Coordination Of Distributed Energy Resources Research Articles

A Decentralized Framework for the Optimal Coordination of Distributed Energy Resources

Demand-response aggregators are faced with the challenge of how to best manage numerous and heterogeneous distributed energy resources (DERs). This paper proposes a decentralized methodology for optimal coordination of DERs. The proposed approach is based on Dantzig–Wolfe decomposition and column generation, thus allowing to integrate any type of resource whose operation can be formulated within a mixed-integer linear program. We show that the proposed framework offers the same guarantees of optimality as a centralized formulation, with the added benefits of distributed computation, enhanced privacy, and higher robustness to changes in the problem data. The practical efficiency of the algorithm is demonstrated through extensive computational experiments, on a set of instances generated using data from Ontario energy markets. The proposed approach was able to solve all test instances to proven optimality, while achieving significant speed-ups over a centralized formulation solved by state-of-the-art optimization software.

Distributed Energy Resource Coordination Over Time-Varying Directed Communication Networks

In this paper, we consider the optimal coordination problem for distributed energy resources (DERs), including distributed generators and energy storages. We first propose an algorithm based on the push-sum and gradient method to solve the optimal DER coordination problem in a distributed manner. In the proposed algorithm, each DER only maintains a set of variables and updates them through information exchange with a few neighboring DERs over a time-varying directed communication network. We show that the proposed distributed algorithm with appropriately chosen diminishing step sizes solves the optimal DER coordination problem if the time-varying directed communication network is uniformly jointly strongly connected. Moreover, in order to improve the convergence speed and to reduce the communication burden, we propose an accelerated distributed algorithm with a fixed step size. We show that the new proposed algorithm exponentially solves the optimal DER coordination problem if the cost functions satisfy an additional assumption and the selected step size is less than a certain critical value. Both proposed distributed algorithms are validated and evaluated using the IEEE 39-bus system.

Optimal scheduling of distributed energy resources and responsive loads in islanded microgrids considering voltage and frequency security constraints

Low inertia of distributed energy resources (DERs), high penetration levels of renewable energy sources (RESs), and load demand variations put the islanded microgrids' (MGs) security at the risk of instability. This paper proposes a two-stage stochastic model for coordination of DERs and responsive loads in islanded MGs with regard to voltage and frequency security constraints. Based on the proposed model, scheduling of the controllable units in both supply and demand sides is done in a way not only to maximize the expected profit of the MG operator (MGO) but also to minimize the energy payments of customers under the premise of security and stability of MG. An AC optimal power flow procedure is also used to study the operating condition of the system under uncertainties and to guarantee acceptable nodal voltages and system frequency under different scenarios. The proposed stochastic optimization model is then applied to a typical autonomous MG, and its effectiveness is demonstrated through different scenarios under uncertainties in load consumption and renewable energy resource (RES) productions. Simulation results demonstrate that customers' participation in DR programs has a significant effect on the system's performance in terms of voltage and frequency stability. Moreover, optimal coordination of DERs and responsive loads can increase the expected profit of MGO significantly. The effectiveness of the proposed scheduling approach is verified on an islanded MG test system over a 24-h period.

Distributed Coordination of DERs With Storage for Dynamic Economic Dispatch

This paper considers the dynamic economic dispatch problem for a group of distributed energy resources (DERs) with storage that communicate over a weight-balanced strongly connected digraph. The objective is to collectively meet a certain load profile over a finite time horizon while minimizing the aggregate cost. At each time slot, each DER decides on the amount of generated power, the amount sent to/drawn from the storage unit, and the amount injected into the grid to satisfy the load. Additional constraints include bounds on the amount of generated power, ramp constraints on the difference in generation across successive time slots, and bounds on the amount of power in storage. We synthesize a provably correct distributed algorithm that solves the resulting finite-horizon optimization problem starting from any initial condition. Our design consists of two interconnected systems, one estimating the mismatch between the injection and the total load at each time slot, and another using this estimate to reduce the mismatch and optimize the total cost of generation while meeting the constraints.

Phase Balancing in Power Distribution Network with Data Center

High degree of unbalance in electric distribution feeders can significantly affect power quality, damage electrical equipment, and result in tripping of protective devices. If not properly managed, integration of new data center and distributed energy resources into the power distribution network will exacerbate the problem. This paper proposes a new paradigm which coordinates the operation of data center and distributed energy resources to reduce phase unbalance and improve the reliability and efficiency of electric distribution networks. The coordination scheme is implemented within the framework of a distribution system operator managed electricity market. The proposed phase balancing algorithm with data center is validated using a modified IEEE distribution test feeder. The simulation results show the proposed data center and distributed energy resources coordination scheme not only significantly reduces the degree of unbalance of distribution feeders but also results in sizable reduction in data center electricity costs.

Distributed Optimal Coordination for Distributed Energy Resources in Power Systems

Driven by smart grid technologies, distributed energy resources (DERs) have been rapidly developing in recent years for improving reliability and efficiency of distribution systems. Emerging DERs require effective and efficient coordination in order to reap their potential benefits. In this paper, we consider an optimal DER coordination problem over multiple time periods subject to constraints at both system and device levels. Fully distributed algorithms are proposed to dynamically and automatically coordinate distributed generators with multiple/single storages. With the proposed algorithms, the coordination agent at each DER maintains only a set of variables and updates them through information exchange with a few neighbors. We show that the proposed algorithms with properly chosen parameters solve the DER coordination problem as long as the underlying communication network is connected. The simulation results are used to illustrate and validate the proposed method.

A Framework for Evaluating the Resilience of Dynamic Real-Time Market Mechanisms

Fluctuations in renewable generation motivate a need for real-time coordination of distributed energy resources (DERs) such as demand response resources. Dynamic real-time market mechanisms are a promising approach to facilitate coordination of DERs. However, the implementation of such mechanisms over a large geographic region requires communication across networks which can introduce non-negligible latency, congestion, and packet loss. Such network disruptions raise questions regarding grid resilience, especially, when combined with physical outages. In this paper, we propose a framework for evaluating the resilience of dynamic real-time market mechanisms under a variety of network scenarios that are indicative of real-time implementation challenges. We develop a non-dimensional metric, which takes into account the impact of a physical contingency, and can be used to evaluate the ability of a dynamic market mechanism to adapt to and recover from this contingency. We evaluate the resilience of a recently proposed dynamic real-time market mechanism on the IEEE 118-bus system following a single generator outage in the presence of communication outages.