Xinbo Geng

A data-driven approach to identifying system pattern regions in market operations

This paper studies the fundamental coupling between individual load levels and locational marginal prices in security constrained economic dispatch. The concepts of system pattern and system pattern region (SPR) are introduced for the analysis. Theoretical investigation suggests that SPRs are disjoint, convex, and separable sets and there exists separating hyperplanes among SPRs. Furthermore, the total number of SPRs is finite and the SPRs are one-to-one mapped with vectors of LMPs. Monte-Carlo simulation results provide solid support of the theoretical analysis and reveal more characteristics of system patterns and SPRs. Based on the theoretical analysis, a data-driven approach to identifying the separating hyperplanes among SPRs is proposed. This approach suggests the potential use of historical load/price data for understanding and predicting system status and prices. One promising feature of the proposed approach is that the vector of LMPs at all the buses can be successfully pinpointed given a load vector without the information of system topology. Case studies in IEEE 24 bus system illustrate the potential value of this approach in operational planning and energy trading.

Architecture and Algorithms for Privacy Preserving Thermal Inertial Load Management by a Load Serving Entity

Motivated by the growing importance of demand response in modern power systems operations, we propose an architecture and supporting algorithms for privacy preserving thermal inertial load management as a service provided by the load serving entity (LSE). We focus on an LSE managing a population of its customers’ air conditioners, and propose a contractual model where the LSE guarantees quality of service to each customer in terms of keeping their indoor temperature trajectories within respective bands around the desired individual comfort temperatures. We show how the LSE can price the contracts differentiated by the flexibility embodied by the width of the specified bands. We address architectural questions of (i) how the LSE can strategize its energy procurement based on price and ambient temperature forecasts, (ii) how an LSE can close the real-time control loop at the aggregate level while providing individual comfort guarantees to loads, without ever measuring the states of an air conditioner for privacy reasons. Control algorithms to enable our proposed architecture are given, and their efficacy is demonstrated on real data.

A control system framework for privacy preserving demand response of thermal inertial loads

We address a problem in demand response for the class of thermal inertial loads: How to control the total demand of a set of loads, and also what to control it to, all while respecting constraints on load states, as well as maintaining privacy of load states. The architecture we investigate consists of an aggregator or Load Serving Entity (LSE) serving several thermostatically controlled loads (TCLs), whose set-points are controlled by the LSE to follow a desired total power consumption. We propose a modeling, analysis and design framework for the LSE that accomplishes this goal by solving a hierarchy of two control problems. The first control problem consists of determining an optimal aggregate power trajectory given the price forecasts. The second problem is that of controlling the set-points of the TCL population so as to drive their total power consumption to follow the optimal power trajectory. We show how the LSE can solve these control problems while guaranteeing privacy and contractual comfort bounds for the TCL states. Numerical simulations illustrate the efficacy of the proposed framework.

Mean Field Games in Nudge Systems for Societal Networks

We consider the general problem of resource sharing in societal networks, consisting of interconnected communication, transportation, energy, and other networks important to the functioning of society. Participants in such network need to take decisions daily, both on the quantity of resources to use as well as the periods of usage. With this in mind, we discuss the problem of incentivizing users to behave in such a way that society as a whole benefits. To perceive societal level impact, such incentives may take the form of rewarding users with lottery tickets based on good behavior and periodically conducting a lottery to translate these tickets into real rewards. We will pose the user decision problem as a mean field game and the incentives question as one of trying to select a good mean field equilibrium (MFE). In such a framework, each agent (a participant in the societal network) takes a decision based on an assumed distribution of actions of his/her competitors and the incentives provided by the social planner. The system is said to be at MFE if the agent’s action is a sample drawn from the assumed distribution. We will show the existence of such an MFE under general settings, and also illustrate how to choose an attractive equilibrium using as an example demand-response in the (smart) electricity network.

Voltage security constrained look-ahead coordination of reactive power support devices with high renewables

Reactive power support devices (RPSDs) such as capacitor banks and Static Var Compensators (SVCs) play a pivotal role in ensuring system voltage security. In large power systems with high penetration of renewables, the variability brought about by the renewables requires more coordination among these reactive power support devices. In this paper, we investigate the benefits of look-ahead coordination of both continuous-state and discrete-state RPSDs across multiple control areas. The objective is to coordinate multiple RPSDs in anticipation of near-term net load variations in order to minimize the costs of RPSD operations and transmission losses. Constraints include ensuring voltage security with respect to a set of possible contingency scenarios. This problem is first formulated as a Mixed Integer Non-Linear Programming (MINLP) problem and then approximated as a Mixed Integer Quadratic Programming (MIQP) problem via power flow Jacobian matrix. The validity of the solution to the MIQP problem is verified by solving AC power flow equations. The proposed approach is examined on the IEEE 24-bus Reliability Test System (RTS) system. Critical discussions on the impacts of wind uncertainties are provided, and a linear approximation approach is proposed to estimate the impacts of wind fluctuations on voltage magnitudes.