Energy Management Algorithm for Resilient Controlled Delivery Grids

Resilience of the power grid is most challenged at power blackouts since the issues that led to it may not be fully resolved by the time the power is back. In this paper, a Real-Time Energy Management Algorithm (RTEMA) has been developed to increase the resilience of power systems based on the controlled delivery grid (CDG) concept. In a CDG, loads communicate with a central controller, periodically sending requests for power. The central controller runs an algorithm, based on which it may decide whether to grant the requested energy fully or partially. Therefore, the CDG limits loads discretionary access to electric energy until all problems are resolved. The developed algorithm aims at granting most or all of the requested loads, while maintaining the health of the power system (i.e. the voltage at each bus, and the line loading are within acceptable limits), and minimizing the overall losses. An IEEE 30-bus standard Test Case, encountering a blackout condition, with high penetration of microgrids, has been used to test the developed algorithm. Results proved that the developed algorithm with the CDG have the potential to substantially increase the resilience of power systems

Optimal Microgrids Placement in Electric Distribution Systems Using Complex Network Framework

This paper provides a new approach to find the optimal location for Microgrids (MGs) in electric distribution systems using complex network analysis. An optimal location in this paper refers to a location that would result in increased grid resilience, reduced power losses, less line loading, higher voltage stability and secured supply to critical loads during power outage. The criteria used to find the optimal placement of MGs were based on the centrality analysis adopted from complex network theory, the center of mass concept used in physics, and the controlled delivery grid (CDG) concept. An IEEE 30-bus system was used as a case study. Results using MATLAB and PowerWorld show the effectiveness of the proposed methodology to be used for MG placement

Applications of Complex Network Analysis in Electric Power Systems

This paper provides a review of the research conducted on complex network analysis (CNA) in electric power systems. Moreover, a new approach is presented to find optimal locations for microgrids (MGs) in electric distribution systems (EDS) utilizing complex network analysis. The optimal placement in this paper points to the location that will result in enhanced grid resilience, reduced power losses and line loading, better voltage stability, and a supply to critical loads during a blackout. The criteria used to point out the optimal placement of the MGs were predicated on the centrality analysis selected from the complex network theory, the center of mass (COM) concept from physics, and the recently developed controlled delivery grid (CDG) model. An IEEE 30 bus network was utilized as a case study. Results using MATLAB (MathWorks, Inc., Nattick, MA, USA) and PowerWorld (PowerWorld Corporation, Champaign, IL, USA) demonstrate the usefulness of the proposed approach for MGs placement

A Case Study on Grid Impacts of Electric Vehicles on New York City Power Grid

The U.S. electric power industry is anticipating a huge increase in electricity demand in the future due to reformation of the transportation industry. In this work, we focus on electric cars and their impact on the transportation industry as well as the electric grid. The increase in number of electric cars over the years and their growing number indicates that in the future, transportation means are going to largely depend upon electricity to achieve cost and environmental benefits. In other words, in future, the transportation will be impacting the electric grid and vice versa. The surge in electric vehicles on streets particularly in New York City requires the charging infrastructure to support the electricity demand, and mandates proper planning for the electric power grids to keep them upgraded and resilient enough to support the growth in electric vehicles load. In this thesis, the historical minimum and peak load demand data of areas served by Consolidated Edison, an energy company, in New York City have been collected, processed and analyzed to analyze the performance of the future electric grid. The available data of electric vehicles and parking spaces in different regions of New York City were analyzed to study the impact of electric vehicles on future power infrastructure in the City. Also, the charging and parking behavior of vehicles in New York City was analyzed to determine how the time of charging will impact the electricity demand at the different hours of the day at different locations in New York City, and to find ways to minimize the demand in areas where the electric grid network is congested. It was also concluded that in the future, after phasing out of a portion of the gasoline fleets, electric vehicles will be able help to reduce the greenhouse gasses and conserve the environment and help the City and State of New York’s initiatives to achieve their goals of sustainability. Last but not least, more than eighty percent of the New York City electric infrastructure is underground, which means when the demand in peak hours of summer requires upgrading and increasing the feeder capacity, it will require massive capital investment. So, electric vehicles can be used as Energy Storage Resources and can be utilized if needed to shave the peak demand. The data has been analyzed to find out the kind of infrastructure required and the potential locations in different areas of New York City to use the electric vehicles as distributed energy storage resources

