Designing pricing strategies for coordination of networked distributed energy resources Bahman Gharesifard * Tamer Ba¸ sar ** Alejandro D. Dom´ ınguez-Garc´ ıa ** * Department of Mathematics and Statistics, Queen’s University, Kingston, Canada, bahman@mast.queensu.ca. ** Coordinated Science Lab, University of Illinois, Urbana-Champaign, USA, basar1@illinois.edu, aledan@illinois.edu. Abstract: We study the problem of aggregator’s mechanism design for controlling the amount of active, or reactive, power provided, or consumed, by a group of distributed energy resources (DERs). The aggregator interacts with the wholesale electricity market and through some market-clearing mechanism is incentivized to provide (or consume) a certain amount of active (or reactive) power over some period of time, for which it will be compensated. The objective is for the aggregator to design a pricing strategy for incentivizing DERs to modify their active (or reactive) power consumptions (or productions) so that they collectively provide the amount that the aggregator has agreed to provide. The aggregator and DERs’ strategic decision-making process can be cast as a Stackelberg game, in which aggregator acts as the leader and the DERs are the followers. In previous work [Gharesifard et al., 2013b,a], we have introduced a framework in which each DER uses the pricing information provided by the aggregator and some estimate of the average energy that neighboring DERs can provide to compute a Nash equilibrium solution in a distributed manner. Here, we focus on the interplay between the aggregator’s decision-making process and the DERs’ decision-making process. In particular, we propose a simple feedback-based privacy-preserving pricing control strategy that allows the aggregator to coordinate the DERs so that they collectively provide the amount of active (or reactive) power agreed upon, provided that there is enough capacity available among the DERs. We provide a formal analysis of the stability of the resulting closed-loop system. We also discuss the shortcomings of the proposed pricing strategy, and propose some avenues of future work. We illustrate the proposed strategy via numerical simulations. Keywords: Power systems, distributed energy resources, energy market, distributed control, game theory. 1. INTRODUCTION Power distribution networks are undergoing radical trans- formation in structure and functionality. These trans- formations are enabled by the increased reliance on ad- vanced communications and controls, as well as by the increased penetration of renewable-based electricity gen- eration resources (e.g., solar photovoltaics (PV) installa- tions), controllable loads (e.g., thermostatically-controlled loads (TCLs)), and storage-capable loads (e.g., plug-in electric vehicles (PEVs)). These generation resources and loads are commonly referred to as distributed energy resources (DERs), and, if properly controlled, they can be utilized to provide ancillary services. For example, PEVs and TCLs can be utilized to provide frequency regulation services [Guille and Gross, 2009, Callaway and Hiskens, 2012]. However, in order to enable the added function- ality that DERs may provide, it is necessary to develop appropriate control mechanisms. In this paper, we address this problem and propose a framework for controlling the power provided/consumed by DERs, and perhaps also the reactive power if the objective is to regulate voltage. ⋆ This work was supported in part by a grant through the Informa- tion Trust Institute of the University of Illinois; and by NSF under grant ECCS-CPS-1135598. Focusing on controllable loads, their control is currently achieved through demand response programs in which participants sign a contract with an aggregating entity— the demand response provider—so that their electrical energy consumption can be curtailed by the aggregator in response to market prices or in order to ensure reliable operation of the system, in exchange for lower electricity prices. In this work, we also consider an aggregating entity that will interact with the wholesale electricity market and, through pricing, will incentivize DERs to provide/consume active (or reactive) power in exchange for monetary benefits. As an example, a household with a PV system (with a reactive power capable power electron- ics grid interface) and a TCL might choose to offer these two resources to an aggregator so that the PV system is utilized to provide reactive power for voltage control, and the TCL is utilized to provide frequency regulation. In this sense, the interplay between the DERs and the aggregator can be modeled as a Stackelberg game, where the aggregator acts as the leader and the DERs are the followers. 1.1 Literature Review Game-theoretic models have been used recently for study- ing energy markets (see, e.g., [Fan, 2012, Kiani and An- Preprints of the 19th World Congress The International Federation of Automatic Control Cape Town, South Africa. August 24-29, 2014 Copyright © 2014 IFAC 5405