Development of a fuzzy control based self-adaptive system for energy saving in constrained networks for the Internet of Things

Las redes del futuro, incluyendo las redes de próxima generación, tienen entre sus objetivos de diseño el control sobre el consumo de energía y la conectividad de la red. Estos objetivos cobran especial relevancia cuando hablamos de redes con capacidades limitadas, como es el caso de las redes de sensores inalámbricos (WSN por sus siglas en inglés). Estas redes se caracterizan por estar formadas por dispositivos de baja o muy baja capacidad de proceso y por depender de baterías para su alimentación. Por tanto la optimización de la energía consumida se hace muy importante. Son muchas las propuestas que se han realizado para optimizar el consumo de energía en este tipo de redes. Quizás las más conocidas son las que se basan en la planificación coordinada de periodos de actividad e inactividad, siendo una de las formas más eficaces para extender el tiempo de vida de las baterías. La propuesta que se presenta en este trabajo se basa en el control de la conectividad mediante una aproximación probabilística. La idea subyacente es que se puede esperar que una red mantenga la conectividad si todos sus nodos tienen al menos un número determinado de vecinos. Empleando algún mecanismo que mantenga ese número, se espera que se pueda mantener la conectividad con un consumo energético menor que si se empleara una potencia de transmisión fija que garantizara una conectividad similar. Para que el mecanismo sea eficiente debe tener la menor huella posible en los dispositivos donde se vaya a emplear. Por eso se propone el uso de un sistema auto-adaptativo basado en control mediante lógica borrosa. En este trabajo se ha diseñado e implementado el sistema descrito, y se ha probado en un despliegue real confirmando que efectivamente existen configuraciones posibles que permiten mantener la conectividad ahorrando energía con respecto al uso de una potencia de transmisión fija. ABSTRACT. Among the design goals for future networks, including next generation networks, we can find the energy consumption and the connectivity. These two goals are of special relevance when dealing with constrained networks. That is the case of Wireless Sensors Networks (WSN). These networks consist of devices with low or very low processing capabilities. They also depend on batteries for their operation. Thus energy optimization becomes a very important issue. Several proposals have been made for optimizing the energy consumption in this kind of networks. Perhaps the best known are those based on the coordinated planning of active and sleep intervals. They are indeed one of the most effective ways to extend the lifetime of the batteries. The proposal presented in this work uses a probabilistic approach to control the connectivity of a network. The underlying idea is that it is highly probable that the network will have a good connectivity if all the nodes have a minimum number of neighbors. By using some mechanism to reach that number, we hope that we can preserve the connectivity with a lower energy consumption compared to the required one if a fixed transmission power is used to achieve a similar connectivity. The mechanism must have the smallest footprint possible on the devices being used in order to be efficient. Therefore a fuzzy control based self-adaptive system is proposed. This work includes the design and implementation of the described system. It also has been validated in a real scenario deployment. We have obtained results supporting that there exist configurations where it is possible to get a good connectivity saving energy when compared to the use of a fixed transmission power for a similar connectivity.

Pre-investigation of water electrolysis for flexible energy storage at large scales: the case of the Spanish power system

This report analyzes the basis of hydrogen and power integration strategies, by using water electrolysis processes as a means of flexible energy storage at large scales. It is a prospective study, where the scope is to describe the characteristics of current power systems (like the generation technologies, load curves and grid constraints), and define future scenarios of hydrogen for balancing the electrical grids, considering the efficiency, economy and easiness of operations. We focus in the "Spanish case", which is a good example for planning the transition from a power system holding large reserve capacities, high penetration of renewable energies and limited interconnections, to a more sustainable energy system being capable to optimize the volumes, the regulation modes, the utilization ratios and the impacts of the installations. Thus, we explore a novel aspect of the "hydrogen economy" which is based in the potentials of existing power systems and the properties of hydrogen as energy carrier, by considering the electricity generation and demand globally and determining the optimal size and operation of the hydrogen production processes along the country; e.g. the cost production of hydrogen becomes viable for a base-load scenario with 58 TWh/year of power surplus at 0.025 V/kWh, and large number electrolyzer plants (50 MW) running in variable mode (1-12 kA/m2)

