Cost Efficient Distributed Load Frequency Control in Power Systems

The introduction of new technologies and increased penetration of renewable resources is altering the power distribution landscape which now includes a larger numbers of micro-generators. The centralized strategies currently employed for performing frequency control in a cost efficient way need to be revisited and decentralized to conform with the increase of distributed generation in the grid. In this paper, the use of Multi-Agent and Multi-Objective Reinforcement Learning techniques to train models to perform cost efficient frequency control through decentralized decision making is proposed. More specifically, we cast the frequency control problem as a Markov Decision Process and propose the use of reward composition and action composition multi-objective techniques and compare the results between the two. Reward composition is achieved by increasing the dimensionality of the reward function, while action composition is achieved through linear combination of actions produced by multiple single objective models. The proposed framework is validated through comparing the observed dynamics with the acceptable limits enforced in the industry and the cost optimal setups

Load Frequency Control: A Deep Multi-Agent Reinforcement Learning Approach

The paradigm shift in energy generation towards microgrid-based architectures is changing the landscape of the energy control structure heavily in distribution systems. More specifically, distributed generation is deployed in the network demanding decentralised control mechanisms to ensure reliable power system operations. In this work, a Multi-Agent Reinforcement Learning approach is proposed to deliver an agentbased solution to implement load frequency control without the need of a centralised authority. Multi-Agent Deep Deterministic Policy Gradient is used to approximate the frequency control at the primary and the secondary levels. Each generation unit is represented as an agent that is modelled by a Recurrent Neural Network. Agents learn the optimal way of acting and interacting with the environment to maximise their long term performance and to balance generation and load, thus restoring frequency. In this paper we prove using three test systems, with two, four and eight generators, that our Multi-Agent Reinforcement Learning approach can efficiently be used to perform frequency control in a decentralised way

Biodiversity offsetting and conservation: Reframing nature to save it

AbstractBiodiversity offsetting involves the balancing of biodiversity loss in one place (and at one time) by an equivalent biodiversity gain elsewhere (an outcome referred to as No Net Loss). The conservation science literature has chiefly addressed the extent to which biodiversity offsets can serve as a conservation tool, focusing on the technical challenges of its implementation. However, offsetting has more profound implications than this technical approach suggests. In this paper we introduce the concept of policy frames, and use it to identify four ways in which non-human nature and its conservation are reframed by offsetting. Firstly, offsetting reframes nature in terms of isolated biodiversity units that can be simply defined, measured and exchanged across time and space to achieve equivalence between ecological losses and gains. Secondly, it reframes biodiversity as lacking locational specificity, ignoring broader dimensions of place and deepening a nature–culture and nature–society divide. Thirdly, it reframes conservation as an exchange of credits implying that the value of non-human nature can be set by price. Fourthly, it ties conservation to land development and economic growth, foreshadowing and bypassing an oppositional position. We conclude that by presenting offsetting as a technical issue, the problem of biodiversity loss due to development is depoliticized. As a result the possibility of opposing and challenging environmental destruction is foreclosed, and a dystopian future of continued biodiversity loss is presented as the only alternative.This study was supported by a Marie Curie Intra-European Fellowship (PIEF-GA-2013-622631) within the 7th European Community Framework Programme (Conservation and Ecosystem Services in the New Biodiversity Economy).This is the final version of the article. It first appeared from Cambridge University Press via https://doi.org//10.1017/S003060531500078

Neoliberal Capitalism and Conservation in the Post-crisis Era: The Dialectics of "Green" and "Un-green" Grabbing in Greece and the UK

“Green-grabbing”, in which environmental arguments support expropriation of land and resources, is a recognized element in neoliberal conservation. However, capitalism’s strategic interest in promoting the neoliberalization of conservation is accompanied by attempts to exploit hitherto protected natures without any pretence at “greenness”. In this paper we explore the dialectics between “green” and “un-green” grabbing as neoliberal strategies in the reconstruction of nature conservation policies after the 2008 financial “crash” in Greece and the UK. In both countries, accelerated neoliberalization is manifested in diverse ways, including initiatives to roll back conservation regulation, market-based approaches to “saving” nature and the privatization of public nature assets. The intensification of “green” and “un-green” grabbing reflects capitalism’s strategic interest in both promoting and obstructing nature conservation, ultimately leaving for “protected natures” two choices: either to be further degraded to boost growth or to be “saved” through their deeper inclusion as commodities visible to the market.This study was partly supported by an Aristeia Fellowship awarded to Dr Apostolopoulou by the Research Committee of Aristotle University of Thessaloniki in 2013, and by Marie Curie Fellowship(PIEF-GA-2013-622631 CESINE.This is the accepted manuscript. The final version is available from Wiley at http://onlinelibrary.wiley.com/doi/10.1111/anti.12102/abstract

