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In cyber-physical systems (CPS), the problem of controlling resources can be depicted as an actuator selection problem. Given a large library of actuators and a control objective, what is the least number of actuators to be selected, and what is the corresponding optimal control law? These dynamic design questions are inherently coupled. In this paper, we show that a breadth of actuator selection...
For a single-phase distribution network with constant-power, constant-current, and constant-impedance loads (ZIP loads), sufficient conditions are presented that explicitly define a region where a unique load-flow solution exists. The Z-Bus method is shown to be a contraction mapping iteration, which upon initialization within this region, is guaranteed to converge to the unique load-flow solution...
This paper presents an augmented optimal power flow (OPF) formulation that minimizes a power network's transient control costs using a linear quadratic regulator (LQR). The network is described by AC power flows with third-order generator dynamics modeling. Then, linearized dynamics around a known solution of the power flow equations are considered. Leveraging the equivalent linear matrix inequality...
This paper is concerned with the Z-Bus method to solve the load-flow problem in three-phase distribution networks with wye and delta constant-power, constant-current, and constant-impedance loads (ZIP loads). The Z-Bus method is viewed as a fixed-point iteration. By leveraging the contraction mapping theorem, a set of sufficient conditions is then presented that guarantees a) the existence of a unique...
Power grids have evolved into cyber-networks equipped with high speed communications and advanced sensors. While this evolution has been monumental, the risk of cyber-attacks is growing. In grids, phasor measurement units (PMU)—equipped with GPS receivers—are now ubiquitously installed in widespread locations, while providing real time grid-visibility. Cooperatively, limited number of PMUs can enable...
This paper proposes a novel approach for Wireless Local Area Networks (WLAN) indoor fingerprinting localization using a novel interpretation and optimization solution. The user's location is introduced as a sparse vector which can be estimated in a single minimization problem. The coarse localization is embedded in the fine localization to prevent the cases where the user's position is searched in...
This paper is concerned with optimal multi-period scheduling of distributed energy resources (DERs) dispersed in electricity distribution networks. DERs considered here comprise programmable loads with the ability to adjust their real power, photovoltaic (PV) generators with the ability to inject or absorb reactive power, as well as storage units (batteries) that can be charged or discharged and also...
A two-stage stochastic programming approach is pursued to optimally place and size photovoltaic (PV) inverters in a radial distribution network under solar irradiance and load uncertainties. First-stage variables include binary PV unit placement as well as continuous real and apparent power capacities of the inverters. Second-stage decisions comprise reactive power compensation, power flows, and nodal...
A risk-averse strategy is presented for optimal placement and sizing of photovoltaic (PV) inverters in distribution networks under solar irradiance and load uncertainty. By modeling uncertainties through a finite set of scenarios, a two-stage stochastic program is formulated. First-stage decisions comprise binary placement variables, area, and apparent power capacity of PV units. Second-stage decisions...
Voltage regulation in distribution networks featuring high penetration of distributed photovoltaic (PV) generation is particularly challenging due to the stochastic nature of solar energy. To ensure that voltage levels remain within safety margins, this paper introduces a real and reactive power optimization model that penalizes the conditional value-at-risk of the voltage deviation from its nominal...
The stochastic nature of solar renewable power poses challenges in distribution networks with high-penetration photovoltaic (PV) generation in terms of achieving thermal loss minimization, voltage regulation, and customer satisfaction. This paper introduces a stochastic optimization model for real and reactive power management in such distribution systems with high level of residential-scale PV penetration...
A system comprising a utility company serving a set of electricity end-users is considered. The utility company can purchase energy from the wholesale market. It is also connected to a renewable energy production facility, from which it can harvest energy at no cost, and also to a battery for energy storage. Ahead of a scheduling horizon, the utility purchases energy based on forecasted demand and...
A fast distributed approach is developed for the market clearing with large-scale demand response in electric power networks. In addition to conventional supply bids, demand offers from aggregators serving large numbers of residential smart appliances with different energy constraints are incorporated. Leveraging the Lagrangian relaxation based dual decomposition, the resulting optimization problem...
Energy management for a microgrid featuring distributed generation from conventional and renewable energy sources and adjustable loads is the theme of this paper. The microgrid is connected to the main grid, thus enabling energy import from and export to the main grid. A two-stage stochastic programming formulation is developed, where first-stage decisions are the conventional generation schedules...
High wind energy penetration critically challenges the economic dispatch of current and future power systems. Supply and demand must be balanced at every bus of the grid, while respecting transmission line ratings and accounting for the stochastic nature of renewable energy sources. Aligned to that goal, a network-constrained economic dispatch is developed in this paper. To account for the uncertainty...
To achieve the goal of high wind power penetration in future smart grids, economic energy management accounting for the stochastic nature of wind power is of paramount importance. Multi-period economic dispatch and demand-side management for power systems with multiple wind farms is considered in this paper. To address the challenge of intrinsically stochastic availability of the non-dispatchable...
Dual decomposition coupled with the subgradient method has found application to optimal resource management in communication networks, as it can lead to distributed and scalable algorithms. Network entities—nodes or functional layers—exchange Lagrange multipliers and primal minimizers of the Lagrangian function towards optimizing a network-wide performance metric. It is of interest to study the performance...
Due to the low communication overhead and robustness to failures, distributed energy management is of paramount importance in smart grids, especially in microgrids, which feature distributed generation (DG). Distributed economic dispatch for a microgrid with renewable penetration and demand-side management operating in the grid-connected mode is considered in this paper. To address the challenge of...
This paper deals with optimal scheduling of demand response in a residential setup when the electricity prices are known ahead of time. Each end-user has a “must-run” load, and two types of adjustable loads. The first type must consume a specified total amount of energy over the scheduling horizon, but its consumption can be adjusted across the horizon. The second type of load has adjustable power...
A cross-layer design along with an optimal resource allocation framework is formulated for wireless fading networks, where the nodes perform network coding. The aim is to jointly optimize end-to-end multicast rates, network code design variables, broadcast link flows, link capacities, average power consumption, and short-term power allocation policies. As in the conventional routing paradigm, the...
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