Analysis of the benefits of Regenerative Braking in Urban Railway Traction System

Increasing environmental awareness and the requirement for lower project costs is forcing transit system suppliers to think more innovatively and engineer more accurately to strengthen their competitive edge. Of late, clients more often desire a system that is optimized to minimize the energy consumed during operation; a requirement that is often imposed upon transit system suppliers through financially binding energy commitments. Electric rail transit systems are large consumers of energy. In trains with regenerative braking capability, a fraction of the energy used to power a train is regenerated during braking. This regenerated energy, if recuperated and reused, can result in economic as well as technical merits. One of the ways that this could be achieved is with the implementation of Wayside Energy Storage System (WESS). In addition to reducing energy consumption, energy storage systems can be operated to regulate system voltage levels, provide backup power in the event of a utility power outage, and relieve demand on the utility during the costlier operating periods. This dissertation presents a stacked-benefits analysis of regenerative energy and wayside energy storage for New York City Transit (NYCT), and examines how the electric utility and the transit system can collaborate to gain the best value of energy storage

ICT-Enabled Control and Energy Management of Community Microgrids for Resilient Smart Grid Operation

Our research has focused on developing novel controllers and algorithms to enhance the resilience of the power grid and increase its readiness level against major disturbances. The U.S. power grid currently encounters two main challenges: (1) the massive and extended blackouts caused by natural disasters, such as hurricane Sandy. These blackouts have raised a national call to explore innovative approaches for enhanced grid resiliency. Scrutinizing how previous blackouts initiated and propagated throughout the power grid, the major reasons are lack of situational awareness, lack of real-time monitoring and control, underdeveloped controllers at both the transmission and distribution levels, and lack of preparation for major emergencies; and (2) the projected high penetration of renewable energy resources (RES) into the electric grid, which is mainly driven by federal and state regulatory actions to reduce GHG emissions from new and existing power plants, and to encourage Non Wire Solutions (NWS). RESs are intermittent by nature imposing a challenge to forecast load and maintain generation/demand balance. The conceived vision of the smart grid is a cyber-physical system that amalgamates high processing power and increased dependence on communication networks to enable real-time monitoring and control. This will allow for, among other objectives, the realization of increased resilience and self-healing capabilities. This vision entails a hierarchical control architecture in which a myriad of microgrids, each locally controlled at the prosumer level, coordinates within the distribution level with their correspondent distribution system operator (i.e. area controllers). The various area controllers are managed by a Wide Area Monitoring, Protection and Control operator. The smart grid has been devised to address the grid main challenges; however, some technical barriers are yet to be overcome. These barriers include the need to develop new control techniques and algorithms that enable flexible transitions between operational modes of a single controller, and effective coordination between hierarchical control layers. In addition, there is a need to understand the reliability impacts of increased dependence on communication networks. In an attempt to tackle the aforementioned barriers, in my work, novel controllers to manage the prosumer and distribution networks were developed and analyzed. Specifically, the following has been accomplished at the prosumer level, we: 1) designed and implemented a DC MG testbed with minimal off-the-shelf components to enable testing new control techniques with significant flexibility and reconfiguration capability; 2) developed a communication-based hybrid state/event driven control scheme that aims at reducing the communication load and complexity, processor computations, and consequently system cost while maintaining resilient autonomous operation during all possible scenarios including major emergencies; and 3) analyzed the effect of communication latency on the performance of centralized ICT-based DC microgrids, and developed mathematical models to describe the behavior of microgrids during latency. In addition, we proposed a practical solution to mitigate severe impacts of latency. At the distribution level, we: 1) developed a model for an IEEE distribution test network with multiple MGs integrated[AM1] [PL2] ; 2) developed a control scheme to manage community MGs to mitigate RES intermittency and enhance the grid resiliency, deferring the need for infrastructure upgrade; and 3) investigated the optimal placement and operation of community MGs in distribution networks using complex network analysis, to increase distribution networks resilience. At the transmission level (T.L), New York State T.L was modeled. A case study was conducted on Long Island City to study the impact of high penetration of renewable energy resources on the grid resilience in the transmission level. These research accomplishments should pave the way and help facilitate a smooth transition towards the future smart grid.