Analytical modelling of integrated solar drying system

The drying of fruit and vegetables is a subject of great importance. Dried fruit and vegetables have gained commercial importance, and their growth on a commercial scale has become an important sector of the agricultural industry. However, food drying is one of the most energy intensive processes of the major industrial process and accounts for up to 15 % of all industrial energy usage. Due to increasingly high electricity prices and environmental concern, a dryer using traditional energy sources is not a feasible option anymore. Therefore, an alternative/renewable energy source is needed. In this regard, an integrated solar drying system that includes highly efficient double-pass counter flow v-groove solar collector, conical-shaped rock-bed thermal storage, auxiliary heater, the centrifugal fan and the drying chamber has been designed and constructed. Mathematical model for all the individual components as well as an integrated model combining all components of the drying system has been developed. Mathematical equations were solved using MATLAB program. This paper presents the analytical model and key finding of the simulation.

Development of an efficiency equation for solar evaporator- collectors

Considering the growing energy needs and concern for environmental degradation, clean and inexhaustible energy sources, e.g solar energy are receiving greater attention for various applications. The use of solar energy systems for low temperature applications reduces the burden on conventional fossil fuels and has little or no harmful effects on the environment. The performance of a solar system depends to a great extent on the collector used for the conversion of solar radiant energy to thermal energy. A solar evaporatorcollector (SEC) is basically an unglazed flat plate collector where refrigerant, like R134a, is used as the working fluid. As the operating temperature of SEC is very low, it collects energy both from solar irradiation and ambient energy leading to a much higher efficiency than the conventional collectors. The capability of SEC to utilize ambient energy also enables the system to operate at night. Therefore it is not appropriate to use for the evaluation of performance of SEC by conventional efficiency equation where ambient energy and condensation is not considered as energy input in addition to irradiation. In the National University of Singapore, several Solar Assisted Heat Pump (SAHP) systems were built for the evaluation of performance under the metrological condition of Singapore for thermal applications of desalination and SEC was the main component to harness renewable energy. In this paper, the design and performance of SEC are explored. Furthermore, an attempt is made to develop an efficiency equation for SEC and maximum efficiency attained 98% under the meteorological condition of Singapore.

Commercialization of sustainable energy technologies

Commercialization efforts to diffuse sustainable energy technologies (SETs1) have so far remained as the biggest challenge in the field of renewable energy and energy efficiency. Limited success of diffusion through government driven pathways urges the need for market based approaches. This paper reviews the existing state of commercialization of SETs in the backdrop of the basic theory of technology diffusion. The different SETs in India are positioned in the technology diffusion map to reflect their slow state of commercialization. The dynamics of SET market is analysed to identify the issues, barriers and stakeholders in the process of SET commercialization. By upgrading the ‘potential adopters’ to ‘techno-entrepreneurs’, the study presents the mechanisms for adopting a private sector driven ‘business model’ approach for successful diffusion of SETs. This is expected to integrate the processes of market transformation and entrepreneurship development with innovative regulatory, marketing, financing, incentive and delivery mechanisms leading to SET commercialization.

Decentralized Sustainable Energy Planning of Tumkur District, India

Present work shows the feasibility of decentralized energy options for the Tumkur district in India. Decentralized energy planning (DEP) involves scaling down energy planning to subnational or regional scales. The important aspect of the energy planning at decentralized level would be to prepare an area-based DEP to meet energy needs and development of alternate energy sources at least-cost to the economy and environment. The geographical coverage and scale reflects the level at which the analysis takes place, which is an important factor in determining the structure of models. In the present work, DEP modeling under different scenarios has been carried out for Tumkur district of India for the year 2020. DEP model is suitably scaled for obtaining the optimal mix of energy resources and technologies using a computer-based goal programming technique. The rural areas of the Tumkur district have different energy needs. Results show that electricity needs can be met by biomass gasifier technology, using biomass feedstock produced by allocating only 12% of the wasteland in the district at 8 t/ha/yr of biomass productivity. Surplus electricity can be produced by adopting the option of biomass power generation from energy plantations. The surplus electricity generated can be supplied to the grid. The sustainable development scenario is a least cost scenario apart from promoting self-reliance, local employment, and environmental benefits. (C) 2010 American Institute of Chemical Engineers Environ Prog, 30: 248-258, 2011

