Multi-Time Scale Optimal Scheduling of a Photovoltaic Energy Storage Building System Based on Model Predictive Control

Building emission reduction is an important way to achieve China’s carbon peaking and carbon neutrality goals.Aiming at the problem of low carbon economic operation of a photovoltaic energy storage building system,a multi-time scale optimal scheduling strategy based on model predictive control(MPC)is proposed under the consideration of load optimization.First,load optimization is achieved by controlling the charging time of electric vehicles as well as adjusting the air conditioning operation temperature,and the photovoltaic energy storage building system model is constructed to propose a day-ahead scheduling strategy with the lowest daily operation cost.Second,considering inter-day to intra-day source-load prediction error,an intraday rolling optimal scheduling strategy based on MPC is proposed that dynamically corrects the day-ahead dispatch results to stabilize system power fluctuations and promote photovoltaic consumption.Finally,taking an office building on a summer work day as an example,the effectiveness of the proposed scheduling strategy is verified.The results of the example show that the strategy reduces the total operating cost of the photovoltaic energy storage building system by 17.11%,improves the carbon emission reduction by 7.99%,and the photovoltaic consumption rate reaches 98.57%,improving the system’s low-carbon and economic performance.

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.

Energy Management and Capacity Optimization of Photovoltaic, Energy Storage System, Flexible Building Power System Considering Combined Benefit

Building structures themselves are one of the key areas of urban energy consumption,therefore,are a major source of greenhouse gas emissions.With this understood,the carbon trading market is gradually expanding to the building sector to control greenhouse gas emissions.Hence,to balance the interests of the environment and the building users,this paper proposes an optimal operation scheme for the photovoltaic,energy storage system,and flexible building power system(PEFB),considering the combined benefit of building.Based on the model of conventional photovoltaic(PV)and energy storage system(ESS),the mathematical optimization model of the system is proposed by taking the combined benefit of the building to the economy,society,and environment as the optimization objective,taking the near-zero energy consumption and carbon emission limitation of the building as the main constraints.The optimized operation strategy in this paper can give optimal results by making a trade-off between the users’costs and the combined benefits of the building.The efficiency and effectiveness of the proposed methods are verified by simulated experiments.

Evaluation of the Performance of Lithium-Ion Accumulators for Photovoltaic Energy Storage

In a context of climate change exacerbated by the increasing scarcity of fossil fuels, renewable energies, in particular photovoltaic solar energy, offer a promising alternative. Solar energy is non-polluting, globally available and the most widely distributed resource on Earth. However, the intermittency of this energy source considerably limits its expansion. To solve this problem, storage techniques are being used, in particular, electrochemical storage using lithium-ion batteries. In this article, we will evaluate the performance of lithium-ion batteries when integrated into a photovoltaic grid. To do this, modelling and simulation of a photovoltaic system connected to a lithium-ion battery storage system will be carried out using MATLAB/Simulink software. A diagnostic of the energy consumption of the Kaya Polytechnic University Centre will be carried out, and the data will then be used in the simulator to observe the behaviour of the PV-Lion system. The results obtained indicate that lithium-ion batteries can effectively meet the centre’s energy demand. In addition, it was observed that lithium-ion batteries perform better under high energy demand than the other battery technologies studied. Successive storage systems with the same capacity but different battery technologies were compared. It was found that these storage systems can handle a maximum power of 4 × 105 W for lead-acid batteries, 6.5 × 105 W for nickel-cadmium batteries, 8.5 × 105 W for nickel-metal-hydride batteries, and more than 10 × 105 W for lithium-ion technology.

Research on Virtual DC Generator-Based Control Strategy of DCMicrogrid with Photovoltaic and Energy Storage

With the penetration of a large number of photovoltaic power generation units and power electronic converters,the DC microgrid shows low inertia characteristics,which might affect the stable operation of the microgrid in extreme cases.In order to enhance the“flexible features”of the interface converter connected to the DC bus,a control strategy of DCmicrogrid with photovoltaic and energy storage based on the virtual DC generator(VDCG)is proposed in this paper.The interface converters of the photovoltaic power generation system and the energy storage system simulates the inertia and damping characteristics of the DC generator to improve the stability of the DC bus voltage.The impedance ratio of DC microgrid was obtained by establishing the small-signal model of photovoltaic power generation system and energy storage system,and the Nyquist curves was applied to analyze the small-signal stability of the system.Finally,the simulation results were verified with MATLAB/Simulink.The results show that the proposed control strategy can slow down the fluctuation of bus voltage under the conditions of photovoltaic power fluctuation and load mutation,thus enhancing the system stability.

