Smart Grid

The electric power grid is undergoing a transformation as we seek to reduce our environmental footprint and reliance on foreign fuels while simultaneously electrifying transportation and heating. These concerns have led to a focused effort towards a high penetration of distributed energy resources (DERs), which include distributed generation (DG), demand response (DR), and storage. These small-scale resources can provide various services to the grid including voltage support from clusters of DERs, reduced line congestion from better generation/load management, lower operating costs by using cheaper resources (ex. renewables), and demand flexibility by enabling DR throughout the distribution grid. Technologies such as storage and price-responsive demand systems are also being adopted at an accelerating pace, in an attempt to reduce operational costs and manage increasingly dynamic electrical system conditions. Sensing and control systems need to be revisited to efficiently integrate these new technologies, transforming our energy systems into smart grids. The following are specific topics that are currently under investigation:

  • Distributed Optimization Algorithm for Smart Distribution Grids
  • Retail Market Mechanisms for Distribution Grids
  • Transactive Control of Electric Railway Systems
  • Hierarchical local electricity markets
  • Efficient Ultra-coordinated IoT networks for Grid Resilience

  • Distributed Optimization Algorithm for Smart Distribution Grids

    Convergence Results for PAC The modern grid is characterized by the high penetration of Distributed Energy Resources (DERs), including generation units, flexible consumption units (demand response), and storage, which are largely owned by different third-party agents. To take advantage of these distributed resources and maintain privacy for individual agents, a fully distributed control architecture is necessary. This corresponds to having a fully distributed optimization algorithm, which will solve the Optimal Power Flow (OPF) problem: determining actuation of DERs constrained by power flow physics, grid limits, and meeting electricity demand.

    Atomization Example for PAC

    This project has culminated in the fully distributed Proximal Atomic Coordination (PAC) algorithm, which exhibits similar convergence rates to the popular Alternating Direction Method of Multipliers (ADMM) algorithm (O(1/tau), tau = number of iterations), but has lower communication requirements, shorter iteration time, and most crucially, data privacy between agents is an intrinsic property of PAC.

    An optimization problem over a connected network is decomposed into K different coupled sub-optimization problems. Dependencies between atoms are dealt with by creating local “copies” of variables owned by other atoms, and introducing additional constraints to force these local copies to converge to the real values of the variables. In contrast, ADMM treats dependencies as shared variables between atoms. The dynamics of the PAC algorithm involve the system moving towards feasibility (meeting OPF constraints) and moving towards consistency (local copies = real variables), while trying to minimize a Lagrangian objective function for each agent.

    PAC Algorithm Dynamics

    Future works:
    • Analyze robustness of PAC to cyber-events (failure or attack in communication network)
    • Develop asynchronous PAC variant

    Retail Market Mechanisms for Distribution Grids

    Price Demand Curve showing Inefficiencies

    In the United States, the procurement and integration of distributed generators (DGs) is largely limited to providing ancillary services through participation in the Wholesale Electricity Market (WEM); there is some participation from DR units and storage devices evidenced by FERC order 841. Typically, these DERs must meet minimum size requirements, with some electricity markets not allowing aggregation. As the penetration of DERs increases, specifically renewable generation, demand response, and storage, the WEM alone may not suffice in realizing an efficient and reliable power delivery. A properly designed retail market that oversees the participation of variable scale DERs in the distribution grid and implements a suitable mechanism for their scheduling and compensation is highly necessary.

    High-level approach for Retail Markets

    To address these issues, we have been developing a retail market mechanism which details a real-time pricing scheme for distribution grids in the presence of high DER penetration, enabled by the recently developed distributed optimization algorithm, the proximal atomic coordination algorithm (PAC). We introduce a Distribution System Operator (DSO), which handles market settlements with the WEM on behalf of the distribution grid, charges agents for their consumption, and compensates flexible consumers and generators. By using the retail market, the distribution grid is more efficiently managed, and smaller DERs are able to participate in the WEM by bidding through the DSO. A case study conducted on a distribution grid in Komae City, Tokyo, Japan, shows the retail market mechanism results in projected savings over a 24-hour period for the DSO.

    Retail Market Mechanism Future works:
    • Relaxing assumption that the load/generation profile of DSO is not binding at each WEM clearing
    • Designing a bidding mechanism between the DSO and WEM
    • Multi-period market settlements
    • Incorporating storage units and appropriate compensation
    • Better modeling of DR contracts

    Transactive Control of Electric Railway Systems

    Transactive Control of Electric Railway Systems

    Electric railway systems are a major untapped source of demand-side flexibility in electricity networks. Electric trains can both demand power from their traction system for locomotion and inject power back into the electricity network through regenerative braking, virtually enabling them to store electricity in the form of kinetic energy. The power profile of a train along a route is in many cases determined by the conductor based on training and experience, attempting to meet a given schedule with little regard to the varying cost of power along the route.