The role of sustainable agriculture and renewable-resource management in reducing greenhouse-gas emissions and increasing sinks in China and India

This paper contains an analysis of the technical options in agriculture for reducing greenhouse-gas emissions and increasing sinks, arising from three distinct mechanisms: (i) increasing carbon sinks in soil organic matter and above-ground biomass; (ii) avoiding carbon emissions from farms by reducing direct and indirect energy use; and (iii) increasing renewable-energy production from biomass that either substitutes for consumption of fossil fuels or replaces inefficient burning of fuelwood or crop residues, and so avoids carbon emissions, together with use of biogas digesters and improved cookstoves. We then review best-practice sustainable agriculture and renewable-resource-management projects and initiatives in China and India, and analyse the annual net sinks being created by these projects, and the potential market value of the carbon sequestered. We conclude with a summary of the policy and institutional conditions and reforms required for adoption of best sustainability practice in the agricultural sector to achieve the desired reductions in emissions and increases in sinks. A review of 40 sustainable agriculture and renewable-resource-management projects in China and India under the three mechanisms estimated a carbon mitigation potential of 64.8 MtC yr(-1) from 5.5 Mha. The potential income for carbon mitigation is $324 million at $5 per tonne of carbon. The potential exists to increase this by orders of magnitude, and so contribute significantly to greenhouse-gas abatement. Most agricultural mitigation options also provide several ancillary benefits. However, there are many technical, financial, policy, legal and institutional barriers to overcome.

Algal biofuel from urban wastewater in India: Scope and challenges

Rapidly depleting stocks of fossil fuels and increasing greenhouse gas (GHG) emissions have necessitated the exploration of cost effective sustainable energy sources focussing on biofuels through algae. Abundant wastewaters generated in urban localities every day provide the nourishment to nurture algae for biofuel generation. The present communication focuses on the lipid prospects of algae grown in wastewater systems. Euglena sp., Spirogyra sp. and Phormidium sp. were collected from selected locations of sewage fed urban lakes and sewage treatment plants of Bangalore and Mysore. The total lipid content of Euglena sp. was higher (24.6%) compared to Spirogyra sp. (18.4%) followed by Phormidium sp. (8.8%) and their annual lipid yield potential was 6.52, 1.94 and 2.856 t/ha/year, respectively. These species showed higher content of fatty acids (palmitate, stearate followed by oleic and linoleic acids) with the desirable biofuel properties. (C) 2013 Elsevier Ltd. All rights reserved.

Power-optimal scheduling for a green base station with delay constraints

We consider a power optimization problem with average delay constraint on the downlink of a Green Base-station. A Green Base-station is powered by both renewable energy such as solar or wind energy as well as conventional sources like diesel generators or the power grid. We try to minimize the energy drawn from conventional energy sources and utilize the harvested energy to the maximum extent. Each user also has an average delay constraint for its data. The optimal action consists of scheduling the users and allocating the optimal transmission rate for the chosen user. In this paper, we formulate the problem as a Markov Decision Problem and show the existence of a stationary average-cost optimal policy. We also derive some structural results for the optimal policy.

Energy Sharing for Multiple Sensor Nodes With Finite Buffers

We consider the problem of finding optimal energy sharing policies that maximize the network performance of a system comprising of multiple sensor nodes and a single energy harvesting (EH) source. Sensor nodes periodically sense the random field and generate data, which is stored in the corresponding data queues. The EH source harnesses energy from ambient energy sources and the generated energy is stored in an energy buffer. Sensor nodes receive energy for data transmission from the EH source. The EH source has to efficiently share the stored energy among the nodes to minimize the long-run average delay in data transmission. We formulate the problem of energy sharing between the nodes in the framework of average cost infinite-horizon Markov decision processes (MDPs). We develop efficient energy sharing algorithms, namely Q-learning algorithm with exploration mechanisms based on the epsilon-greedy method as well as upper confidence bound (UCB). We extend these algorithms by incorporating state and action space aggregation to tackle state-action space explosion in the MDP. We also develop a cross entropy based method that incorporates policy parameterization to find near optimal energy sharing policies. Through simulations, we show that our algorithms yield energy sharing policies that outperform the heuristic greedy method.

