Energies2014, 7(9), 6063-6082; doi:10.3390/en7096063 (registering DOI) - published 16 September 2014 Show/Hide Abstract
Abstract: The Federal Government of Brazil has ambitious plans to build a system of 58 additional hydroelectric dams in the Brazilian Amazon, with Hundreds of additional dams planned for other countries in the watershed. Although hydropower is often billed as clean energy, we argue that the environmental impacts of this project are likely to be large, and will result in substantial loss of biodiversity, as well as changes in the flows of ecological services. Moreover, the projects will generate significant greenhouse gas emissions from deforestation and decay of organic matter in the reservoirs. These emissions are equivalent to the five years of emissions that would be generated by gas powered plants of equivalent capacity. In addition, we examine the economic benefits of the hydropower in comparison to new alternatives, such as photovoltaic energy and wind power. We find that current costs of hydropower exceed alternatives, and the costs of costs of these alternatives are likely to fall substantially below those of hydropower, while the environmental damages from the dams will be extensive and irreversible.
Energies2014, 7(9), 6050-6062; doi:10.3390/en7096050 - published 15 September 2014 Show/Hide Abstract
Abstract: This paper addresses a multiagent-based distributed load shedding scheme to restore frequency for the microgrids during islanded operation. The objective of the proposed scheme is to realize a distributed load shedding considering its associated cost and the capacity of the flexible loads. There are two advantages of the proposed scheme: (1) it is a distributed scheme using average-consensus theorem, which can discover the global information when only communications between immediate neighboring agents are used, moreover it can meet the requirements of plug-and-play operations more easily than a centralized scheme; (2) it is a new adaptive load shedding through the comprehensive weights which take into accounts the cost of load shedding and the capacity of flexible loads, these comprehensive weights are evaluated locally by making use of the adaptability and intelligence characteristics of agents. Simulation results in power systems computer aided design (PSCAD) illustrate the validity and adaptability of the proposed load shedding scheme.
Energies2014, 7(9), 6031-6049; doi:10.3390/en7096031 - published 12 September 2014 Show/Hide Abstract
Abstract: This paper proposes an algorithm for fault detection, faulted phase and winding identification of a three-winding power transformer based on the induced voltages in the electrical power system. The ratio of the induced voltages of the primary-secondary, primary-tertiary and secondary-tertiary windings is the same as the corresponding turns ratio during normal operating conditions, magnetic inrush, and over-excitation. It differs from the turns ratio during an internal fault. For a single phase and a three-phase power transformer with wye-connected windings, the induced voltages of each pair of windings are estimated. For a three-phase power transformer with delta-connected windings, the induced voltage differences are estimated to use the line currents, because the delta winding currents are practically unavailable. Six detectors are suggested for fault detection. An additional three detectors and a rule for faulted phase and winding identification are presented as well. The proposed algorithm can not only detect an internal fault, but also identify the faulted phase and winding of a three-winding power transformer. The various test results with Electromagnetic Transients Program (EMTP)-generated data show that the proposed algorithm successfully discriminates internal faults from normal operating conditions including magnetic inrush and over-excitation. This paper concludes by implementing the algorithm into a prototype relay based on a digital signal processor.
Energies2014, 7(9), 6013-6030; doi:10.3390/en7096013 - published 12 September 2014 Show/Hide Abstract
Abstract: The paper proposes a generic methodology to incorporate constraints (pollutant emission, battery health, drivability) into on-line energy management strategies (EMSs) for hybrid electric vehicles (HEVs) and plug-in hybrid electric vehicles (PHEVs). The integration of each constraint into the EMS, made with the Pontryagin maximum principle, shows a tradeoff between the fuel consumption and the constraint introduced. As state dynamics come into play (catalyst temperature, battery cell temperature, etc.), the optimization problem becomes more complex. Simulation results are presented to highlight the contribution of this generic strategy, including constraints compared to the standard approach. These results show that it is possible to find an energy management strategy that takes into account an increasing number of constraints (drivability, pollution, aging, environment, etc.). However, taking these constraints into account increases fuel consumption (the existence of a trade-off curve). This trade-off can be sometimes difficult to find, and the tools developed in this paper should help to find an acceptable solution quickly
Energies2014, 7(9), 5995-6012; doi:10.3390/en7095995 - published 10 September 2014 Show/Hide Abstract
Abstract: The state of charge (SOC) is important for the safety and reliability of battery operation since it indicates the remaining capacity of a battery. However, it is difficult to get an accurate value of SOC, because the SOC cannot be directly measured by a sensor. In this paper, an adaptive gain nonlinear observer (AGNO) for SOC estimation of lithium-ion batteries (LIBs) in electric vehicles (EVs) is proposed. The second-order resistor–capacitor (2RC) equivalent circuit model is used to simulate the dynamic behaviors of a LIB, based on which the state equations are derived to design the AGNO for SOC estimation. The model parameters are identified using the exponential-function fitting method. The sixth-order polynomial function is used to describe the highly nonlinear relationship between the open circuit voltage (OCV) and the SOC. The convergence of the proposed AGNO is proved using the Lyapunov stability theory. Two typical driving cycles, including the New European Driving Cycle (NEDC) and Federal Urban Driving Schedule (FUDS) are adopted to evaluate the performance of the AGNO by comparing with the unscented Kalman filter (UKF) algorithm. The experimental results show that the AGNO has better performance than the UKF algorithm in terms of reducing the computation cost, improving the estimation accuracy and enhancing the convergence ability.
Energies2014, 7(9), 5953-5994; doi:10.3390/en7095953 - published 10 September 2014 Show/Hide Abstract
Abstract: There is an increasing tendency of turning the current power grid, essentially unaware of variations in electricity demand and scattered energy sources, into something capable of bringing a degree of intelligence by using tools strongly related to information and communication technologies, thus turning into the so-called Smart Grid. In fact, it could be considered that the Smart Grid is an extensive smart system that spreads throughout any area where power is required, providing a significant optimization in energy generation, storage and consumption. However, the information that must be treated to accomplish these tasks is challenging both in terms of complexity (semantic features, distributed systems, suitable hardware) and quantity (consumption data, generation data, forecasting functionalities, service reporting), since the different energy beneficiaries are prone to be heterogeneous, as the nature of their own activities is. This paper presents a proposal on how to deal with these issues by using a semantic middleware architecture that integrates different components focused on specific tasks, and how it is used to handle information at every level and satisfy end user requests.