8,821 research outputs found

    Inexactness of the Hydro-Thermal Coordination Semidefinite Relaxation

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    Hydro-thermal coordination is the problem of determining the optimal economic dispatch of hydro and thermal power plants over time. The physics of hydroelectricity generation is commonly simplified in the literature to account for its fundamentally nonlinear nature. Advances in convex relaxation theory have allowed the advent of Shor's semidefinite programming (SDP) relaxations of quadratic models of the problem. This paper shows how a recently published SDP relaxation is only exact if a very strict condition regarding turbine efficiency is observed, failing otherwise. It further proposes the use of a set of convex envelopes as a strategy to successfully obtain a stricter lower bound of the optimal solution. This strategy is combined with a standard iterative convex-concave procedure to recover a stationary point of the original non-convex problem.Comment: Submitted to IEEE PES General Meeting 201

    Rural electrification in central america and east africa, two case studies of sustainable microgrids

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    This paper deals with the electrification of rural villages in developing countries using Sustainable Energy Systems. The rural electrification feasibility study is done using Hybrid Optimization Model for Electric Renewable PRO (HOMER PRO). The HOMER PRO energy modelling software is an optimization software improved by U.S. National Renewable Energy Laboratory. It helps in designing, comparing and optimizing the design of power generation technologies. In this paper, two rural electrification case studies are modelled and analysed using HOMER PRO. Technical and economic evaluation criteria are applied to study the feasibility of a micro-hydro plant in El DĂ­ptamo (Honduras), and a hybrid plant composed of photovoltaic module arrays, Diesel generators, and flow batteries, in a small island on Victoria Lake. For both cases, we show the results of the studies of the daily and yearly loads, of the resources available in the area and the economic evaluation of the chosen plants configuration

    Power plant preventive maintenance scheduling problem: a 0/1 mixed integer linear programming approach based on cost and reliability to establish an effective policy

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    The problem addressed is the Power Plant Preventive Maintenance Scheduling. The problem is taken from the power industry and it requires determining the perioThis paper addresses the Power Plant Preventive Maintenance Scheduling Problem. The problem is taken from the power industry, where providing electric energy to the consumers without interruption is of high importance. This problem is usually treated in the long-term exploitation of electric production systems. It requires determining the period for which generating units of an electric power utility should be taken offline for planned preventive maintenance over a time horizon, usually on a yearly basis. The objective is to minimize the total operating cost while a set of constraints is satisfied, with emphasis on realiability.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

    Incorporating life cycle external cost in optimization of the electricity generation mix

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    The present work aims to examine the strategic decision of future electricity generation mix considering, together with all other factors, the effect of the external cost associated with the available power generation technology options, not only during their operation but also during their whole life cycle. The analysis has been performed by integrating the Life Cycle Assessment concept into a linear programming model for the yearly decisions on which option should be used to minimize the electricity generation cost. The model has been applied for the case of Greece for the years 2012-2050 and has led to several interesting results. Firstly, most of the new generating capacity should be renewable (mostly biomass and wind), while natural gas is usually the only conventional fuel technology chosen. If externalities are considered, wind energy increases its share and hydro-power replaces significant amounts of biomass-generated energy. Furthermore, a sensitivity analysis has been performed. One of the most important findings is that natural gas increases its contribution when externalities are increased. Summing-up, external cost has been found to be a significant percentage of the total electricity generation cost for some energy sources, therefore significantly changing the ranking order of cost-competitiveness for the energy sources examined

    Hydroelectric power plant management relying on neural networks and expert system integration

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    The use of Neural Networks (NN) is a novel approach that can help in taking decisions when integrated in a more general system, in particular with expert systems. In this paper, an architecture for the management of hydroelectric power plants is introduced. This relies on monitoring a large number of signals, representing the technical parameters of the real plant. The general architecture is composed of an Expert System and two NN modules: Acoustic Prediction (NNAP) and Predictive Maintenance (NNPM). The NNAP is based on Kohonen Learning Vector Quantization (LVQ) Networks in order to distinguish the sounds emitted by electricity-generating machine groups. The NNPM uses an ART-MAP to identify different situations from the plant state variables, in order to prevent future malfunctions. In addition, a special process to generate a complete training set has been designed for the ART-MAP module. This process has been developed to deal with the absence of data about abnormal plant situations, and is based on neural nets trained with the backpropagation algorithm.Publicad

    A novel incentive-based demand response model for Cournot competition in electricity markets

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    This paper presents an analysis of competition between generators when incentive-based demand response is employed in an electricity market. Thermal and hydropower generation are considered in the model. A smooth inverse demand function is designed using a sigmoid and two linear functions for modeling the consumer preferences under incentive-based demand response program. Generators compete to sell energy bilaterally to consumers and system operator provides transmission and arbitrage services. The profit of each agent is posed as an optimization problem, then the competition result is found by solving simultaneously Karush-Kuhn-Tucker conditions for all generators. A Nash-Cournot equilibrium is found when the system operates normally and at peak demand times when DR is required. Under this model, results show that DR diminishes the energy consumption at peak periods, shifts the power requirement to off-peak times and improves the net consumer surplus due to incentives received for participating in DR program. However, the generators decrease their profit due to the reduction of traded energy and market prices

    EFFECTIVE SEDIMENT CONTROL IN A RESERVOIR

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    Sedimentation in a reservoir cannot be avoided. The average rate of sedimentation on the storage volume reduction of a reservoir in the world is about 1 % per year (Yoon,1992), meanwhile, the storage volume reduction in several reservoir in Indonesia reaches 1,64% to 2,83% per year (Atmojo,2012). These sediment’s accumulations in the reservoir will continually reduce the storage volume, thus the intended functions of reservoirs for flood control (Atmojo, 2013), irrigation and water supply, electric generation, etc. will also reduced and not optimal. Some of sediment control measures have been practiced in reducing sediment accumulation in reservoirs around the world. In principle, there are two approaches i.e., reduce the sediment input to a reservoir by land conservation, construction of check dam, sand pocket, diversion channel, etc. and reduce the sedimentation in the reservoir by sluicing, turbidity current, dredging, and flushing (Morris and Fan, 1998; Emamgholizadeh et al., 2006). This paper presents the performance of sediment’s reduction from a reservoir by flushing, sluicing, and disturbing flushing based on some laboratories results (Atmojo,2012). It is expected that this paper can contribute to elicits some finding on the selection of which suitable method for sediment reduction from a reservoir

    Optimizing Hydroelectric Power Generation: The Case of Shiroro Dam

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    Abstract—Hydroelectric power, one of the most important sources of mass generation of electric power, is a renewable source of energy. The amount of electricity that can be produced by a hydro-electricity generating system depends on systemic variables viz; plant efficiency, volumetric water flow through the turbine and the head of the water from the water surface to the turbine. The availability of the Water in the reservoir is a function of some hydrological variables principal among which are rainfall, reservoir inflows and evaporation. Understanding the dynamics of these variables, and the correlation between them are core to proper planning and management of a hydroelectric power station. In this Study, simple mathematical methods that include linear programming and statistical analysis based on simulation techniques were used to evaluate vital parameters based on the hydrologic data obtained from the Hydrologic Units of the Shiroro Power Stations in Nigeria. The overall aim of the study is to idealize power generation at Shiroro dam in and out of rain season so as to ensure optimum generation of electricity all year round in order to achieve energy sufficiency in Nigeria
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