A “midinfrared” scenario for cuprate superconductivity

I conjecture that the mechanism of superconductivity in the cuprates is a saving, due to the improved screening resulting from Cooper pair formation, of the part of the Coulomb energy associated with long wavelengths and midinfrared frequencies. This scenario is shown to provide a plausible explanation of the trend of transition temperature with layering structure in the Ca-spaced compounds and to predict a spectacularly large decrease in the electron-energy-loss spectroscopy cross-section in the midinfrared region on transition to the superconducting state, as well as less spectacular but still surprisingly large changes in the optical behavior. Existing experimental results appear to be consistent with this picture.

Orchestration of energy efficiency capabilities for a sustainable network management

The energy demand for operating Information and Communication Technology (ICT) systems has been growing, implying in high operational costs and consequent increase of carbon emissions. Both in datacenters and telecom infrastructures, the networks represent a significant amount of energy spending. Given that, there is an increased demand for energy eficiency solutions, and several capabilities to save energy have been proposed. However, it is very dificult to orchestrate such energy eficiency capabilities, i.e., coordinate or combine them in the same network, ensuring a conflict-free operation and choosing the best one for a given scenario, ensuring that a capability not suited to the current bandwidth utilization will not be applied and lead to congestion or packet loss. Also, there is no way in the literature to do this taking business directives into account. In this regard, a method able to orchestrate diferent energy eficiency capabilities is proposed considering the possible combinations and conflicts among them, as well as the best option for a given bandwidth utilization and network characteristics. In the proposed method, the business policies specified in a high-level interface are refined down to the network level in order to bring highlevel directives into the operation, and a Utility Function is used to combine energy eficiency and performance requirements. A Decision Tree able to determine what to do in each scenario is deployed in a Software Defined Network environment. The proposed method was validated with diferent experiments, testing the Utility Function, checking the extra savings when combining several capabilities, the decision tree interpolation and dynamicity aspects. The orchestration proved to be valid to solve the problem of finding the best combination for a given scenario, achieving additional savings due to the combination, besides ensuring a conflict-free operation.

The Potential Evolution of the European Energy System to 2020 and 2050. CEPS Working Document No. 392, 26 March 2014

This paper assesses the impact of decarbonisation of the energy sector on employment in Europe. Setting the stage for such an assessment, the paper provides an analysis of possible pathways to decarbonise Europe’s energy system, taking into account EU greenhouse gas emissions reduction targets for 2020 and 2050. It pays particular attention to various low-carbon technologies that could be deployed in different regions of the EU. It concludes that efficiency and renewables play a major role in any decarbonisation scenario and that the power sector is the main enabler for the transition to a low-carbon economy in Europe, despite rising electricity demand. The extent of the decline in the share of fossil fuels will largely depend on the existence of carbon capture and storage (CCS), which remains a major source of uncertainty.

The Relationship between Energy and Socio-Economic Development in the Southern and Eastern Mediterranean. MEDPRO Technical Report No. 27/February 2013

This report aims to identify, explain and detail the links and interactions in southern and eastern Mediterranean countries (SEMCs) between energy supply and demand and socio-economic development, as well as the potential role of energy supply and demand policies on both. Another related aim is to identify and analyse, in a quantitative and qualitative way, the changing role of energy (both demand and supply) in southern Mediterranean economies, focusing on its positive and negative impact on socio-economic development. This report investigates in particular: o The most important channels through which resource wealth can contribute to or hamper economic and social development in the analysed region; o Mechanisms and channels of relations between energy supply and demand policies and economic and social development. The burdens of energy subsidies and ‘oil syndrome’ are of particular relevance for the region. An integrated socio-economic development and energy policy scenario approach showing the potential benefits and synergies within countries and the region is developed in the final part of the report.

