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.

An Analytical Method for Delineating Feasible Region for PV Integration Capacities in Net-zero Distribution Systems Considering Battery Energy Storage System Flexibility

To provide guidance for photovoltaic(PV)system integration in net-zero distribution systems(DSs),this paper proposes an analytical method for delineating the feasible region for PV integration capacities(PVICs),where the impact of battery energy storage system(BESS)flexibility is considered.First,we introduce distributionally robust chance constraints on network security and energy/carbon net-zero requirements,which form the upper and lower bounds of the feasible region.Then,the formulation and solution of the feasible region is proposed.The resulting analytical expression is a set of linear inequalities,illustrating that the feasible region is a polyhedron in a high-dimensional space.A procedure is designed to verify and adjust the feasible region,ensuring that it satisfies network loss constraints under alternating current(AC)power flow.Case studies on the 4-bus system,the IEEE 33-bus system,and the IEEE 123-bus system verify the effectiveness of the proposed method.It is demonstrated that the proposed method fully captures the spatio-temporal coupling relationship among PVs,loads,and BESSs,while also quantifying the impact of this relationship on the boundaries of the feasible region.

Improved Energy Management Strategy for Prosumer Buildings with Renewable Energy Sources and Battery Energy Storage Systems

The concept of utilizing microgrids(MGs)to convert buildings into prosumers is gaining massive popularity because of its economic and environmental benefits.These pro-sumer buildings consist of renewable energy sources and usually install battery energy storage systems(BESSs)to deal with the uncertain nature of renewable energy sources.However,because of the high capital investment of BESS and the limitation of available energy,there is a need for an effective energy management strategy for prosumer buildings that maximizes the profit of building owner and increases the operating life span of BESS.In this regard,this paper proposes an improved energy management strategy(IEMS)for the prosumer building to minimize the operating cost of MG and degradation factor of BESS.Moreover,to estimate the practical operating life span of BESS,this paper utilizes a non-linear battery degradation model.In addition,a flexible load shifting(FLS)scheme is also developed and integrated into the proposed strategy to further improve its performance.The proposed strategy is tested for the real-time annual data of a grid-tied solar photovoltaic(PV)and BESS-powered AC-DC hybrid MG installed at a commercial building.Moreover,the scenario reduction technique is used to handle the uncertainty associated with generation and load demand.To validate the performance of the proposed strategy,the results of IEMS are compared with the well-established energy management strategies.The simulation results verify that the proposed strategy substantially increases the profit of the building owner and operating life span of BESS.Moreover,FLS enhances the performance of IEMS by further improving the financial profit of MG owner and the life span of BESS,thus making the operation of prosumer building more economical and efficient.

Optimal Bidding Strategy for PV and BESSs in Joint Energy and Frequency Regulation Markets Considering Carbon Reduction Benefits

Photovoltaic(PV)and battery energy storage systems(BESSs)are key components in the energy market and crucial contributors to carbon emission reduction targets.These systems can not only provide energy but can also generate considerable revenue by providing frequency regulation services and participating in carbon trading.This study proposes a bidding strategy for PV and BESSs operating in joint energy and frequency regulation markets,with a specific focus on carbon reduction benefits.A two-stage bidding framework that optimizes the profit of PV and BESSs is presented.In the first stage,the day-ahead energy market takes into account potential real-time forecast deviations.In the second stage,the real-time balancing market uses a rolling optimization method to account for multiple uncertainties.Notably,a real-time frequency regulation control method is proposed for the participation of PV and BESSs in automatic generation control(AGC).This is particularly relevant given the uncertainty of grid frequency fluctuations in the optimization model of the real-time balancing market.This control method dynamically assigns the frequency regulation amount undertaken by the PV and BESSs according to the control interval in which the area control error(ACE)occurs.The case study results demonstrate that the proposed bidding strategy not only enables the PV and BESSs to effectively participate in the grid frequency regulation response but also yields considerable carbon emission reduction benefits and effectively improves the system operation economy.

