Distributed energy storage node controller and control strategy based on energy storage cloud platform architecture

Based on the energy storage cloud platform architecture,this study considers the extensive configuration of energy storage devices and the future large-scale application of electric vehicles at the customer side to build a new mode of smart power consumption with a flexible interaction,smooth the peak/valley difference of the load side power,and improve energy efficiency.A plug and play device for customer-side energy storage and an internet-based energy storage cloud platform are developed herein to build a new intelligent power consumption mode with a flexible interaction suitable for ordinary customers.Based on the load perception of the power grid,this study aims to investigate the operating state and service life of distributed energy storage devices.By selecting an integrated optimal control scheme,this study designs a kind of energy optimization and deployment strategy for stratified partition to reduce the operating cost of the energy storage device on the client side.The effectiveness of the system and the control strategy is verified through the Suzhou client-side distributed energy storage demonstration project.

Research on Distributed Cooperative Control Strategy of Microgrid Hybrid Energy Storage Based on Adaptive Event Triggering

Distributed collaborative control strategies for microgrids often use periodic time to trigger communication,which is likely to enhance the burden of communication and increase the frequency of controller updates,leading to greater waste of communication resources.In response to this problem,a distributed cooperative control strategy triggered by an adaptive event is proposed.By introducing an adaptive event triggering mechanism in the distributed controller,the triggering parameters are dynamically adjusted so that the distributed controller can communicate only at a certain time,the communication pressure is reduced,and the DC bus voltage deviation is effectively reduced,at the same time,the accuracy of power distribution is improved.The MATLAB/Simulink modeling and simulation results prove the correctness and effectiveness of the proposed control strategy.

Evaluation of intermittent-distributed-generation hosting capability of a distribution system with integrated energy-storage systems

The penetration rate of distributed generation is gradually increasing in the distribution system concerned.This is creating new problems and challenges in the planning and operation of the system.The intermittency and variability of power outputs from numerous distributed renewable generators could significantly jeopardize the secure operation of the distribution system.Therefore,it is necessary to assess the hosting capability for intermittent distributed generation by a distribution system considering operational constraints.This is the subject of this study.An assessment model considering the uncertainty of generation outputs from distributed generators is presented for this purpose.It involves different types of regulation or control functions using on-load tap-changers(OLTCs),reactive power compensation devices,energy storage systems,and the reactive power support of the distributed generators employed.A robust optimization model is then attained It is solved by Bertsimas robust counterpart through GUROBI solver.Finally,the feasibility and efficiency of the proposed method are demonstrated by a modified IEEE 33-bus distribution system.In addition,the effects of the aforementioned regulation or control functions on the enhancement of the hosting capability for intermittent distributed generation are examined.

Grid Side Distributed Energy Storage Cloud Group End Region Hierarchical Time-Sharing Configuration Algorithm Based onMulti-Scale and Multi Feature Convolution Neural Network

There is instability in the distributed energy storage cloud group end region on the power grid side.In order to avoid large-scale fluctuating charging and discharging in the power grid environment and make the capacitor components showa continuous and stable charging and discharging state,a hierarchical time-sharing configuration algorithm of distributed energy storage cloud group end region on the power grid side based on multi-scale and multi feature convolution neural network is proposed.Firstly,a voltage stability analysis model based onmulti-scale and multi feature convolution neural network is constructed,and the multi-scale and multi feature convolution neural network is optimized based on Self-OrganizingMaps(SOM)algorithm to analyze the voltage stability of the cloud group end region of distributed energy storage on the grid side under the framework of credibility.According to the optimal scheduling objectives and network size,the distributed robust optimal configuration control model is solved under the framework of coordinated optimal scheduling at multiple time scales;Finally,the time series characteristics of regional power grid load and distributed generation are analyzed.According to the regional hierarchical time-sharing configuration model of“cloud”,“group”and“end”layer,the grid side distributed energy storage cloud group end regional hierarchical time-sharing configuration algorithm is realized.The experimental results show that after applying this algorithm,the best grid side distributed energy storage configuration scheme can be determined,and the stability of grid side distributed energy storage cloud group end region layered timesharing configuration can be improved.