    We propose an alternative operation methodology that solves the energy cost minimization problem, taking into account the scheduling and operational constraints of the railway system. In addition, we provide a control mechanism to coordinate multiple trains and rail-side distributed energy resources (DERs) tied to the electric railway, which dynamically change the price of electricity along the track, ultimately enabling the operational cost minimization of the system. The proposed transactive control methodology has been tested in numerical simulations of the high-speed Amtrak Acela service which operates along the northeast United States suggesting savings on the order of 10% of the annual energy costs of the operator.

    Hierarchical local electricity markets

    With increasing penetration of distributed energy resources (DERs) such as renewables, storage and flexible loads in the distribution system, it is critical to design market structures that enable their smooth integration at the grid edge - to balance variable supply and demand, and increase the utilization of clean, renewable energy sources while maintaining affordability, reliability, and improving resilience. This talk focuses on the optimal design of hierarchical retail local electricity market (LEM) structures to facilitate DER integration, increase market participation of customers and prosumers, and leverage them to provide valuable grid services. The increasing proliferation of smart inverters allows us to control reactive power injections in addition to real power, by varying the power factor. A suite of retail markets is proposed for primary and secondary feeders in the distribution network, at the medium and low voltage levels respectively. The Primary Market (PM) is overseen by a distribution system operator which also interacts with the transmission system operator in the wholesale energy market. Within the Secondary Market (SM), DERs and prosumers are aggregated and represented by entities known as DER-coordinated assets (DCA). The SM operator (SMO) coordinates these DCAs to increase grid efficiency and resiliency, while accurately compensating DERs and prosumers for their flexibility through spatial-temporal price differentiation resulting in localized real-time tariffs.

    Retail Market Mechanism

    Our novel LEM architecture can be used to optimally schedule and coordinate DER injections across the distribution grid, via price-based market mechanisms instead of direct control or dispatch of DERs by the grid operator. We also show how the LEM can provide distribution grid services, specifically Volt-VAR control (VVC) for voltage regulation and conservation voltage reduction. We extend our market beyond radial, balanced systems to unbalanced, multi-phase and meshed networks by using a Current-Injection based linear model for solving AC Optimal Power Flow at the primary level, employing McCormick envelopes convex relaxations. A distributed Proximal Atomic Coordination algorithm is used for PM clearing which preserves privacy, reduces communication requirements, and improves computational tractability. We also introduce 3-phase pricing at both the SM and PM, to motivate how we can determine the value of such grid services in real-time energy markets based on an optimization framework. We disaggregate the distribution locational marginal prices (d-LMP) and local retail tariffs among different SMOs and DCAs, respectively, and decompose their components arising from economic objectives like maximizing social welfare and minimizing costs versus grid objectives like minimizing line losses and voltage profile deviations.

    Efficient Ultra-coordinated IoT networks for Grid Resilience

    The electricity landscape is undergoing a rapid transformation, especially at the grid edge. With every end-user having just 5 connected devices, the grid infrastructure will consist of 8 billion digital nodes. Many of these nodes are capable of sensing, computing, and communicating, thereby possibly enabling controlling and monitoring disturbed generation and consumption at time-scales and line-scales never envisioned before. Motivated by issues of availability, latency and privacy, Internet of Technology (IoT) involves the deployment of devices capable of performing local computations on data they hold to provide services to end users. In particular, IoT technologies have enabled key connectivity between distributed energy resources (DER) along critical energy supply corridors and within critical facilities. The ultimate goal of this project is to realize a resilient grid edge for the electricity grid infrastructure by leveraging the connectivity of IoT devices together with various grid assets. An architecture EUREICA (Efficient Ultra Resilient IoT-Coordinated Assets), is being developed that pertains to a distributed networking of IoT and grid assets leading to enhanced power system resilience. The objective is to create situational awareness to the operator and resilience- and commitment-scores of the assets. These scores will be utilized to develop reconfiguration paths for enhanced resilience. A market pathway is being put together for the grid edge to enable the computation of the resilience and commitment scores. Tools related to cyber-physical security, distributed optimization, and game theory are being analyzed and synthesized to determine how Situational Awareness, Resilience Scores, and Commitment Scores can be calculated. Several challenges remain in the form developing scenarios that cause the grid to go from normal to alert to in-extremis states. The specific roles of various operators in assessing the vulnerabilities across a large grid need to be determined.