Microgrid Energy Storage Research Articles

Research on the optimal allocation method of PV micro-grid energy storage capacity based on empirical modal decomposition

To address the problem of high battery usage throughout the year, an empirical modal decomposition-based optimal allocation method for PV microgrid energy storage capacity is designed. This paper describes the basic structure of the photovoltaic equivalent circuit to obtain the output power of the photovoltaic microgrid panel. We use the energy storage battery as a secondary power source to smooth the photovoltaic power output and calculate the wasted power. In this paper, an energy management model based on empirical mode decomposition is constructed, and the photovoltaic power generation unit and energy storage unit are regarded as optimally configured whole. Based on the above conditions, an optimal allocation method of energy storage capacity is designed. Experimental results: the mean value of annual battery usage for the PV microgrid capacity optimization allocation method in the paper is: 53.74%, indicating that the designed PV microgrid capacity optimization allocation method is more feasible after combining the empirical modal decomposition algorithm.

Optimal Allocation of Energy Storage Capacity in Distributed Micro-grid Based on Improved Whale Algorithm

At present, the setting of monitoring nodes for optimal allocation of energy storage capacity in micro-grid is generally target-based, with slow allocation speed and weak pertinence, which can easily lead to the increase of the final difference adjustment coefficient and affect the final allocation effect. Therefore, the research and analysis on the optimal allocation method of distributed micro-grid energy storage capacity based on the improved whale algorithm are proposed. According to the actual disposal requirements and standards, the basic operation frequency and reserve capacity of the micro-grid are determined, the multi-level monitoring node deployment form is set, the monitoring range is expanded, and the speed and pertinence of configuration are improved to complete the layout of energy storage capacity monitoring nodes. The optimal allocation model of the improved whale calculation of grid energy storage capacity is constructed. The optimal allocation is realized by constraint programming. The test results verify that the energy storage power of the micro-grid will be enhanced with the increase of the frequency modulation times of energy storage calculated by the whale calculation optimization configuration test group. In this context, the difference adjustment coefficient of the micro-grid configuration becomes lower, only 1.03, indicating that in the process of practical application, the energy storage capacity configuration of micro-grid is optimized. The frequency modulation fluctuation is slowed down, the running frequency is faster, and the method has practical application value.

Research and implementation of frequency control strategy of islanded microgrids rich in grid-connected small hydropower

Due to the weak network architecture of mountainous power grid rich in grid-connected small hydropower, once the small hydropower units operate independently as a network when the upper power grid fails and loses power, the reliability of the power supply could be effectively improved. To cope with the problem of insufficient frequency regulation capacity of small hydropower units and the large risk of separation fault, this paper proposes a piecewise variable coefficient PID control strategy which improves the speed regulation control strategy of hydropower units, and a joint frequency regulation strategy of hydropower energy storage is designed to optimize the system operation state. Based on the MATLAB simulation platform, a hydropower energy storage microgrid model of mountainous power grid was built to verify the effectiveness of the segmented variable parameter control strategy. Using the proposed control strategy, the hydropower intelligent control terminal was developed and put into application in a certain area of Guangdong. Through simulation analysis and engineering applications, the practicality of the application of device engineering is verified to have good application and promotion value for a multi-hydropower mountainous power grid.

Research on Optimization of Distribution Network based on Power Electronic Transformer

As the core equipment of hybrid microgrid, power electronic transformer is a new type of multifunctional transformer which integrates power electronic technology, information communication technology and control protection technology. On the background of the Beijing Low-Carbon Winter Olympics Smart Grid Demonstration Project, this paper proposed an AC/DC hybrid microgrid topology with dual-end power supply based on power electronic transformer. Moreover, a coordinated optimization control for AC/DC hybrid microgrid based on power electronic transformer is studied. The content of the paper mainly includes: The common topology of power electronic transformer is studied, and a three stage four-port power electronic transformer is proposed according to the demand of demonstration project. The interface converter topology structure and control method of distributed generation and energy storage in hybrid microgrid are analyzed, and the system model of hybrid microgrid is established. Simulation results show that MPPT control can maximize the power output of distributed generation, and piecewise droop control can realize seamless switching between power control and voltage control in the grid-tied or autonomous mode.

Simulation study on disturbance of energy storage microgrid system based on bi-directional DC/DC converter

With the national policy of energy saving and emission reduction, microgrid technology has gradually entered into people’s daily life and received more and more technical and financial support. In this paper, we build an energy storage microgrid system based on a bi-directional DC/DC converter through Matlab/Simulink software, construct a simple simulation model of a PV battery, storage battery and bi-directional DC/DC converter, and simulate and verify the anti-interference ability and stability recovery ability of the microgrid under the situation of external disturbance. The experimental results show that the system can simulate the operation of a microgrid system.