Coordinated planning for flexible interconnection and energy storage system in low-voltage distribution networks to improve the accommodation capacity of photovoltaic

The increasing proportion of distributed photovoltaics(DPVs)and electric vehicle charging stations in low-voltage distribution networks(LVDNs)has resulted in challenges such as distribution transformer overloads and voltage violations.To address these problems,we propose a coordinated planning method for flexible interconnections and energy storage systems(ESSs)to improve the accommodation capacity of DPVs.First,the power-transfer characteristics of flexible interconnection and ESSs are analyzed.The equipment costs of the voltage source converters(VSCs)and ESSs are also analyzed comprehensively,considering the differences in installation and maintenance costs for different installation locations.Second,a bilevel programming model is established to minimize the annual comprehensive cost and yearly total PV curtailment capacity.Within this framework,the upper-level model optimizes the installation locations and capacities of the VSCs and ESSs,whereas the lower-level model optimizes the operating power of the VSCs and ESSs.The proposed model is solved using a non-dominated sorting genetic algorithm with an elite strategy(NSGA-II).The effectiveness of the proposed planning method is validated through an actual LVDN scenario,which demonstrates its advantages in enhancing PV accommodation capacity.In addition,the economic benefits of various planning schemes with different flexible interconnection topologies and different PV grid-connected forms are quantitatively analyzed,demonstrating the adaptability of the proposed coordinated planning method.

Grid tie inverter energy stabilizing in smart distribution grid with energy storage

With the growing deployment of smart distribution grid,it has become urgent to investigate the smart distribution grid behavior during transient faults and improve the system stability.The feasibility of segmenting large power grids and multiple smart distribution grids interconnections using energy storage technology for improving the system dynamic stability was studied.The segmentation validity of the large power grids and smart distribution grid inverter output interconnections power system using energy storage technology was proved in terms of theoretical analysis.Then,the influences of the energy storage device location and capacity on the proposed method were discussed in detail.The conclusion is obtained that the ESD optimal locations are allocated at the tie line terminal buses in the interconnected grid,respectively.The effectiveness of the proposed method was verified by simulations in an actual power system.

Towards Implementation of Smart Grid: An Updated Review on Electrical Energy Storage Systems

A smart grid will require, to greater or lesser degrees, advanced tools for planning and operation, broadly accepted communications platforms, smart sensors and controls, and real-time pricing. The smart grid has been described as something of an ecosystem with constantly communication, proactive, and virtually self-aware. The use of smart grid has a lot of economical and environmental advantages;however it has a downside of instability and unpredictability introduced by distributed generation (DG) from renewable energy into the public electric systems. Variable energies such as solar and wind power have a lack of stability and to avoid short-term fluctuations in power supplied to the grid, a local storage subsystem could be used to provide higher quality and stability in the fed energy. Energy storage systems (ESSs) would be a facilitator of smart grid deployment and a “small amount” of storage would have a “great impact” on the future power grid. The smart grid, with its various superior communications and control features, would make it possible to integrate the potential application of widely dispersed battery storage systems as well other ESSs. This work deals with a detailed updated review on available ESSs applications in future smart power grids. It also highlights latest projects carried out on different ESSs throughout all around the world.

A Two-Layer Fuzzy Control Strategy for the Participation of Energy Storage Battery Systems in Grid Frequency Regulation

To address the frequency fluctuation problem caused by the power dynamic imbalance between the power system and the loadwhen a large number of newenergy sources are connected to the grid,a two-layer fuzzy control strategy is proposed for the participation of the energy storage battery system in FM.Firstly,considering the coordination of FM units responding to automatic power generation control commands,a comprehensive allocation strategy of two signals under automatic power generation control commands is proposed to give full play to the advantages of two FM signals while enabling better coordination of two FM units responding to FM commands;secondly,based on the grid FM demand and battery FM capability,a double-layer fuzzy control strategy is proposed for FM units responding to automatic power generation control commands in a coordinated manner under dual-signal allocation mode to precisely allocate the power output depth of FM units,which can control the fluctuation of frequency deviation within a smaller range at a faster speed while maintaining the battery charge state;finally,the proposed Finally,the proposed control strategy is simulated and verified inMatlab/Simulink.The results show that the proposed control strategy can control the frequency deviation within a smaller range in a shorter time,better stabilize the fluctuation of the battery charge level,and improve the utilization of the FM unit.