Optimal operation modes of photovoltaicbattery energy storage system based power plants considering typical scenarios

Recent advances in battery energy storage technologies enable increasing number of photovoltaic-battery energy storage systems(PV-BESS)to be deployed and connected with current power grids.The reliable and efficient utilization of BESS imposes an obvious technical challenge which needs to be urgently addressed.In this paper,the optimal operation of PV-BESS based power plant is investigated.The operational scenarios are firstly partitioned using a self-organizing map(SOM)clustering based approach.The revenue optimization model is adopted for the PV-BESS power plants to determine the optimal operational modes under typical conditions for a set of considerations,e.g.power generation revenue,assessing rewards/penalties as well as peak shaving/valley filling revenue.The solution is evaluated through a set of case studies,and the numerical result demonstrates the effectiveness of the suggested solution can optimally operate the BESS with the maximal revenue.

一种复合三端口AC/DC/DC光储并网变换器

为实现分布式光伏发电装置与储能装置的就地接入,复合三端口变换器相较于组合式三端口变换器,具有体积小、成本低、高功率密度等优势。针对现有复合三端口(AC/DC/DC)变换器存在的器件交流环流等问题,该文提出一种新型复合三端口拓扑。该拓扑由含6个开关管的全桥逆变器、1个曲折变压器、2套滤波电感与2个滤波电容组成。其中,工频变副边采用曲折接法,能够在引入第三端口的同时实现交流环流有效抑制与铁芯直流磁通的消除。首先,分析复合拓扑中所含AC/DC、DC/DC变换原理、功率范围及效率等特点,与其他拓扑相比具有更高的效率;其次,分析拓扑控制策略,提出含改进直压环的双环混合电压控制方法;最后,通过基于RT-LAB的控制在环实验与1kW样机实验,验证所提拓扑与策略的有效性与可行性。

一种电网友好型光储分布式电源控制策略

提出一种电网友好型光储分布式电源,采用具有惯性环节的虚拟同步机(virtual synchronous generator,VSG)控制方法作为与电网的接口,并提出了电网频率自适应控制策略,根据电网频率变化区间自适应选择三种运行模式:离网运行模式、并网发电模式、频率调节模式。针对这3种运行模式,分析了虚拟同步发电机的有功–频率环节的传递函数以及虚拟转动惯量对暂态稳定性的影响。为了提高系统并网运行时的暂态稳定性,构造了系统的暂态能量分析函数,分析了扰动发生后系统的暂态能量变化过程,并提出了一种虚拟转动惯量动态调节方法优化系统的暂态控制过程。在搭建的Matlab/Simulink仿真模型中分析了所提的控制策略和方法,并在搭建的10k W VSG实验平台中验证了所提方法的正确性和可行性。

储能型光伏系统功率控制仿真分析

光伏发电系统输出功率易受外部环境的影响,存在诸多不确定因素。该文采用蓄电池储能单元作为光伏并网的能量缓冲装置,以控制并网的功率输出。文中建立了基于等效电路的电池储能光伏并网系统整体动态数学模型,设计相应的控制策略,对系统的输出功率进行控制,并以随机光照强度的扰动为例,对系统输出的电能质量和稳定性进行仿真研究。结果表明,该并网系统灵活性强,能很好实现系统功率可控稳定输出。

基于MMC的光伏发电-电池储能系统控制策略

将模块化多电平(MMC)技术与电池储能相结合,提出了一种基于模块化多电平技术的光伏发电-电池储能系统的拓扑结构,并对该系统的核心环节——基于MMC的电池储能系统(BESS)进行了研究。以功率控制为出发点,分别对BESS交流接口和直流接口的电流控制进行了讨论分析,提出了一种适合于光伏发电-储能一体化系统充电与放电的控制策略。在Matlab/Simulink环境下的仿真证明了相关分析以及控制策略的合理性。