Prospects for Energy Supply and Demand in the Southern Mediterranean: Scenarios for 2010-30. MEDPRO Technical Report No. 22/December 2012

The aim of this technical report is to quantify alternative energy demand and supply scenarios for ten southern and eastern Mediterranean countries up to 2030. The report presents the model-based results of four alternative scenarios that are broadly in line with the MEDPRO scenario specifications on regional integration and cooperation with the EU. The report analyses the main implications of the scenarios in the following areas: • final energy demand by sector (industry, households, services, agriculture and transport); • the evolution of the power generation mix, the development of renewable energy sources and electricity exports to the EU; • primary energy production and the balance of trade for hydrocarbons; • energy-related CO2 emissions; and • power generation costs.

Outlook for Electricity and Renewable Energy in Southern and Eastern Mediterranean Countries. MEDPRO Technical Report No. 16/October 2012

The aim of this report is to elaborate the MEDPRO Energy Reference Scenario for electricity demand and power generation (by energy source) in the southern and eastern part of the Mediterranean (MED- 11 countries) up to 2030. The report assesses  the prospects for the implementation of renewable energy in the MED-11 countries over the next decades. The development of renewable energy is a cornerstone of the MED-11 countries’ efforts to improve security of supply and reduce CO2 emissions;  the prospects for regional renewable-energy plans (the Mediterranean Solar Plan, DESERTEC and Medgrid); and  the development of electricity interconnections in MED-11 countries and the possible integration of Mediterranean electricity and renewable markets (both south–south and south–north).

The investigation of energy efficiency measures in the traditional buildings in Oporto World Heritage Site

Background The improvement of energy efficiency in buildings is widely promoted as a measure to mitigate climate change through the reduction of CO2 emissions. Thermal regulations worldwide promote it, for both new and existing buildings. Among the existing stock, traditional and historic buildings pose the additional challenge of heritage conservation. Their energy efficiency upgrade raises the risk of provoking negative impacts on their significance. Aims and Methodology This research used an approach based on impact assessment methodologies, defining an inital baseline scenario for both heritage and energy, from which the appropriate improvement solutions were identified and assessed. The measures were dynamically simulated and the results for energy, CO2, cost and comfort compared with the initial scenario, and then being further assessed for their heritage impact to eventually determine the most feasible solutions. To test this method, ten case studies, representative of the identified typological variants, were selected among Oporto’s traditional buildings located in the World Heritage Site. Findings and Conclusions The fieldwork data revealed that the energy consumption of these dwellings was below the European average. Additionally, the households expressed that their home comfort sensation was overall positive. The simulations showed that the introduction of insulation and solar thermal panels were ineffective on these cases in terms of energy, cost and comfort. At the same time, these measures pose a great risk to the buildings heritage value. The most efficient solutions were obtained from behavioural changes and DHW retrofit. The study reinforced the idea that traditional buildings performed better than expected and can be retrofitted and updated at a low-cost and with passive solutions. The use of insulation and solar panels should be disregarded.

A review of the effects of distributed energy resources and power-electronic controlled loading on distribution network stability

This paper looks at potential distribution network stability problems under the Smart Grid scenario. This is to consider distributed energy resources (DERs) e.g. renewable power generations and intelligent loads with power-electronic controlled converters. The background of this topic is introduced and potential problems are defined from conventional power system stability and power electronic system stability theories. Challenges are identified with possible solutions from steady-state limits, small-signal, and large-signal stability indexes and criteria. Parallel computation techniques might be included for simulation or simplification approaches are required for a largescale distribution network analysis.

