Optimal Chiller and Thermal Energy Storage Design for Building HVAC Systems

In the context of indoor building temperature regulation, a controller calculates the inputs for the HVAC system that result in appropriate thermal comfort conditions. Additionally, if electricity prices are time dependent, these control actions will also impact economic expenditures. To improve economic performance, Thermal Energy Storage (TES) is typically used in conjunction with HVAC to time-shift chiller cooling loads to times of low energy price. The method of Economic Model Predictive Control (EMPC) has been demonstrated to effectively reduce expenditures. Since TES and chiller sizes have a direct impact on achievable operational savings, an economic analysis considering the investment costs associated with these equipments is necessary. This work presents a novel algorithm intended to optimally select equipment sizes based on Net Present Value analysis and utilizing the recently developed methods of Economic Linear Optimal Control (ELOC) and constrained ELOC. Implementation of the numeric optimization is illustrated with a case study

Upward propagation of gigantic jets revealed by 3D radio and optical mapping

Occasionally, lightning will exit the top of a thunderstorm and connect to the lower edge of space, forming a gigantic jet. Here, we report on observations of a negative gigantic jet that transferred an extraordinary amount of charge between the troposphere and ionosphere (~300 C). It occurred in unusual circumstances, emerging from an area of weak convection. As the discharge ascended from the cloud top, tens of very high frequency (VHF) radio sources were detected from 22 to 45 km altitude, while simultaneous optical emissions (777.4 nm OI emitted from lightning leaders) remained near cloud top (15 to 20 km altitude). This implies that the high-altitude VHF sources were produced by streamers and the streamer discharge activity can extend all the way from near cloud top to the ionosphere. The simultaneous three-dimensional radio and optical data indicate that VHF lightning networks detect emissions from streamer corona rather than the leader channel, which has broad implications to lightning physics beyond that of gigantic jets.Peer ReviewedPostprint (published version

HVAC control using infinite-horizon economic MPC

Air Conditioning (HVAC) systems is usually heaviest when electricity prices are at their highest. The method of Economic Model Predictive Control (EMPC) can be used in conjunction with Thermal Energy Storage (TES) to time-shift power consumption away from periods of high demand to periods of low energy cost. In addition to enormous computational costs, implementation of such algorithms can result in unexpected and sometimes pathological closed-loop behavior, including inventory creep and bang-bang actuation. This paper will present an infinite-horizon formulation of the EMPC problem. While the design of this controller is achieved by a fairly simple convex optimization problem, it will be shown to alleviate many of the pathological behaviors observed in the finite-horizon case as well as significantly reduce the computational effort required for implementation. The method is illustrated on a simple building example using active TES. Index Terms--Control system synthesis, Model predictive control, Infinite horizon optimal control, Thermal variable

Value-Optimal Sensor Network Design for Steady-State and Closed-Loop Systems Using the Generalized Benders Decomposition

The problem of value-optimal sensor network design for linear systems has been shown to be of the nonconvex mixed integer programming class. While the branch and bound search procedure can be used to obtain a global solution, such a method is limited to fairly small systems. The bottleneck is that during each iteration of the branch and bound search, a fairly slow semi-definite programming (SDP) problem must be solved to its global optimum. In this paper, it is demonstrated that an equivalent reformulation of the nonconvex mixed integer programming problem and subsequent application of the generalized benders decomposition (GBD) algorithm will result in massive reductions in computational effort. While the proposed algorithm has to solve multiple mixed integer linear programs, this increase in computational effort is significantly outweighed by a reduction in the number of SDP problems that must be solved

Integrated Process Design and Control for Smart Grid Coordinated IGCC Power Plants Using Economic Linear Optimal Control

The Integrated Gasification Combined Cycle (IGCC) possesses a number of advantages over traditional power generation plants, including increased efficiency, flex-fuel, and carbon capture. A lesser-known advantage of the IGCC system is the ability to coordinate with the smart grid. The idea is that process modifications can enable dispatch capabilities in the sense of shifting power production away from periods of low electricity price to periods of high price and thus generate greater revenue. The work begins with a demonstration of Economic Model Predictive Control (EMPC) as a strategy to determine the dispatch policy by directly pursuing the objective of maximizing plant revenue. However, the numeric nature of EMPC creates an inherent limitation when it comes to process design. Thus, Economic Linear Optimal Control (ELOC) is proposed as a surrogate for EMPC in the formulation of the integrated design and control problem for IGCC power plants with smart grid coordination

Distributed Feed Fuel Cell Stack

A fuel cell having a distributed fuel feed in which the heat generation profile can be better controlled. Fuel channel stack and system efficiency improvements are achieved.Sponsorship: Illinois Institute of TechnologyUnited States Paten

Dry Gasification Oxy-combustion Power Cycle

Proposed within this work is a novel coal conversion process, dubbed the “dry gasification oxy-combustion” (DGOC) power cycle. In the unique two-stage conversion process, feed coal is partially oxidized at high pressures in an oxygen-blown, fluidized-bed gasification unit, using recycled flue gas as a gasification agent (≈61% CO₂ and 32% H₂O). In addition, the reducing environment of the gasifier provides an opportunity to perform pre-combustion sulfur removal through sorbent-based capture. The second stage, oxy-combustion, also uses recycled flue gas, for temperature moderation, while providing the energy to raise steam for power generation. The process effluent is concentrated in CO₂ and at high pressures, which enables the use of ambient cooling to flush out the water from the process stream. Full condensation of the remaining CO₂ in a high-purity liquid stream requires the inclusion of a refrigeration cycle. The resulting stream is ready for further compression, drying and pipelining for sequestration. Analysis of a preliminary design was carried out using process simulation models developed in Aspen Plus. Results suggest that DGOC can achieve carbon capture and sequestration (CCS) goals with a 4.9% higher thermal efficiency over the estimated 29.3% for current CCS technologies based on oxy-combustion. This is due to benefits gained by shifting sulfur removal from the flue gas desulfurization (FGD) recycle loop to the gasifier, as well as recovery of CaS oxidation heat. Furthermore, recoverable latent heat is available as a result of high-pressure operation and is provided primarily from the condensation of water contained in the flue stream. Results also suggest that DGOC will remain competitive against the integrated gasification combined cycle (IGCC) process, in terms of fresh water consumption