wind and solar conditions. Then, by combining k-means clustering with an extreme scenario selection method, typical scenarios and extreme scenarios are selected from the generated scenario set, forming the scenario set for the DRO model of island microgrids. On this basis, a DRO model based on multiple discrete scenarios is constructed with the objective of minimizing the sum of investment costs, operation and maintenance costs, fuel purchase costs, penalty costs of wind and solar curtailment, and penalty costs of load loss. The model is subjected to equipment operation and power balance constraints, and solved using the columns and constraints generation (CCG) algorithm. Finally, through typical examples, the effectiveness of this paper’s method in balancing the economic viability and robustness of the configuration scheme for the island microgrid, as well as reducing wind and solar curtailment and load loss, is verified.

CWGAN-GP with residual network model for lithium-ion battery thermal image data expansion with quantitative metrics

Lithium batteries find extensive applications in energy storage.Temperature is a crucial indicator for assessing the state of lithium-ion batteries,and numerous experiments require thermal images of lithium-ion batteries for research purposes.However,acquiring thermal imaging samples of lithium-ion battery faults is challenging due to factors such as high experimental costs and associated risks.To address this,our study proposes the utilization of a Conditional Wasserstein Generative Adversarial Network with Gradient Penalty and Residual Network(CWGAN-GP with Residual Network)to augment the dataset of thermal images depicting lithium-ion battery faults.We employ various evaluation metrics to quantitatively analyze and compare the generated thermal images of lithium-ion batteries.Subsequently,the expanded dataset,comprising four types of thermal images depicting lithium-ion battery faults,is input into a Mask Region-based Convolutional Neural Network for training.The results demonstrate that the proposed model surpasses both traditional Generative Adversarial Network and Wasserstein Generative Adversarial Network in terms of the quality of generated thermal images of lithium-ion batteries.Moreover,the augmentation of the dataset leads to an improvement in the fault diagnosis accuracy of the Mask Region-based Convolutional Neural Network.

Maximum entropy based probabilistic load flow calculation for power system integrated with wind power generation

Distributed generation including wind turbine(WT) and photovoltaic panel increases very fast in recent years around the world, challenging the conventional way of probabilistic load flow(PLF) calculation. Reliable and efficient PLF method is required to take this chage into account.This paper studies the maximum entropy probabilistic density function reconstruction method based on cumulant arithmetic of linearized load flow formulation,and then develops a maximum entropy based PLF(MEPLF) calculation algorithm for power system integrated with wind power generation(WPG). Compared with traditional Gram–Charlier expansion based PLF(GC-PLF)calculation method, the proposed ME-PLF calculation algorithm can obtain more reliable and accurate probabilistic density functions(PDFs) of bus voltages and branch flows in various WT parameter scenarios. It can solve thelimitation of GC-PLF calculation method that mistakenly gains negative values in tail regions of PDFs. Linear dependence between active and reactive power injections of WPG can also be effectively considered by the modified cumulant calculation framework. Accuracy and efficiency of the proposed approach are validated with some test systems. Uncertainties yielded by the wind speed variations, WT locations, power factor fluctuations are considered.

An Economic Benefit Evaluation Model and its Application for Optimizing Transmission Capacity of Multinational Interconnections

Multinational power grid interconnections play a critical part in supporting the vision of global energy internet.During the early stages of the Global Energy Internet,the value proposition of multinational interconnections should be carefully investigated in order to stimulate the activities for associated countries in such potential interconnections.This paper proposes a new e conomic benefit evaluation model which is quantified by using a chronological production cost simulation approach.The economic benefit model comprehensively considered investment costs and the benefits of the decrease of load payments and the increase of net generation revenue due to a transmission project interconnected with different countries.This economic benefit model can assist to quantitatively determine the optimal transmission capacity for multinational interconnections to achieve maximum economic benefits as a whole.In the case study,the economic benefit of an interconnected system of western China and the Gulf States is assessed by using the method proposed in this paper.And the optimal interconnection capacity with maximum benefit is achieved.The case study shows that the proposed method can be used for economic benefit assessment and is of great significance to the multinational and intercontinental transmission interconnections.