A Novel Resilient Control of Grid-Integrated Solar PV-Hybrid Energy Storage Microgrid for Power Smoothing and Pulse Power Load Accommodation

Solar photovoltaics (PVs) are increasingly penetrating remote are a power systems. However, the adverse effect of pulse power loads and fluctuating PV power brings severe grid instability. Therefore, an effort is made to propose a hybrid energy storage system (HESS) that encompasses hydrogen/bromine redox flow battery (RFB) and supercapacitor (SC) for grid-integrated PV systems to facilitate high energy and power support. Furthermore, the system is equipped with an antiwindup mixed-order generalized integrator (AWMOGI), an improved sparrow search algorithm (ISSA) tuned tilt integral–derivative with filter (TIDF) controller, and a fast-acting adaptive dc-link power-based energy management control. AWMOGI extracts fundamental components of grid voltage and is immune to noise and grid disturbances. The ISSA-tuned TIDF controller has better error mitigation ability and quickly settles the actual signal to the reference for dc-link voltage control of the voltage-source inverter, PV maximum power point tracking, and HESS control that improves the overall system dynamics. The energy management system coordinates RFB and SC participation in handling sudden and average changes in power surges resulting in the first dc-link voltage regulation and less current stress on RFB. The proposed system and furnished control effectiveness are confirmed through MATLAB simulation and OPAL-RT real-time simulator test bench.

Relaxation‐based bi‐lever reformulation and decomposition algorithm‐based collaborative optimization of multi‐microgrid for cloud energy storage

AbstractEnergy storage devices become an indispensable part of modern power systems with high renewable energy penetration level. To reduce the operating costs, it is a promising way to allow the sharing and leasing of energy storage devices. In this paper, a bi‐lever optimized dispatch scheme is proposed to improve the usage efficiency of cloud energy storage in multi microgrids (MMG) system. Minimizing the operating costs of shared cloud energy storage is the main task of the upper lever while maximizing the profits of MMG is the goal of the lower lever. Moreover, the transaction cost and benefit between the two levers play an important role in system level optimization. This leads to a hybrid optimization problem with both discrete decision variables and continuous decision variables. To solve the problem, a relaxation‐based bi‐lever reformulation and decomposition algorithm is developed. The effectiveness of the proposed bi‐lever dispatch optimization model is verified by carrying out numerical experiments in three scenarios. It is shown that the proposed cloud energy storage service can effectively reduce the operating cost of MMG.

IoT-Enabled Campus Prosumer Microgrid Energy Management, Architecture, Storage Technologies, and Simulation Tools: A Comprehensive Study

Energy is very important in daily life. The smart power system provides an energy management system using various techniques. Among other load types, campus microgrids are very important, and they consume large amounts of energy. Energy management systems in campus prosumer microgrids have been addressed in different works. A comprehensive study of previous works has not reviewed the architecture, tools, and energy storage systems of campus microgrids. In this paper, a survey of campus prosumer microgrids is presented considering their energy management schemes, optimization techniques, architectures, storage types, and design tools. The survey is comprised of one decade of past works for a true analysis. In the optimization techniques, deterministic and metaheuristic methods are reviewed considering their pros and cons. Smart grids are being installed in different campuses all over the world, and these are considered the best alternatives to conventional power systems. However, efficient energy management techniques and tools are required to make these grids more economical and stable.

Grouping Control Strategy for Battery Energy Storage Power Stations Considering the Wind and Solar Power Generation Trend

For the optimal power distribution problem of battery energy storage power stations containing multiple energy storage units, a grouping control strategy considering the wind and solar power generation trend is proposed. Firstly, a state of charge (SOC) consistency algorithm based on multi-agent is proposed. The adaptive power distribution among the units started can be realized using this algorithm. Then, considering the trend of wind and solar power generation, a reasonable grouping control strategy is formulated. The grouping situation of the units is determined by using the probability distribution characteristics of energy storage charging and discharging, which reduces the number of charging and discharging conversions and extends the power station life. Finally, the actual data of a wind–solar energy storage microgrid is used to verify the method. The simulation results demonstrate that the proposed method has certain advantages in terms of control effect, SOC consistency, and extending the power station life.