Electronic Controlled Energy Storage Devices and Applications in Future Smart Grid

This paper discusses the future power system consisting of distributed generations connected to local loads in the form of micro-grid systems.The benefits of having energy storage systems and the role of power electronics in micro-grid systems are presented.This paper also examines how micro-grids have a key role to play in the development of the smart grid.

Battery Energy Storage System and Demand Response Based Optimal Virtual Power Plant Operation

With certain controllability of various distribution energy resources (DERs) such as battery energy storage system (BESS), demand response (DR) and distributed generations (DGs), virtual power plant (VPP) can suitably regulate the powers access to the distribution network. In this paper, an optimal VPP operating problem is used to optimize the charging/discharging schedule of each BESS and the DR scheme with the objective to maximize the benefit by regulating the supplied powers over daily 24 hours. The proposed solution method is composed of an iterative dynamic programming optimal BESS schedule approach and a particle swarm optimization based (PSO-based) DR scheme approach. The two approaches are executed alternatively until the minimum elec-tricity cost of the whole day is obtained. The validity of the proposed method was confirmed with the obviously decreased supplied powers in the peak-load hours and the largely reduced electricity cost.

Network security protection technology for a cloud energy storage network controller

As part of the ongoing information revolution,smart power grid technology has become a key focus area for research into power systems.Intelligent electrical appliances are now an important component of power systems,providing a smart power grid with increased control,stability,and safety.Based on the secure communication requirements of cloud energy storage systems,this paper presents the design and development of a node controller for a cloud energy storage network.The function division and system deployment processes were carried out to ensure the security of the communication network used for the cloud energy storage system.Safety protection measures were proposed according to the demands of the communication network,allowing the system to run safely and stably.Finally,the effectiveness of the system was verified through a client-side distributed energy storage demonstration project in Suzhou,China.The system was observed to operate safely and stably,demonstrating good peak-clipping and valley filling effects,and improving the system load characteristics.

Role of Energy Storage on Distribution Transformer Loading in Low Voltage Distribution Network

Energy storage (ES) is a form of media that store one form of energy to be utilized at another time. Importance of ES is comprehended while intermittent nature of renewable energy (RE) generation increases and integration into the grid becomes viable in terms of economics and environment. However, technical analysis should be carried out before large scale integration into the grid. Some utilities experienced in Europe and expressed concern about issues in integrating large scale renewable energy in the areas of harmonics, voltage regulation, network protection and islanding. In Australia, distribution network (DN) is not robust compared to the European grid;moreover loads are largely distributed over large geographical areas. Installation of RE such as roof top solar photovoltaic (PV) is increasing in Australia which also boosted by the governments incentives to the individual owners. It is therefore obvious that large scale PV integration into the Australian grid is imminent. The intermittent characteristic of solar PV is expected to have greater impacts on DN in Australia compared to the DN in Europe. Therefore this paper investigated the impacts of solar PV on low voltage (LV) DN where loads connected through distribution transformer (DT) and finally further investigation was conducted with the deployment of ES into the respective load centers. It was found that storage reduced the overall peak load condition on the DT, and also reduced the energy fluctuation in the DN. It was also found that storage improved the voltage regulation on the LV side of DT and stabilized node voltage.

