We discuss a framework for coordinating the response of distributed energy resources (DERs) connected to electric power distribution networks to provide frequency regulation services. These resources include plug-in electric vehicles, thermostatically controlled loads, and microturbines. In this framework, we consider an aggregator that participates in the real-time market by submitting an offer to provide frequency regulation services. If the offer is accepted, the aggregator needs to coordinate the response of a set of DERs. The DERs are compensated through bilateral contracts, the terms of which are negotiated in advance. The DER coordination problem the aggregator is faced with is cast as an optimal control problem, and we propose a bilayer framework to obtain a sub-optimal solution. In the first layer, we utilize model-predictive control techniques driven by regulation signal forecasts and parameter estimates to obtain a reference control signal for the DERs. A second control layer provides closed-loop regulation around the reference computed by the top layer, which minimizes the error that arises due to forecast error, plant-model mismatch, and the slower speed of the optimal control.

1 aHughes, Justin, T.1 aDominguez-Garcia, Alejandro, D.1 aPoolla, Kameshwar uhttp://aisel.aisnet.org/hicss-50/es/renewable_resources/3/01430nas a2200157 4500008003900000245003400039210003400073260003700107300001400144520098100158653001301139100001501152700001801167700002201185856006501207 2016 d00aCommunity storage for firming0 aCommunity storage for firming aSydney, AustraliabIEEEc11/2016 a570 - 5753 aWe analyze the benefit of storage capacity sharing for a set of consumers in a community (e.g., an apartment building or an industrial park). Each consumer has its own choice of either installing its own storage system or investing in a shared storage system. More precisely, they will decide on the capacity of the storage system to minimize the installation cost subject to a chance constraint for firming (e.g., to limit the exposure risk to the real time market). If the consumers decide to operate a shared storage system, they must also decide on a scheme to allocate the costs. We formulate the problem as a cooperative game and identify an efficient and stable cost allocation rule. In settings where certain statistical information is private, the cooperative storage sharing game becomes embedded with a non-cooperative information reporting game. We show our proposed cost allocation rule induces all consumers to report their private information truthfully.

10aRM11-0061 aWu, Chenye1 aPorter, Jared1 aPoolla, Kameshwar uhttps://certs.lbl.gov/publications/community-storage-firming01724nas a2200169 4500008003900000245009500039210006900134260003800203300001600241520111500257653001301372100002601385700002101411700002801432700002201460856007201482 2016 d00aA cooperative game for the realized profit of an aggregation of renewable energy producers0 acooperative game for the realized profit of an aggregation of re aLas Vegas, NV, USAbIEEEc12/2016 a5805 - 58123 aThe aggregation of renewable energy has significant potential to mitigate undesirable characteristics such as intermittency and variability and thereby facilitate grid integration. Using cooperative game theory, it has been shown that aggregation is also beneficial for renewable energy producers because they can increase their expected profit by making a coalition, bidding a joint contract that maximizes the expected profit and sharing the profit in a way that keeps the game stable. However, we show that the realized (as opposed to expected) profit of the coalition, using the contract that maximizes the expected profit, cannot be suitably distributed among its members. We propose an alternative coalition contract and prove that it allows for a satisfactory distribution of the realized profit among the coalition members keeping the game stable. We design a new payoff allocation that lies in the core of the game of the realized profit. Finally, we analyze the cost of stabilizing the game by evaluating the loss of expected profit that a coalition incurs by bidding the stabilizing contract.

10aRM11-0061 aChakraborty, Pratyush1 aBaeyens, Enrique1 aKhargonekar, Pramod, P.1 aPoolla, Kameshwar uhttps://certs.lbl.gov/publications/cooperative-game-realized-profit01455nas a2200157 4500008003900000245008100039210006900120260003200189520084900221653001301070100001401083700002101097700002201118700001901140856013801159 2015 d00aCoordination of wind power and flexible load through demand response options0 aCoordination of wind power and flexible load through demand resp aOsaka, JapanbIEEEc12/20153 aWe explore the value of demand response (DR) for enhancing wind power integration. This value is derived through load curtailment to manage the variability of wind power. It increases the opportunity to use wind power and brings economic benefits to the aggregation of the load serving entity (LSE) and the flexible energy consumer. DR is provided by the flexible load through call options offers to the LSE. A transaction mechanism is designed to incentivize the DR aggregator by an appropriate selection of the strike price. It is shown that the strike price should be chosen to be the true value of lost load. A multi-stage decision-theoretic formulation is presented to model the interaction between the aggregator and two settlement markets. Simulations reveal that the proposed approach reduces the total costs incurred by the LSE.

10aRM11-0061 aWang, Dai1 aKalathil, Dileep1 aPoolla, Kameshwar1 aGuan, Xiaohong uhttp://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7403359&refinements%3D4229014380%26filter%3DAND%28p_IS_Number%3A7402066%29