An MQTT Gateway for HIL Testing of Energy Systems

In this paper, we present an MQTT gateway for Hardware-in-the-Loop (HIL) testing of energy systems control solutions. The proposed solution is the result of a workflow that automatise the mapping process between the set points obtained from the controllers, and the corresponding parameters in the simulation model. In the workflow, different MQTT topics are created for each controlled parameter in the simulation model, then the communication flows are generated in the open-source platform Node-RED. The validity of the proposed solution is investigated through its implementation in an HIL co-simulation framework, where a power system is coupled with a low-temperature district heating network and its model predictive control-based controller acting as a device under test

A Hardware-in-the-Loop Co-simulation of Multi-modal Energy System for Control Validation

In this paper, we present a Hardware-in-the-Loop (HIL) co-simulation framework to test multi-modal energy systems. The framework has been tested using as an example a section of the Living Lab Energy Campus (LLEC) of the Forshungszentrum Jülich (DE). A master algorithm has been developed to orchestrate the two components of the co-simulation platform: the real-time simulation of the power network running on OPAL-RT, and the real-time simulation of the low-temperature district heating (LTDH) network using Functional Mock-up Units (FMU) on a custom cluster. The master algorithm also coordinates the exchange of information between the real-time simulators and the device under test. The device under test is composed of a cloud-based model predictive control (MPC) - that operates on the heat pumps in the LTDH network - and an MQTT broker. The results show the co-simulation is successful and the framework can validate the control algorithm

The demand response potential in copper production

Demand response (DR) of large industrial electricity consumers is a promising option to balance the fluctuating supply by renewable energies in the electricity grid. Renewable energy technologies themselves depend on copper as a key material. At the same time, the production of copper is a power-intensive process but its DR potential has not yet been quantified in detail via process scheduling. Here, we analyze the DR potential of copper production by optimally scheduling the batch and continuous tasks of a representative copper process. To determine the optimal schedule, we formulate a mixed-integer linear program (MILP) based on the resource-task network (RTN) formulation approach. We first optimize the production volume to define a reference case and then minimize the electricity costs under time-varying electricity prices while retaining the production target. A sensitivity analysis evaluates the impact of task capacities on the production volume and DR potential. The results indicate a significant DR potential, as optimal scheduling can reduce the annual electricity costs by up to 14.2% while still producing the maximum copper output as the reference process schedule. The power-intensive electrolytic refining shows the largest potential for reducing costs. Offgas handling, air separation, and air compression further show significant cost reduction potentials. These tasks must process large material streams that are directly connected to operating the smelting and refining tasks. Our model shows the potential of considering these interlinked tasks in one scheduling model that focuses on DR. The results suggest that DR scheduling in copper production has a significant economic potential without compromising production goals. Further, the DR scheduling shifts large amounts of electricity demand by responding to fluctuating electricity prices, which enables flexibility of the demand side and can thus support the integration of renewable energy into the electric grid.ISSN:0959-652

Redox regulation of matrix metalloproteinase gene family in small cell lung cancer cells

It has been implicated that reactive oxygen species (ROS) play important roles in modulating tumor progression. However, the mechanisms by which redox-regulated tumor progression are largely unknown. We previously demonstrated that reduced intracellular redox conditions could be achieved in stably transfected small cell lung cancer cells with gamma-glutamylcysteine synthetase (gamma-GCSh) cDNA which encodes a rate-limiting enzyme in the biosynthesis of glutathione (GSH), a major physiological redox regulator. In the present study, using DNA microarray analyses, we compared the expression profiles between the gamma-GCSh-transfected cells and their nontransfected counterpart. We observed downregulation of several matrix metalloproteinases (MMPs), i.e., MMPI and MMP3, and MMP10 in the transfected cells. Dot blot and Northern blot hybridizations confirmed that, among the 18 MMP gene family members and four tissue inhibitors of matrix metalloprotein family (TIMP) analyzed, the expression levels of these three MMPs were consistently reduced. Transiently increased gamma-GCSh expression using tetracycline-inducible gamma-GCSh adenoviral expression system also showed down-regulation of MMP3 and MMP10, but not MMP1. Our results demonstrated that redox regulation of MMP1, MMP3 and MMP10 expression depend upon different modes of redox manipulation. These results bear implication that antioxidant modulation of antitumor progression may be contributed at least in part by the downregulation of a subset of metrix metalloproteins

Source: Solar Energy News

�85 % of Texas load �6.1 million advanced meters,>1.9GW demand response resources �Peak demand: 68,305 MW (Aug 3, 2011) �Wind capacity: 10,407 M