Smart Inverter Functionality Testing for Battery Energy Storage Systems

Variable distributed energy resources (DERs) such as photovoltaic (PV) systems and wind power systems require additional power resources to control the balance between supply and demand. Battery energy storage systems (BESSs) are one such possible resource for providing grid stability. It has been proposed that decentralized BESSs could help support microgrids (MGs) with intelligent control when advanced functionalities are implemented with variable DERs. One key challenge is developing and testing smart inverter controls for DERs. This paper presents a standardized method to test the interoperability and functionality of BESSs. First, a survey of grid-support standards prevalent in several countries was conducted. Then, the following four interoperability functions defined in IEC TR 61850-90-7 were tested: the specified active power from storage test (INV4), the var-priority Volt/VAR test (VV) and the specified power factor test (INV3) and frequency-watt control (FW). This study then out-lines the remaining technical issues related to basic BESS smart inverter test protocols.

Thermocline Thickness Evaluation on Stratified Thermal Energy Storage Tank of Co-generated District Cooling Plant

Temperature distribution of water inside of thermal storage tank reflects the condition of cooling energy stored in the tank. It can be used to define important parameters required for evaluation the performance of thermal storage tank. In this study, the thermocline thickness was evaluated for two cases of charging cycles： case Ⅰ at 393 m^3 / hr and case Ⅰ at 524 m^3 / hr. Hourly data were used for the study. Curve fitting approach was used to plot the temperature distribution profiles. Results obtained revealed that the fitting function enabled quantification of thermocline thickness of the thermal storage tank. The parameters that were determined are average cool-warm water temperatures and cool water depth in the tank. The approach offer an advantage to determine the thermocline thickness based on functionally relationship of temperature distribution profile. Results obtained shown that thermocline thickness increases at the higher flow rate. This was due to increased mixing of cool and warm water. It was also noted that thicker thermocline occurred in the region nearby the inlet diffuser. The findings indicate that the operating thermal energy storage as performing as a stratified tank.

Decoding the Einstein-Type Formula for Reducing Energy Conversion to Carbon Emissions in Renewables Systems

This article explores the role of distributed energy resources such as efficient solar cells that drive carbon neutrality within the solar energy. For example, the perovskite solar cells offer high efficiency and potential for low-cost production. A novel theoretical model is discovered in distributed energy resources for power emissions and cost. The smart carbon neutrality approaches are analyzed in both theory and experiments. The advantages, current challenges, and future prospects of the related solutions are discussed methodically. By addressing stability and scalability issues, these approaches can contribute significantly to reducing carbon emissions and promoting sustainable energy solutions.

Data-driven Predictive Voltage Control for Distributed Energy Storage in Active Distribution Networks

Integration of distributed energy storage(DES)is beneficial for mitigating voltage fluctuations in highly distributed generator(DG)-penetrated active distribution networks(ADNs).Based on an accurate physical model of ADN,conventional model-based methods can realize optimal control of DES.However,absence of network parameters and complex operational states of ADN poses challenges to model-based methods.This paper proposes a data-driven predictive voltage control method for DES.First,considering time-series constraints,a data-driven predictive control model is formulated for DES by using measurement data.Then,a data-driven coordination method is proposed for DES and DGs in each area.Through boundary information interaction,voltage mitigation effects can be improved by interarea coordination control.Finally,control performance is tested on a modified IEEE 33-node test case.Case studies demonstrate that by fully utilizing multi-source data,the proposed predictive control method can effectively regulate DES and DGs to mitigate voltage violations.

Incremental cost analysis model of distribution network based on economic dispatch of distributed new-energy storage system

With the implementation of China’s carbon-peaking and carbon-neutrality strategy,new energy will achieve leapfrog growth.Due to the good economics of distributed new-energy generation,it can not only save users’own investment,but also help to achieve local consumption of new energy.However,it will also bring about a series of incremental costs to the power grid.This paper first enumerates the concept,development status and scheduling mode of a distributed new-energy storage system.Based on the above,it establishes a new-energy power generation model and an energy storage system charging and discharging model,and proposes a global optimization scheduling model for a distributed new-energy storage system,considering the time-of-use electricity price and taking the lowest total operating cost of the distributed new-energy power generation system as the objective function.Finally,it proposes a distribution network incremental cost analysis model based on the penetration of distributed new energy.The calculation results show that the incremental cost of grid-connected distributed new energy is 1.0849,1.2585 and 1.3473 yuan/kWh,respectively,which indicates that the global dispatching model can optimize the power consumption structure of a distributed power generation system,and has the function of peak shaving and valley filling,but the incremental cost of the distribution network will also increase.