Optimal configuration strategy of energy storage system in high photovoltaic penetration micro-grid based on voltage sensitivity analysis

Energy storage is an effective measure to deal with internal power fluctuation of micro-grid and ensure stable operation, especially in the micro-grid with high photovoltaic(PV) penetration. Its capacity configuration is related to the steady, safety and economy of micro-grid.In order to improve the absorptive capacity of micro-grid on maximizing the use of distributed PV power in micro-grid, and improve the power quality, an optimal energy storage configuration strategy is proposed, which takes many factors into account, such as the topology of micro-grid, the change of irradiance, the load fluctuation and the cable. The strategy can optimize the energy storage allocation model to minimize the storage power capacity and optimize the node configuration.The key electrical nodes are identified by using the sensitivity coefficient of the voltage, and then the model is optimized to simplify calculation. Finally, an example of the European low-voltage micro-grid and a micro-grid system in the laboratory is used to verify the effectiveness of the proposed method.The results show that the proposed method can optimize the allocation of capacity and the node of the energy storage system.

Equivalent Method of Integrated Power Generation System of Wind, Photovoltaic and Energy Storage in Power Flow Calculation and Transient Simulation

针对工程实际开展风光储联合发电系统在潮流计算和机电暂态仿真中的等值方法研究，旨在为大容量风光储联合发电系统的并网仿真分析奠定基础。将潮流计算的等值分为单元机组和集电系统2部分来研究。单元机组等值采用根据不同控制模式选取不同节点类型的方法，针对集电系统等值提出基于损耗不变原则的方法。等值模型和详细模型的算例结果表明，潮流计算等值方法具有较好的精度。在机电暂态仿真动态等值中，基于实际工程计算的最严重工况分析原则，提出运行在满出力点的单机“倍乘”等值模型，为工程计算中的风光储联合发电系统动态等值提供了一种解决方案。

Composition Modeling and Equivalence of an Integrated Power Generation System of Wind, Photovoltaic and Energy Storage Unit

利用间接组合建模的方法,在建立典型的双馈风机、光伏发电单元和储能单元的装置级机电暂态模型基础上,采用等值方法建立三者电站级的机电暂态模型,最终通过组合建模得到了风光储联合发电系统的机电暂态模型。在大型电力系统分析软件包的PSD-BPA暂态稳定程序中实现了风光储联合发电系统的仿真功能,通过典型算例和张北＂国家风光储输示范工程＂的仿真分析验证了模型的正确性,为风光储联合发电系统的并网研究提供了分析手段。

A novel coordinated control strategy considering power smoothing for a hybrid photovoltaic/battery energy storage system

This work presents a novel coordinated control strategy of a hybrid photovoltaic/battery energy storage(PV/BES) system. Different controller operation modes are simulated considering normal, high fluctuation and emergency conditions. When the system is grid-connected, BES regulates the fluctuated power output which ensures smooth net injected power from the PV/BES system. In islanded operation, BES system is transferred to single master operation during which the frequency and voltage of the islanded microgrid are regulated at the desired level. PSCAD/EMTDC simulation validates the proposed method and obtained favorable results on power set-point tracking strategies with very small deviations of net output power compared to the power set-point. The state-of-charge regulation scheme also very effective with SOC has been regulated between 32% and 79% range.

Optimal configuration for photovoltaic storage system capacity in 5G base station microgrids

Base station operators deploy a large number of distributed photovoltaics to solve the problems of high energy consumption and high electricity costs of 5G base stations.In this study,the idle space of the base station’s energy storage is used to stabilize the photovoltaic output,and a photovoltaic storage system microgrid of a 5G base station is constructed.Aiming at the capacity planning problem of photovoltaic storage systems,a two-layer optimal configuration method is proposed.The inner layer optimization considers the energy sharing among the base station microgrids,combines the communication characteristics of the 5G base station and the backup power demand of the energy storage battery,and determines an economic scheduling strategy for each photovoltaic storage system with the goal of minimizing the daily operation cost of the base station microgrid.The outer model aims to minimize the annual average comprehensive revenue of the 5G base station microgrid,while considering peak clipping and valley filling,to optimize the photovoltaic storage system capacity.The CPLEX solver and a genetic algorithm were used to solve the two-layer models.Considering the construction of the 5G base station in a certain area as an example,the results showed that the proposed model can not only reduce the cost of the 5G base station operators,but also reduce the peak load of the power grid and promote the local digestion of photovoltaic power.