Integration of SiC Devices and High-Frequency Transformer for High-Power Renewable Energy Applications

This paper presents a novel structure of Integrated SiC MOSFETs with a high-frequency transformer (I-SiC-HFT) for various high-power isolated DC–DC converters. Several resonant converters are considered for integration in this paper, including the phase-shift full-bridge (PSFB) converter, inductor–inductor–capacitor (LLC) resonant converter, bidirectional PSFB converter, and capacitor–inductor–inductor–capacitor (CLLC) resonant converter. The applications of I-SiC-HFT are focused on V2G EV battery charging systems, energy storage in DC and AC microgrids, and renewable energy systems. SiC devices, including MOSFETs, Schottky diodes, and MOSFET modules, are used in this novel structure of I-SiC-HFT. The high-frequency magnetic structure uses distributed ferrite cores to form a large central space to accommodate SiC devices. The optimized architecture of I-SiC-HFT and heatsink structure is proposed for thermal management of SiC devices. To prove the concept, a small-scale 1.5 kW prototype I-SiC-HFT is used to demonstrate the basic structure and various performance indicators through the FEM based electromagnetic simulation and DC–DC converter experiments.

Prospects and Barriers for Renewable Microgeneration in India

Today, India is one of the largest emitters of greenhouse gases with fast growing energy demand. The fact that India has no nationwide energy system due to natural causes such as impassable forests, mountainous areas, and considerable distances, makes the development of microgeneration based on renewable energy is a promising direction for this country from technical, economical, and environmental points of view. The present paper aims at analyzing barriers for developing the microgeneration based on the most advanced renewable energy technologies (photovoltaics and small wind) in India. Our results demonstrate that for many territories in India, microgeneration is not just a supplementary way to provide electricity to the local population, but also the only way. Therefore, higher technical requirements are imposed, particularly the need for parallel development of microgrid management and energy storage technologies. This creates additional technical, infrastructural, and financial barriers to development and reduces the role of an individual consumer (prosumer). Due to the low importance of individual consumers, companies selling and servicing micro-generating equipment are more focused on the B2B sells format, manifested in the strategy of their representation on the Internet.

A Group Resident Daily Load Forecasting Method Fusing Self-Attention Mechanism Based on Load Clustering

Daily load forecasting is the basis of the economic and safe operation of a power grid. Accurate prediction results can improve the matching of microgrid energy storage capacity allocation. With the popularization of smart meters, the interaction between residential electricity demand and sources and networks is increasing, and massive data are generated at the same time. Previous forecasting methods suffer from poor targeting and high noise. They cannot make full use of the important information of the load data. This paper proposes a new framework for daily load forecasting of group residents. Firstly, we use the singular value decomposition to address the problem of high dimensions of residential electricity data. Meanwhile, we apply a K-Shape-based group residential load clustering method to obtain the typical residential load data. Secondly, we introduce an empirical mode decomposition method to address the problem of high noise of residential load data. Finally, we propose a Bi-LSTM-Attention model for residential daily load forecasting. This method can make full use of the contextual information and the important information of the daily load of group residents. The experiments conducted on a real data set of a power grid show that our method achieves excellent improvements on five prediction error indicators, such as MAPE, which are significantly smaller than the compared baseline methods.

A Hierarchical Control of Supercapacitor and Microsources in Islanded DC Microgrids

This paper proposes a hierarchical control approach for SuperCapacitor (SC) energy storage and microsources in islanded DC microgrids. It takes into account microsources’ dynamic and steady-state limitations. The proposed approach relies on an architecture presented for the SC’s and microsources’ interfaces with the DC bus. In the proposed architecture, DC microsources interface with the DC bus through buck converters. Moreover, the SC interfaces with the DC bus through the bi-directional buck converter. The instantaneous loads currents are measured and employed in the secondary control to calculate the reference currents for buck converters. In the primary control, we run buck converters as current sources. Moreover, the bi-directional buck converter is run to regulate the DC bus voltage. The proposed approach is generic; meaning that it can be employed for any islanded DC microgrid. Without loss of generality, to prove its effectiveness, we utilized it for a Low Voltage DC (LVDC) microgrid in this paper. Analysis, design, simulations, and experimental verifications are presented for the LVDC microgrid. The experimental results confirm that, by employing the proposed approach, the DC bus voltage deviations from its reference voltage is 5% and it restores in less than <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$1~sec$ </tex-math></inline-formula> .

Robust Planning Method for Photovoltaic Microgrid Energy Storage Considering Source-Load Flexibility Resources

The microgrid based on distributed generation is one of the new forms of power system distribution network, and energy storage can provide important support for the access of distributed generation. Due to the shortcomings of the traditional photovoltaic microgrid energy storage method, the energy storage capacity is low. To improve the energy storage level of the photovoltaic microgrid, the robustness planning method of photovoltaic microgrid energy storage considering the flexibility resources of source, network and load is studied. Based on the flexibility resources of the microgrid, the balance index of flexibility supply and demand and the planning index of flexibility response capability is proposed. According to the source-network load algorithm, the optimal scheme of resource complementation is obtained. Based on the storage battery and supercapacitor of the photovoltaic microgrid, the photovoltaic microgrid energy storage robust configuration model is constructed. Comparing the energy storage planning method designed in this paper with two groups of traditional methods, the experimental results show that in the same energy storage time, the energy storage capacity of this method accounts for 50.49%, while that of the traditional group 1 and group 2 is 32.52% and 41.26%, respectively. The proposed PV microgrid robust planning method considering source-load flexibility is reasonable and effective in the energy storage resource allocation scheme, which is of great significance for promoting energy transformation and building a new power system.

