Resource Management in Heterogeneous Wireless Sensor Networks

We propose a first approach in the direction of a general framework for resource management in wireless sensor networks (WSN). The basic components of the approach are a model for WSNs and a task model. Based on these models, a first version of an algorithm for assigning tasks to a WSN is presented. The models and the algorithm are designed in such a way that an extension to more complex models is possible. Furthermore, the developed approach to solve the RM problem allows an easy adaptation, to fit more complex models. In this way, a flexible approach is achieved, which may form the base for many RM approaches.\ud The possibilities and limitations of the presented approach are tested on randomly generated instances. The aim of these tests is to show that the chosen models and algorithm form a proper starting point to design RM tools

Load control in low voltage level of the electricity grid using µCHP appliances

The introduction of microCHP (Combined Heat and Power) appliances and other means of distributed generation causes a shift in the way electricity is produced and consumed. Households themselves produce electricity and deliver the surplus to the grid. In this way, the distributed generation also has implications on the transformers and, thus, on the grid. In this work we study the influence of introducing microCHP appliances on the total load of a group of houses (behind the last transformer). If this load can be controlled, the transformer may be relieved from peak loads. Moreover, a well controlled fleet production can be offered as a Virtual Power Plant to the electricity grid.\ud \ud In this work we focus on different algorithms to control the fleet and produce a constant electricity output. We assume that produced electricity is consumed as locally as possible (preferably within the household). Produced heat can only be consumed locally. Additionally, heat can be stored in heat stores. Fleet control is achieved by using heat led control algorithms and by specifying as objective how much of the microCHP appliances have to run.\ud \ud First results show that preferred patterns can be produced by using fleet control. However, as the problem is heat driven, still reasonably large deviations from the objective occur. Several combinations of heat store and fleet control algorithm parameters are considered to match the heat demand and supply.\ud \ud This work is a first attempt in controlling a fleet and gives a starting point for further research in this area. A certain degree of control can already be established, but for better stability more intelligent algorithms are needed

Scheduling microCHPs in a group of houses

The increasing penetration of renewable energy sources, the demand for more energy efficient electricity production and the increase in distributed electricity generation causes a shift in the way electricity is produced and consumed. The downside of these changes in the electricity grid is that network stability and controllability become more difficult compared to the old situation. The new network has to accommodate various means of production, consumption and buffering and needs to offer control over the energy flows between these three elements.\ud In order to offer such a control mechanism we need to know more about the individual aspects. In this paper we focus on the modelling of distributed production. Especially, we look at the use of microCHP (Combined Heat and Power) appliances in a group of houses.\ud The problem of planning the production runs of the microCHP is modelled via an ILP formulation, both for a single house and for a group of houses.\u

On the microCHP scheduling problem

In this paper both continuous and discrete models for the microCHP (Combined Heat and Power) scheduling problem are derived. This problem consists of the decision making to plan runs for a specific type of distributed electricity\ud generators, the microCHP. As a special result, one model variant of the problem, named n-DSHSP-restricted, is proven to be NP-complete in the strong sense. This shows the necessity of the development of heuristics for the scheduling of microCHPs, in case multiple generators are combined in a so-called fleet

Demand side load management using a three step optimization methodology

In order to keep a proper functional electricity grid and to prevent large investments in the current grid, the creation, transmission and consumption of electricity needs to be controlled and organized in a different way as done nowadays. Smart meters, distributed generation and -storage and demand side management are novel technologies introduced to reach a sustainable, more efficient and reliable electricity supply. Although these technologies are very promising to reach these goals, coordination between these technologies is required. It is therefore expected that ICT is going to play an important role in future smart grids. In this paper, we present the results of our three step control strategy designed to optimize the overall energy efficiency and to increase the amount of generation based on renewable resources with the ultimate goal to reduce the CO2 emission resulting from generation electricity. The focus of this work is on the control algorithms used to reshape the energy demand profile of a large group of buildings and their requirements on the smart grid. In a use case, steering a large group of freezers, we are able to reshape a demand profile full of peaks to a nicely smoothed demand profile, taking into the account the amount of available communication bandwidth and exploiting the available computation power distributed in the grid

Improved simulator to analyse the impact of distributed generation on the electricity grid

A change in future electricity grids is expected caused by the introduction of distributed generation, distributed storage and demand side load management. To analyse the impact of these technologies, a simulator has been developed. With this simulator, a small group of households with micro-generators can already be analysed. However, due to the large memory footprint, larger groups of houses cannot be simulated. In this paper an improved simulator which is capable of distributing simulations over multiple PCs via a network is presented.\ud Using this distributed approach, more (memory) resources can be utilised and more calculations can be done in parallel. Although the introduction of the network stack gives some overhead, still a large speedup is seen when more PCs are used. Furthermore, far bigger groups of houses can simulated