Optimal Dispatch of Pumped Storage Hydro Cascade under Uncertainty

In this paper, we propose an optimal dispatch scheme for a pumped storage hydro cascade that maximizes the energy per cubic meter of water in the system taking into account uncertainty in the net load variations. To this end, we introduce a model to describe the behaviour of a pumped storage hydro cascade and formulate its optimal dispatch. We then incorporate forecast scenarios in the optimal dispatch, and define a robust variant of the developed system. The resulting optimization problem is intractable due to the infinite number of constraints. Using tools from robust optimization, we reformulate the resulting problem in a tractable form that is amenable to existing numerical tools and show that the computed dispatch is immunised against uncertainty. The efficacy of the proposed approach is demonstrated by means of a realistic case study based on the Seven Forks system located in Kenya

Micro-contactors for kinetic estimation of multiphase chemistries

The revolutionary Alpha process developed by Lucite International (LI) is an industrially advantageous process over the traditional route of acetone cyanhydrin for the production of methyl methacrylate (MMA). The Alpha process entails two stages. The first stage is an homogeneous catalysis process, a methoxycarbonylation reaction which produces methyl propionate (MeP) from ethylene, CO and methanol using a Pd catalyst stabilised with the 1,2-bis(di-tert-butylphosphinomethyl)benzene (dtbpx) phosphine ligand developed by LI. As it is known, kinetics are important for reactor modelling and simulation, interpretation of reaction mechanisms and catalytic phenomena. The kinetics of the methoxycarbonylation reaction are the subject of this research project and have been studied using a 2 L autoclave reactor and a 0.573 ml volume and 11.7 m length capillary microreactor with similar results. A bespoke experimental rig was designed and built to accommodate the micro devices. A theoretical investigation on the significance of mass transfer effects was undertaken to assess the significance of mass transfer limitations and both reactors were found to operate in the kinetic regime. A hydrodynamics study of Taylor flow under reaction conditions in a 6 m, 0.25 mm ID capillary microreactor was conducted to provide better understanding of the flow and improve its characteristics before the execution of kinetic experiments. The effects of methanol and Pd concentration, CO and ethylene partial pressure on the reaction rate have been studied. The reaction was found to be first and zero order with respect to methanol and ethylene respectively while the fractional order of 0.74 was derived with respect to Pd. CO inhibition kinetics were observed for high CO partial pressures and the reaction order was found to shift from positive to negative at pCO equal to 1.8 bar. The effect of temperature has been investigated in the range 80-120 oC and the activation energy was found to be 53 kJ/mol. A molecular level approach was used to derive a rate equation assuming the methanolysis step as the rate-controlling step. A software package was employed for the estimation of the rate parameters at the reaction conditions of 100 oC and 10 bar of gas pressure. Finally, a significant part of this research was spent on the design and development of a mesh microreactor of rectangular shape with dimensions 3 cm x 3 cm x 1.4 mm incorporating a 2 μm silicon nitride mesh with the aim to perform kinetic experiments but unfortunately this device was proved unsuitable for operation at high pressure

Cutting nature to fit: Urbanization, neoliberalism and biodiversity offsetting in England

In this paper, by drawing on primary empirical data obtained through 62 interviews in seven case studies we seek to offer a Marxist historical-geographical analysis of biodiversity offsetting policy in England, and its emergence in the context of the global economic crisis, and government aspirations for large-scale urban development projects. By paying attention to the interplay between offsetting, urbanization and the neoliberal reconstruction of conservation, we aim to extend the focus of the neoliberal conservation literature from the role of offsets as ecological 'commodities' to the way offsetting is used to support the production of space(s), place(s) and nature(s) in line with contemporary patterns of capitalist urban growth. In particular, we show how offsetting operationalized new ideas about nature as a stock of biodiversity, how it streamlined planning to support extended urbanization, how it foreclosed public debate about controversial urban development projects, and how it reterritorialized nature-society relationships. We also give a central role to social contestation against the implementation of offsetting in England, drawing attention to its class character and highlighting the potential for a new emancipatory politics that would encompass a 'right to nature' as a key element of struggles for the 'right to the city'.This study was supported by a Marie Curie Intra-European Fellowship (PIEF-GA-2013-622631) within the 7th European Community Framework Programme (Conservation and Ecosystem Services in the New biodiversity Economy) awarded to Dr. Elia Apostolopoulou in 2013. Dr. Apostolopoulou has also received funding from the Rachel Carson Center for Environment and Society (RCC)

Localized inhibition in the Drosophila mushroom body

Many neurons show compartmentalized activity, in which activity does not spread readily across the cell, allowing input and output to occur locally. However, the functional implications of compartmentalized activity for the wider neural circuit are often unclear. We addressed this problem in the Drosophila mushroom body, whose principal neurons, Kenyon cells, receive feedback inhibition from a non-spiking interneuron called the anterior paired lateral (APL) neuron. We used local stimulation and volumetric calcium imaging to show that APL inhibits Kenyon cells’ dendrites and axons, and that both activity in APL and APL’s inhibitory effect on Kenyon cells are spatially localized (the latter somewhat less so), allowing APL to differentially inhibit different mushroom body compartments. Applying these results to the Drosophila hemibrain connectome predicts that individual Kenyon cells inhibit themselves via APL more strongly than they inhibit other individual Kenyon cells. These findings reveal how cellular physiology and detailed network anatomy can combine to influence circuit function