Energy Harvesting WSNs for Accurately Estimating the Maximum Sensor Reading: Trade-Offs and Optimal Design

Computing the maximum of sensor readings arises in several environmental, health, and industrial monitoring applications of wireless sensor networks (WSNs). We characterize the several novel design trade-offs that arise when green energy harvesting (EH) WSNs, which promise perpetual lifetimes, are deployed for this purpose. The nodes harvest renewable energy from the environment for communicating their readings to a fusion node, which then periodically estimates the maximum. For a randomized transmission schedule in which a pre-specified number of randomly selected nodes transmit in a sensor data collection round, we analyze the mean absolute error (MAE), which is defined as the mean of the absolute difference between the maximum and that estimated by the fusion node in each round. We optimize the transmit power and the number of scheduled nodes to minimize the MAE, both when the nodes have channel state information (CSI) and when they do not. Our results highlight how the optimal system operation depends on the EH rate, availability and cost of acquiring CSI, quantization, and size of the scheduled subset. Our analysis applies to a general class of sensor reading and EH random processes.

Performance of an Ocean Energy Conversion System with DFIG Sensorless Control

The 2009/28/EC Directive requires Member States of the European Union to adopt a National Action Plan for Renewable Energy. In this context, the Basque Energy Board, EVE, is committed to research activities such as the Mutriku Oscillating Water Column plant, OWC. This is an experimental facility whose concept consists of a turbine located in a pneumatic energy collection chamber and a doubly fed induction generator that converts energy extracted by the turbine into a form that can be returned to the network. The turbo-generator control requires a precise knowledge of system parameters and of the rotor angular velocity in particular. Thus, to remove the rotor speed sensor implies a simplification of the hardware that is always convenient in rough working conditions. In this particular case, a Luenberger based observer is considered and the effectiveness of the proposed control is shown by numerical simulations. Comparing these results with those obtained using a traditional speed sensor, it is shown that the proposed solution provides better performance since it increases power extraction in the sense that it allows a more reliable and robust performance of the plant, which is even more relevant in a hostile environment as the ocean.

An austerity-driven energy reform

In July 2013, the government approved a major overhaul of the Spanish electricity sector to correct existing imbalances that have led to an exponential increase of regulated electricity costs and a huge tariff deficit. The reform addresses the problem of financial sustainability of the sector, severely affected by weak demand and overcapacity. Previous regulation introduced in 2012 and early 2013, also aimed at restoring financial stability of the sector, failed to correct the tariff shortfall and new regulatory measures were needed to reduce the 4.5 billion euros forecasted deficit for 2013. The frequent change of the rules of the game in the sector has created regulatory uncertainty, more so as it is not clear that the present reform will be sufficient to eliminate the deficit. Moreover, the government has left the door open to new regulation that would deal with the price formation system. In general, short run financial criteria have prevailed, while efficiency principles and a long run perspective have little weight in the reform.

Agent based modeling of energy networks

Attempts to model any present or future power grid face a huge challenge because a power grid is a complex system, with feedback and multi-agent behaviors, integrated by generation, distribution, storage and consumption systems, using various control and automation computing systems to manage electricity flows. Our approach to modeling is to build upon an established model of the low voltage electricity network which is tested and proven, by extending it to a generalized energy model. But, in order to address the crucial issues of energy efficiency, additional processes like energy conversion and storage, and further energy carriers, such as gas, heat, etc., besides the traditional electrical one, must be considered. Therefore a more powerful model, provided with enhanced nodes or conversion points, able to deal with multidimensional flows, is being required. This article addresses the issue of modeling a local multi-carrier energy network. This problem can be considered as an extension of modeling a low voltage distribution network located at some urban or rural geographic area. But instead of using an external power flow analysis package to do the power flow calculations, as used in electric networks, in this work we integrate a multiagent algorithm to perform the task, in a concurrent way to the other simulation tasks, and not only for the electric fluid but also for a number of additional energy carriers. As the model is mainly focused in system operation, generation and load models are not developed.

Divergences in the Long Run Trends in the Price of Energy and of Energy Services

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