Low-Carbon Dispatching for Virtual Power Plant with Aggregated Distributed Energy Storage Considering Spatiotemporal Distribution of Cleanness Value

The scale of distributed energy resources is increasing,but imperfect business models and value transmission mechanisms lead to low utilization ratio and poor responsiveness.To address this issue,the concept of cleanness value of distributed energy storage(DES)is proposed,and the spatiotemporal distribution mechanism is discussed from the perspectives of electrical energy and cleanness.Based on this,an evaluation system for the environmental benefits of DES is constructed to balance the interests between the aggregator and the power system operator.Then,an optimal low-carbon dispatching for a virtual power plant(VPP)with aggregated DES is constructed,where-in energy value and cleanness value are both considered.To achieve the goal,a green attribute labeling method is used to establish a correlation constraint between the nodal carbon potential of the distribution network(DN)and DES behavior,but as a cost,it brings multiple nonlinear relationships.Subsequently,a solution method based on the convex envelope(CE)linear re-construction method is proposed for the multivariate nonlinear programming problem,thereby improving solution efficiency and feasibility.Finally,the simulation verification based on the IEEE 33-bus DN is conducted.The simulation results show that the multidimensional value recognition of DES motivates the willingness of resource users to respond.Meanwhile,resolving the impact of DES on the nodal carbon potential can effectively alleviate overcompensation of the cleanness value.

State-of-charge Balance Control and Safe Region Analysis for Distributed Energy Storage Systems with Constant Power Loads

This paper presents a fully distributed state-of-charge balance control (DSBC) strategy for a distributed energy storage system (DESS). In this framework, each energy storage unit (ESU) processes the state-of-charge (SoC) information from its neighbors locally and adjusts the virtual impedance of the droop controller in real-time to change the current sharing. It is shown that the SoC balance of all ESUs can be achieved. Due to virtual impedance, voltage deviation of the bus occurs inevitably and increases with load power. Meanwhile, widespread of the constant power load (CPL) in the power system may cause instability. To ensure reliable operation of DESS under the proposed DSBC, the concept of the safe region is put forward. Within the safe region, DESS is stable and voltage deviation is acceptable. The boundary conditions of the safe region are derived from the equivalent model of DESS, in which stability is analyzed in terms of modified Brayton-Moser's criterion. Both simulations and hardware experiments verify the accuracy of the safe region and effectiveness of the proposed DSBC strategy.

Fuzzy Droop Control for SOC Balance and Stability Analysis of DC Microgrid with Distributed Energy Storage Systems

The unbalanced state of charge(SOC)of distributed energy storage systems(DESSs)in autonomous DC microgrid causes energy storage units(ESUs)to terminate operation due to overcharge or overdischarge,which severely affects the power quality.In this paper,a fuzzy droop control for SOC balance and stability analysis of DC microgrid with DESSs is proposed to achieve SOC balance in ESUs while maintaining a stable DC bus voltage.First,the charge and discharge modes of ESUs are determined based on the power supply requirements of the DC microgrid.One-dimensional fuzzy logic is then applied to establish the relationship between SOC and the droop coefficient R,in the aforementioned two modes.In addition,when integrated with voltage-current double closed-loop control,SOC balance in different ESUs is realized.To improve the balance speed and precision,an exponential acceleration factor is added to the input variable of the fuzzy controller.Finally,based on the average model of converter,the system-level stability of microgrid is analyzed.MATLAB/Simulink simulation results verify the effectiveness and rationality of the proposed method.