Economic Feasibility of Micro-Grid Energy Storage and the Impact of Emerging Technologies on Its Viability

Currently, energy storage devices show great promise when used in micro-grid applications, and further advancements in this technology will lead to economically-viable and environmentally-friendly solutions in regards to residential energy consumption. Creating a 21st-century energy infrastructure will be fundamental to society in the coming decades and ensuring cost-effective means of doing so will lessen the burden on the average consumer. While current research has focused primarily on fundamental battery research, the economic viability for the average American consumer has been neglected in many cases. In this work, current and future methods of home energy storage are analyzed via a thorough literature review and the most promising current and near-future methods are explored. These methods include current Lithium-Ion Battery (LIB) technology, reused LIB from Electric Vehicles (EVs), Lithium Nickel manganese cobalt oxides (NMC) cathode composition and the utilization of silicon as an anode material. After the potential of these technologies is explored, an analysis of their economic viability for the average consumer is presented. The literature review demonstrates that the current state of LIB is very close to economically feasible;reused LIBs are less viable than new LIBs, and future LIB compositions show great promise in viability. This shows that within the next decade, micro-grids will be a reasonable alternative to utility energy harnessing techniques, and a major step towards green energy consumption will be realized. Hybrid energy storage systems, on the other hand, are shown to be economically infeasible, in the near future, due to their high cost per kWh. However, when analyzing the energy storage capabilities of these systems, it is shown that they may be vital in updated energy infrastructure and provide a cost saving.

Deep reinforcement learning for online scheduling of photovoltaic systems with battery energy storage systems

A new online scheduling algorithm is proposed for photovoltaic(PV)systems with battery-assisted energy storage systems(BESS).The stochastic nature of renewable energy sources necessitates the employment of BESS to balance energy supplies and demands under uncertain weather conditions.The proposed online scheduling algorithm aims at minimizing the overall energy cost by performing actions such as load shifting and peak shaving through carefully scheduled BESS charging/discharging activities.The scheduling algorithm is developed by using deep deterministic policy gradient(DDPG),a deep reinforcement learning(DRL)algorithm that can deal with continuous state and action spaces.One of the main contributions of this work is a new DDPG reward function,which is designed based on the unique behaviors of energy systems.The new reward function can guide the scheduler to learn the appropriate behaviors of load shifting and peak shaving through a balanced process of exploration and exploitation.The new scheduling algorithm is tested through case studies using real world data,and the results indicate that it outperforms existing algorithms such as Deep Q-learning.The online algorithm can efficiently learn the behaviors of optimum non-casual off-line algorithms.

Dynamic optimal allocation of energy storage systems integrated within photovoltaic based on a dual timescale dynamics model

Energy storage systems(ESSs)operate as independent market participants and collaborate with photovoltaic(PV)generation units to enhance the flexible power supply capabilities of PV units.However,the dynamic variations in the profitability of ESSs in the electricity market are yet to be fully understood.This study introduces a dual-timescale dynamics model that integrates a spot market clearing(SMC)model into a system dynamics(SD)model to investigate the profit-aware capacity growth of ESSs and compares the profitability of independent energy storage systems(IESSs)with that of an ESS integrated within a PV(PV-ESS).Furthermore,this study aims to ascertain the optimal allocation of the PV-ESS.First,SD and SMC models were set up.Second,the SMC model simulated on an hourly timescale was incorporated into the SD model as a subsystem,a dual-timescale model was constructed.Finally,a development simulation and profitability analysis was conducted from 2022 to 2040 to reveal the dynamic optimal range of PV-ESS allocation.Additionally,negative electricity prices were considered during clearing processes.The simulation results revealed differences in profitability and capacity growth between IESS and PV-ESS,helping grid investors and policymakers to determine the boundaries of ESSs and dynamic optimal allocation of PV-ESSs.

Pumped hydro energy storage and 100 % renewable electricity for East Asia

Rapid cost reductions have led to the widespread deployment of renewable technologies such as solar photovoltaics(PV)and wind globally.Additional storage is needed when the share of solar PV and wind in electricity production rises to 50–100%.Pumped hydro energy storage constitutes 97%of the global capacity of stored power and over 99%of stored energy and is the leading method of energy storage.Off-river pumped hydro energy storage options,strong interconnections over large areas,and demand management can support a highly renewable electricity system at a modest cost.East Asia has abundant wind,solar,and off-river pumped hydro energy resources.The identified pumped hydro energy storage potential is 100 times more than required to support 100%renewable energy in East Asia.