Double-Layer-Optimizing Method of Hybrid Energy Storage Microgrid Based on Improved Grey Wolf Optimization

Double-Layer-Optimizing Method of Hybrid Energy Storage Microgrid Based on Improved Grey Wolf Optimization

Coordinated optimal dispatch of composite energy storage microgrid based on double deep Q-network

Coordinated optimal dispatch of composite energy storage microgrid based on double deep Q-network

Case Study of Backup Application with Energy Storage in Microgrids

The reliability of energy supply is an important factor for end-users of electricity. Although many advances and efforts have been made by distribution companies to guarantee energy quality, weak feeders and grids are still usually found. As an alternative to minimize such problems, Battery Energy Storage Systems (BESSs) can be used to supply energy to users in the case of power outages or major energy quality problems. This paper presents test results on a real application scenario in a microgrid with different load configurations in the moment of interruption. The tests were compared to each other to analyze the impact found in each scenario. In addition to those, real unpremeditated cases of power quality problems were also discussed, and the performance of the utilized BESS was evaluated.

Optimal control of source–load–storage energy in DC microgrid based on the virtual energy storage system

By integrating controllable source-load in the form of virtual energy storage into the energy storage control system within the DC microgrid, the virtual energy storage system (VESS) with flexible resources can provide a viable solution for the system to effectively accomplish the co-optimization of source–load–energy storage. Firstly, based on the conversion relationship between the rotational kinetic energy of the wind turbine and asynchronous motor and capacitive energy storage, the wind turbine and desalination load are established as virtual energy storage equivalent models; as electric vehicles have both mobile load and energy storage characteristics, the tariff mechanism is used to develop an orderly charging and discharging model to establish a virtual energy storage model for electric vehicles. Secondly, the economic optimization model of the VESS is established jointly with source–load–storage to maximize the intra-day microgrid operation gain, and an energy cooperative optimization control strategy is formed with virtual capacitance value and virtual charge state as operating parameters in each period of time. Finally, it is verified through simulation that the source–load–storage​ energy co-optimization control can not only relieve the regulation pressure of energy storage in the DC microgrid but also significantly improve the operation economy of the microgrid.

Improving real-time energy decision-making model with an actor-critic agent in modern microgrids with energy storage devices

The hereby study combines a reinforcement learning machine and a myopic optimization model to improve the real-time energy decisions in microgrids with renewable sources and energy storage devices. The reinforcement learning-based agent is built as an actor-critic agent making the aggregated near-optimal charging/discharging energy decisions of the microgrid energy storage devices from a discrete action space relying on a reward related to the microgrid online optimal objective function value. The next step time energy levels of storage devices are then computed and provided to the myopic optimization-based decision-making model as parameters which optimally find the incurred power flow within the microgrid minimizing the real-time microgrid energy cost. The real-time measurement of stochastic parameters of the microgrid coupled with the current energy levels of electrical and heat storage are input to the artificially intelligent machine as observations states. The actor-critic agent approximators are modeled as deep neural networks optimized using the Adam gradient descent algorithm with a gradient threshold. Although the proposed model with a 2-kWh increment of the charging/discharging energy training is time-consuming, it has been able at 100% to optimally make microgrid energy decisions and improve online energy decisions by 90.98% compared to the myopic model alone.

Review of Recent Developments in Microgrid Energy Management Strategies

The grid integration of microgrids and the selection of energy management systems (EMS) based on robustness and energy efficiency in terms of generation, storage, and distribution are becoming more challenging with rising electrical power demand. The problems regarding exploring renewable energy resources with efficient and durable energy storage systems demand side management and sustainable solutions to microgrid development to maintain the power system’s stability and security. This article mainly focuses on the overview of the recent developments of microgrid EMS within the control strategies and the implementation challenges of the microgrid. First, it provides energy management strategies for the major microgrid components, including load, generation, and energy storage systems. Then, it presents the different optimization approaches employed for microgrid energy management, such as classical, metaheuristic, and artificial intelligence. Moreover, this article sheds light on the major implementation challenges of microgrids. Overall, this article provides interactive guidelines for researchers to assist them in deciding on their future research.