Energy-efficient multihop cooperative MISO transmission with optimal hop distance in wireless ad hoc networks

In this paper, we investigate the hop distance optimization problem in ad hoc networks where cooperative multiinput- single-output (MISO) is adopted to improve the energy efficiency of the network. We first establish the energy model of multihop cooperative MISO transmission. Based on the model, the energy consumption per bit of the network with high node density is minimized numerically by finding an optimal hop distance, and, to get the global minimum energy consumption, both hop distance and the number of cooperating nodes around each relay node for multihop transmission are jointly optimized. We also compare the performance between multihop cooperative MISO transmission and single-input-single-output (SISO) transmission, under the same network condition (high node density). We show that cooperative MISO transmission could be energyinefficient compared with SISO transmission when the path-loss exponent becomes high. We then extend our investigation to the networks with varied node densities and show the effectiveness of the joint optimization method in this scenario using simulation results. It is shown that the optimal results depend on network conditions such as node density and path-loss exponent, and the simulation results are closely matched to those obtained using the numerical models for high node density cases.

Optimal combination of energy crops under different policy scenarios:the case of Northern Greece

Energy crops production is considered as environmentally benign and socially acceptable, offering ecological benefits over fossil fuels through their contribution to the reduction of greenhouse gases and acidifying emissions. Energy crops are subjected to persistent policy support by the EU, despite their limited or even marginally negative impact on the greenhouse effect. The present study endeavors to optimize the agricultural income generated by energy crops in a remote and disadvantageous region, with the assistance of linear programming. The optimization concerns the income created from soybean, sunflower (proxy for energy crop), and corn. Different policy scenarios imposed restrictions on the value of the subsidies as a proxy for EU policy tools, the value of inputs (costs of capital and labor) and different irrigation conditions. The results indicate that the area and the imports per energy crop remain unchanged, independently of the policy scenario enacted. Furthermore, corn cultivation contributes the most to iFncome maximization, whereas the implemented CAP policy plays an incremental role in uptaking an energy crop. A key implication is that alternative forms of motivation should be provided to the farmers beyond the financial ones in order the extensive use of energy crops to be achieved.

Robust scenario formulations for strategic supply chain optimization under uncertainty

Strategic supply chain optimization (SCO) problems are often modelled as a two-stage optimization problem, in which the first-stage variables represent decisions on the development of the supply chain and the second-stage variables represent decisions on the operations of the supply chain. When uncertainty is explicitly considered, the problem becomes an intractable infinite-dimensional optimization problem, which is usually solved approximately via a scenario or a robust approach. This paper proposes a novel synergy of the scenario and robust approaches for strategic SCO under uncertainty. Two formulations are developed, namely, naïve robust scenario formulation and affinely adjustable robust scenario formulation. It is shown that both formulations can be reformulated into tractable deterministic optimization problems if the uncertainty is bounded with the infinity-norm, and the uncertain equality constraints can be reformulated into deterministic constraints without assumption of the uncertainty region. Case studies of a classical farm planning problem and an energy and bioproduct SCO problem demonstrate the advantages of the proposed formulations over the classical scenario formulation. The proposed formulations not only can generate solutions with guaranteed feasibility or indicate infeasibility of a problem, but also can achieve optimal expected economic performance with smaller numbers of scenarios.

Numerical study of neutron beam divergence in a beam-fusion scenario employing laser driven ions

The most established route to create a laser-based neutron source is by employing laser accelerated, low atomic-number ions in fusion reactions. In addition to the high reaction cross-sections at moderate energies of the projectile ions, the anisotropy in neutron emission is another important feature of beam-fusion reactions. Using a simple numerical model based on neutron generation in a pitcher–catcher scenario, anisotropy in neutron emission was studied for the deuterium–deuterium fusion reaction. Simulation results are consistent with the narrow-divergence ( ∼ 70 ° full width at half maximum) neutron beam recently served in an experiment employing multi-MeV deuteron beams of narrow divergence (up to 30° FWHM, depending on the ion energy) accelerated by a sub-petawatt laser pulse from thin deuterated plastic foils via the Target Normal Sheath Acceleration mechanism. By varying the input ion beam parameters, simulations show that a further improvement in the neutron beam directionality (i.e. reduction in the beam divergence) can be obtained by increasing the projectile ion beam temperature and cut-off energy, as expected from interactions employing higher power lasers at upcoming facilities.