Reliability Assessment Considering the Coordination of Wind Power, Solar Energy and Energy Storage

风光储联合发电系统并网后必须采取策略与系统之间实现协调调度与运行才可在保证可靠性的前提下最大化利用可再生能源，但现有的可靠性评估中还缺少对大规模风光储联合发电系统协调运行的考虑。针对此问题，基于序贯蒙特卡罗仿真方法，建立了风电、光伏和储能系统的发电可靠性评估模型，并提出了新的协调调度策略。模型综合考虑了风速、太阳光辐照度、环境温度以及2种新能源发电技术的能量变换特性和储能系统的充放电约束等因素。这些模型被应用到IEEERTS79中，通过在Matlab中编制程序进行仿真计算，考察不同的协调运行策略、联合发电系统容量配置以及储能特性对于系统裕度的影响。评估结果可为联合发电系统并网规划与设计提供参考。

Present status of pumped hydro storage operations to mitigate renewable energy fluctuations in Japan

This paper focuses on pumped hydro energy storage(PHES)plants’current operations after electricity system reforms and variable renewable energy(VRE)installations in Japan.PHES plants have historically been developed to create electricity demand at night in order to operate base load power plants,such as nuclear power plants,in stable conditions.Therefore,many PHES plants are located midway between nuclear power plants and large demand areas.However,all nuclear power plants had to–at least temporarily–shut down after the Great East Japan Earthquake followed by a nuclear accident at Fukushima Daiichi in 2011,and renewable energy power plants have been deployed rapidly after the introduction of a feed-in-tariff(FIT)scheme.Therefore,PHES plants are being used to mitigate fluctuations of VRE,especially in areas where renewable energy has been significantly installed.The daily highest capacity ratio of PHES plants in Kyushu area has recorded three times higher than it in the other areas where the past operating mode is still conducted.But those operations on PHES plants are simply followed as a dispatch rule of the Organization for Crossregional Coordination of Transmission Operators(OCCTO),market-based operations have not been conducted enough yet.The market design shall be changed to harmonize VRE installation and PHES plants’operations are necessary to make the transition from the past operating mode of PHES plants across Japan.

Multifunction Battery Energy Storage System for Distribution Networks

Battery Energy Storage System(BESS)is one of the potential solutions to increase energy system flexibility,as BESS is well suited to solve many challenges in transmission and distribution networks.Examples of distribution network’s challenges,which affect network performance,are:(i)Load disconnection or technical constraints violation,which may happen during reconfiguration after fault,(ii)Unpredictable power generation change due to Photovoltaic(PV)penetration,(iii)Undesirable PV reverse power,and(iv)Low Load Factor(LF)which may affect electricity price.In this paper,the BESS is used to support distribution networks in reconfiguration after a fault,increasing Photovoltaic(PV)penetration,cutting peak load,and loading valley filling.The paper presents a methodology for BESS optimal locations and sizing considering technical constraints during reconfiguration after a fault and PV power generation changes.For determining themaximumpower generation change due to PV,actual power registration of connected PV plants in South Cairo Electricity Distribution Company(SCEDC)was considered for a year.In addition,the paper provides a procedure for distribution network operator to employ the proposed BESS to perform multi functions such as:the ability to absorb PV power surplus,cut peak load and fill load valley for improving network’s performances.The methodology is applied to a modified IEEE 37-node and a real network part consisting of 158 nodes in SCEDC zone.The simulation studies are performed using the DIgSILENT PowerFactory software andDPL programming language.The Mixed Integer Linear Programming optimization technique(MILP)in MATLAB is employed to choose the best locations and sizing of BESS.

基于EnergyPlus和Jeplus+EA联合模拟的建筑围护结构及光储系统协同优化研究

建筑本体和可再生能源系统的协同作用对于降低建筑碳排放具有重要意义.以北京某办公建筑为例,基于NSGA-Ⅱ的优化算法,以运行阶段碳排放和生命周期成本为目标函数,以热舒适为约束条件,利用EnergyPlus和Jeplus+EA软件进行联合仿真,开展建筑围护结构和光储系统的协同优化研究.结果表明:配置光储系统可较大程度降低建筑电网购电量及运行阶段碳排放,虽然生命周期成本会略有增加,但其减碳效果,大于单纯依靠围护结构性能提升的传统做法;尽可能利用建筑空间配置光伏对减少碳排放及生命周期成本都是有利的;通过软件联合模拟可实现建筑围护结构和光储系统的协同优化,且较于各自独立优化,能取得更好的设计方案.

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.