Applying Column Generation to the Discrete Fleet Planning Problem

The paper discusses an Integer Linear Programming (ILP) formulation that describes the problem of planning the use of domestic distributed generators, under individual as well as fleet constraints. The planning problem comprises the assignment of time intervals during which the local generator must produce or not. In [1] this ILP is shown to be NP-complete in the strong sense. Heuristic methods have been developed to find solutions in reasonable time.\ud \ud In this work a different technique is used to overcome the complexity problems. We use column generation to search the possible decision vectors in a faster way. The ILP is slightly adjusted to facilitate the column generation technique to search in a clever way through the set of possible solutions.\ud \ud To measure the results, the column generation technique is compared to an earlier developed heuristic method. Both the quality of the objective function and the speed of the methods are compared

Domestic energy efficiency improving algorithms

Due to increasing energy prices and the greenhouse effect more efficient electricity production is desirable, referably based on renewable sources. In the last years, a lot of technologies have been developed to improve the efficiency of the electricity usage and supply. Next to large scale technologies such as windturbine parks, a lot of domestic technologies are developed. These domestic technologies can be divided in 1) Distributed Generation (DG), 2) Energy Storage and 3) Demand Side Load Management. Control methodologies optimizing the combination of techniques raise the potential of the individual techniques. A lot of research in done in this area. This paper outlines a number of papers and deducts the general idea. Next, a three-step optimization methodology is proposed using 1) offline local prediction, 2) offline global planning and 3) online local scheduling. The paper ends with results of simulations and a field test verifying that methodology is promising

Multilevel unit commitment in smart grids

This paper focuses on the planning of electricity resources in the developing electricity infrastructure. First we model the existing infrastructure and extend this model to a smart grid infrastructure, where we focus on the large scale introduction of small electricity generators, leading to generation possibilities at both ends of the electricity network. Then the traditional Unit Commitment Problem (UCP) is given. We extend this formulation to the Multilevel Unit Commitment Problem (MUCP), where we describe and include the possibilities that arise in the developing smart grid, in a general way. Based on the characteristics of the problem with its subdivision into different levels, a planning method for the MUCP is described. Finally we solve and analyze a scenario, where a fleet of 5000 houses is added to a small collection of power plants

Risk profiles and one-year outcomes of patients with newly diagnosed atrial fibrillation in India: Insights from the GARFIELD-AF Registry.

BACKGROUND: The Global Anticoagulant Registry in the FIELD-Atrial Fibrillation (GARFIELD-AF) is an ongoing prospective noninterventional registry, which is providing important information on the baseline characteristics, treatment patterns, and 1-year outcomes in patients with newly diagnosed non-valvular atrial fibrillation (NVAF). This report describes data from Indian patients recruited in this registry. METHODS AND RESULTS: A total of 52,014 patients with newly diagnosed AF were enrolled globally; of these, 1388 patients were recruited from 26 sites within India (2012-2016). In India, the mean age was 65.8 years at diagnosis of NVAF. Hypertension was the most prevalent risk factor for AF, present in 68.5% of patients from India and in 76.3% of patients globally (P < 0.001). Diabetes and coronary artery disease (CAD) were prevalent in 36.2% and 28.1% of patients as compared with global prevalence of 22.2% and 21.6%, respectively (P < 0.001 for both). Antiplatelet therapy was the most common antithrombotic treatment in India. With increasing stroke risk, however, patients were more likely to receive oral anticoagulant therapy [mainly vitamin K antagonist (VKA)], but average international normalized ratio (INR) was lower among Indian patients [median INR value 1.6 (interquartile range {IQR}: 1.3-2.3) versus 2.3 (IQR 1.8-2.8) (P < 0.001)]. Compared with other countries, patients from India had markedly higher rates of all-cause mortality [7.68 per 100 person-years (95% confidence interval 6.32-9.35) vs 4.34 (4.16-4.53), P < 0.0001], while rates of stroke/systemic embolism and major bleeding were lower after 1 year of follow-up. CONCLUSION: Compared to previously published registries from India, the GARFIELD-AF registry describes clinical profiles and outcomes in Indian patients with AF of a different etiology. The registry data show that compared to the rest of the world, Indian AF patients are younger in age and have more diabetes and CAD. Patients with a higher stroke risk are more likely to receive anticoagulation therapy with VKA but are underdosed compared with the global average in the GARFIELD-AF. CLINICAL TRIAL REGISTRATION-URL: http://www.clinicaltrials.gov. Unique identifier: NCT01090362