Sherif A. Abdelrazek

Integrated PV Capacity Firming and Energy Time Shift Battery Energy Storage Management Using Energy-Oriented Optimization

In this paper, we propose a complete active-power-management scheme for the control of battery energy-storage systems (BESSs) for two main applications: 1) photovoltaic (PV) capacity firming and 2) energy time shift (ETS). In the proposed approach, first two control algorithms are designed to provide active-power set points to BESS for the above applications. Then, an optimization routine for integrating these controllers is designed. The proposed approach uses an energy-conservation method to integrate these two applications of energy-storage system. The designed algorithm was tested on a transient simulation platform and then implemented on a 720-node actual power distribution feeder. The main advantage of the proposed method is that the algorithm can be used to optimize multiple functions and perform simultaneous control of BESS.

A novel integrated optimal battery energy management control architecture considering multiple storage functions

In this paper we proposes a complete battery energy storage management scheme that include three functions of energy storage a) energy arbitrage b) PV smoothing c) voltage regulation. The proposed methodology enhances coordination of ancillary services applications like voltage support with Energy Time Shift (ETS) and Renewables Capacity Firming (RCF) applications and thus provides much higher value for battery energy storage devices. The design is tested on an EMTP simulation platform which indicates that the proposed architecture provides optimal control strategy for grid level storage for various functions proposed.

Integrated control of battery energy storage management system considering PV capacity firming and energy time shift applications

This paper present a complete battery energy storage management scheme to maximize potential value that can be brought forth to medium voltage feeders. In general, the potential performance benefits produced by possible energy storage applications include improved system reliability, dynamic stability, enhanced power quality, transmission capacity enhancement and area protection. Here we propose a unique control algorithm that enhances coordination of Renewables Capacity Firming and Energy Time Shift (ETS) applications. Optimization of control parameters and set points are considered for management between the mentioned applications with the help of the proposed architecture. The design is tested on an EMTP® simulation platform and the results indicates that the proposed architecture provides capability to include multiple functionality of the energy storage device maximizing the value of the energy storage in power grid.

An approach for control of battery energy storage management systems considering multiple functions

This paper present a complete electrochemical energy storage management scheme to maximize potential value that can be brought forth to medium voltage feeders. In general, the potential performance benefits produced by possible energy storage applications include improved system reliability, dynamic stability, enhanced power quality, transmission capacity enhancement and area protection. Here we propose a unique control algorithm that enhances coordination of ancillary services applications mainly voltage support along with renewables capacity firming. Optimization of control parameters and set points are considered for management between the mentioned applications. The design is tested on an Electro Magnetic Transient Program (EMTP) simulation platform which shows that the method performs both the functions.

Integrated optimal control of battery energy storage management system for energy management and PV Capacity Firming

In this paper and integrated battery energy management algorithm for optimal control of power and energy of a medium voltage feeder is discussed. The proposed unique control algorithm enhances coordination of two main storage applications, viz., Photo-Voltaic Capacity Firming (PVCF) and electric Energy Time Shift (ETS). Optimization of control parameters and set points are considered for management between the mentioned applications. Practical implementation results on a utility feeder are discussed.

A Weather-Based Optimal Storage Management Algorithm for PV Capacity Firming

This paper presents an optimal battery management algorithm for photovoltaic (PV) stations capacity firming using dynamic programming-based optimization and control architecture. The objective is to manage the output of battery energy storage system (BESS) so that PV station output swings are reduced significantly. First, BESS and PV station located in a medium-voltage distribution network on a North American power grid is modeled along with the reduced-order feeder model. Then, the proposed algorithm is designed and implemented on the power grid distribution feeder based on the feeder data streamed through utility communication infrastructure to the research laboratory. The theoretical formulation, simulation, and implementation results are discussed in detail in this paper.

Coordinated voltage control strategy for voltage regulators and voltage source converters integrated distribution system

Modern day distribution systems (DS) is now hosting increasing number of both small and large scale distributed energy resources (DERs). Even though these DERs have capability to support reactive power along with the active power they provide, practitioners are still hesitant in utilizing the reactive power potential from these DERs. One of the major concerns for the distribution system operator is the coordination between the existing voltage regulators and the inverter based reactive power sources in the DS. This paper presents a situational aware and agnostic coordinated control strategy for voltage regulation in the DS considering power electronic based inverters as reactive power sources that work in conjunction with the existing legacy controllers for an overall value based voltage regulation of the entire feeder. It has also been shown that this can be achieved without major changes in the communication framework currently utilized by the utility (another concern for DS operator). The proposed control technique has been tested in the field verified model of a real feeder. Results show that the proposed coordination approach has a major economic as well and power quality benefits in the operation of DS.

Operational cost value assessment and value based stacked energy storage management for active power distribution systems

In this paper, a formal procedure to evaluate the operational value of ancillary services provided by battery energy storage systems is presented along with a methodology on how to schedule the battery considering maximum benefits. The ancillary services considered are photovoltaic (PV) power output smoothing, voltage support and energy time shift (ETS). The benefits provided by energy storage applications are quantified in terms of monetary value. First, the issues related to such value studies are mentioned and a method has been proposed to resolve these issues. Second, utilizing the value information, an optimization method is developed to modify the algorithms for energy storage applications. It has been concluded that monetary value of different energy storage applications provides additional information that can be used schedule energy storage applications to yield maximum cost benefit of the applications. Results obtained using the field validated simulation model show the potential of proposed method.

Weather forecasting based intelligent distribution feeder load prediction

Increased penetration of renewable energy based generators throughout modern distribution networks makes it crucial to seek elevated levels of accuracy in forecasting methods. This paper presents a new load forecasting method for residential distribution feeders. It uses, load time series decomposition to distinguish between all types of loads and events on feeder. Then, a generalized regression neural network (GRNN) is used to fit the weather variables for weather dependent load component. Proposed algorithm has been evaluated on residential feeder. Results show very accurate prediction for active power as well as the lighting load peaks.

An optimal storage management algorithm for PV capacity firming based on weather patterns

This paper presents an optimal battery management and control algorithm for Photo-Voltaic (PV) stations capacity firming. The proposed method uses a dynamic programming based optimization and control architecture to manage the output of Battery Energy Storage System (BESS) so that PV station output swings are reduced significantly. First, Battery Energy Storage System (BESS) and PV station located in a medium voltage distribution network on a North American Power grid is modeled along with the reduced order feeder model. Then, the proposed algorithm is implemented on the distribution feeder based on the feeder data streamed through utility communication infrastructure to the control station. The theoretical formulation, simulation and implementation results are discussed in detail in this paper.