Successive MISOCP Algorithm for Islanded Distribution Networks with Soft Open Points

An optimal operation scheme is of great significance in islanded distribution networks to restore critical loads and has recently attracted considerable attention.In this paper,an optimal power flow(OPF)model for islanded distribution networks equipped with soft open points(SOPs)is proposed.Unlike in the grid-connected mode,the adequacy of local power generation in distribution networks is critical for islanded systems.The proposed approach utilizes the power output of local distributed generations(DGs)and the benefits of reactive power compensation provided by SOPs to allow maximum loadability.To exploit the available resources,an optimal secondary droop control strategy is introduced for the islanded distribution networks,thereby minimizing load shedding.The formulated OPF problem is essentially a mixed-integer nonlinear programming(MINLP)model.To guarantee the computation efficiency and accuracy.A successive mixed-integer second-order cone programming(SMISOCP)algorithm is proposed for handling the nonlinear islanded power flow formulations.Two case studies,incorporating a modified IEEE 33-bus system and IEEE 123-bus system,are performed to test the effectiveness of the proposed approach.

A preventive control strategy for static voltage stability based on an efficient power plant model of electric vehicles

With the increasing integration of wind farms and electric vehicles(EVs)in power systems,voltage stability is becoming more and more serious.Based on vehicle-to-grid(V2G),an efficient power plant model of EVs(E-EPP)was developed to estimate EV charging load with available corresponding response capacity under different charging strategies.A preventive control strategy based on E-EPP was proposed to maintain the static voltage stability margin(VSM)of power system above a predefined security level.Two control modes were used including the disconnection of EV charging load(‘V1G’mode)and the discharge of stored battery energy back to power grid(‘V2G’mode).A modified IEEE 14-bus system with high penetration of wind power and EVs was used to verify the effectiveness of preventive control strategy.Simulation results showed that the proposed strategy can not only improve the static voltage stability of power system with considerable wind generation,but also guarantee the travelling comfort for EV owners.

Dynamic frequency response from electric vehicles in the Great Britain power system

With the large penetration of renewable energy,fulfilling the balance between electricity demand and supply is a challenge to the modern power system.According to the UK government,the wind power penetration will reach 30%by the year 2020.The role of electric vehicles(EVs)contributing to frequency response was investigated.A dynamic frequency control strategy which considers the comfort level of vehicle owners was developed for EVs to regulate their power consumption according to the deviation of system frequency.A simulation model of a population of EVs equipped with such controlwas implemented inMatlab/Simulink platform.In this paper,a simplified Great Britain power system model is used to study the contribution of EVs to dynamic frequency control.The case study showed that using EVs as a demand response resource can greatly reduce the frequency deviations.And the rapid response from EVs can help reduce the operation cost of conventional generators.

Load curve smoothing strategy based on unified state model of different demand side resources

Renewable energy based distributed generation(DG) has the potential to reach high penetration levels in the residential region. However, its integration at the demand side will cause rapid power fluctuations of the tieline in the residential region. The traditional generators are generally difficult to manage rapid power fluctuations due to their insufficient efficiency requirements and low responding speed. With an effective control strategy, the demand side resources(DSRs) including DGs, electric vehicles and thermostatically-controlled loads at thedemand side, are able to serve as the energy storage system to smooth the load fluctuations. However, it is a challenge to properly model different types of DSRs. To solve this problem, a unified state model is first developed to describe the characteristics of different DSRs. Then a load curve smoothing strategy is proposed to offset the load fluctuations of the tie-line of the residential region, where a control matrix deduced from the unified state model is introduced to manage the power outputs of different DSRs,considering the response order and the comfort levels.Finally, a residential region with households is used to validate the load curve smoothing strategy based on the unified state model, and the results show that the power fluctuation rate of the tie-line is significantly decreased.Meanwhile, comparative study results are shown to demonstrate the advantages of the unified state model based load curve smoothing strategy.