Abstract: As the solar photovoltaic (PV) matures, the economic feasibility of PV projects are increasingly being evaluated using the levelized cost of electricity (LCOE) generation in order to be compared to other electricity generation technologies. Unfortunately, there is lack of clarity of reporting assumptions, justifications and degree of completeness in LCOE calculations, which produces widely varying and contradictory results. This paper reviews the methodology of properly calculating the LCOE for solar PV, correcting the misconceptions made in the assumptions found throughout the literature. Then a template is provided for better reporting of LCOE results for PV needed to influence policy mandates or make invest decisions. A numerical example is provided with variable ranges to test sensitivity, allowing for conclusions to be drawn on the most important variables. Grid parity is considered when the LCOE of solar PV is comparable with grid electrical prices of conventional technologies and is the industry target for cost-effectiveness. Given the state of the art in the technology and favorable financing terms it is clear that PV has already obtained grid parity in specific locations and as installed costs continue to decline, grid electricity prices continue to escalate, and industry experience increases, PV will become an increasingly economically advantageous source of electricity over expanding geographical regions.

Abstract: As the solar photovoltaic (PV) matures, the economic feasibility of PV projects are increasingly being evaluated using the levelized cost of electricity (LCOE) generation in order to be compared to other electricity generation technologies. Unfortunately, there is lack of clarity of reporting assumptions, justifications and degree of completeness in LCOE calculations, which produces widely varying and contradictory results. This paper reviews the methodology of properly calculating the LCOE for solar PV, correcting the misconceptions made in the assumptions found throughout the literature. Then a template is provided for better reporting of LCOE results for PV needed to influence policy mandates or make invest decisions. A numerical example is provided with variable ranges to test sensitivity, allowing for conclusions to be drawn on the most important variables. Grid parity is considered when the LCOE of solar PV is comparable with grid electrical prices of conventional technologies and is the industry target for cost-effectiveness. Given the state of the art in the technology and favorable financing terms it is clear that PV has already obtained grid parity in specific locations and as installed costs continue to decline, grid electricity prices continue to escalate, and industry experience increases, PV will become an increasingly economically advantageous source of electricity over expanding geographical regions.

Abstract: Motivated by the power-grid-side challenges in the integration of electric vehicles, we propose a decentralized protocol for negotiating day-ahead charging schedules for electric vehicles. The overall goal is to shift the load due to electric vehicles to fill the overnight electricity demand valley. In each iteration of the proposed protocol, electric vehicles choose their own charging profiles for the following day according to the price profile broadcast by the utility, and the utility updates the price profile to guide their behavior. This protocol is guaranteed to converge, irrespective of the specifications (e.g., maximum charging rate and deadline) of electric vehicles. At convergence, the l 2 norm of the aggregated demand is minimized, and the aggregated demand profile is as “flat” as it can possibly be. The proposed protocol needs no coordination among the electric vehicles, hence requires low communication and computation capability. Simulation results demonstrate convergence to optimal collections of charging profiles within few iterations.

Abstract: This Deliverable of ANEMOS.plus (Advanced Tools for the Management of Electricity Grids with Large-Scale Wind Generation) and SafeWind projects presents the state of the art in wind power forecasting. More than 380 references of journal and conference papers have been reviewed. (LN)

Abstract: Plug-in hybrid electric vehicles are a midterm solution to reduce the transportation sector's dependency on oil. However, if implemented in a large scale without control, peak load increases significantly and the grid may be overloaded. Two algorithms to address this problem are proposed and analyzed. Both are based on a forecast of future electricity prices and use dynamic programming to find the economically optimal solution for the vehicle owner. The first optimizes the charging time and energy flows. It reduces daily electricity cost substantially without increasing battery degradation. The latter also takes into account vehicle to grid support as a means of generating additional profits by participating in ancillary service markets. Constraints caused by vehicle utilization as well as technical limitations are taken into account. An analysis, based on data of the California independent system operator, indicates that smart charge timing reduces daily electricity costs for driving from $0.43 to $0.2. Provision of regulating power substantially improves plug-in hybrid electric vehicle economics and the daily profits amount to $1.71, including the cost of driving.

Abstract: This paper examines the problem of optimally splitting driver power demand among the different actuators (i.e., the engine and electric machines) in a plug-in hybrid electric vehicle (PHEV). Existing studies focus mostly on optimizing PHEV power management for fuel economy, subject to charge sustenance constraints, over individual drive cycles. This paper adds three original contributions to this literature. First, it uses stochastic dynamic programming to optimize PHEV power management over a distribution of drive cycles, rather than a single cycle. Second, it explicitly trades off fuel and electricity usage in a PHEV, thereby systematically exploring the potential benefits of controlled charge depletion over aggressive charge depletion followed by charge sustenance. Finally, it examines the impact of variations in relative fuel-to-electricity pricing on optimal PHEV power management. The paper focuses on a single-mode power-split PHEV configuration for mid-size sedans, but its approach is extendible to other configurations and sizes as well.

Abstract: This paper is the first global analysis of the potential energy savings which could be found in electric motor- driven system (EMDS). EMDS currently accounts for more than 40% of global electricity consumption. Huge untapped energy efficiency potential was found in EMDS; around 25 % of EMDS electricity use could be saved cost-effectively, which would reduce total global electricity demand by about 10%. To date, energy efficiency opportunities with EMDS have been relatively neglected in comparison with other sustainable energy opportunities. It is crucial to scale up operations and resources committed to realizing the vast potential energy savings and this paper proposes a comprehensive package of policy recommendations to help governments achieve these significant energy savings in EMDS.

Abstract: The purpose of this review is examination of the present scenario of electricity production and investigation of whether an electricity powered world is possible, indicating which primary energy forms should be preferably utilized. Currently, most of the primary energy used by mankind, including that employed to generate electricity, comes from fossil fuels, which need to be phased out because they bring about severe damage to climate, environment, and human health and, additionally, their stock will be largely depleted during the present century. All the energy technologies poised to replace those based on fossil fuels, namely nuclear and renewables (wind, hydro, concentrated solar power, photovoltaics, biomass, geothermal, tidal, wave) essentially produce electricity, and this suggests that we will progressively shift to an electricity-based economy over the course of the 21st century. The economic, technical, ethical and social issues entangled with nuclear technologies and the unexpectedly fast expansion of renewable energies (particularly wind and solar) point to an increasingly important role of the latter in electricity generation. The present one way utility-to-customer energy system, designed over one century ago, will need substantial reshaping to enable the build up of a smart grid capable of dealing with variable renewable supply and fluctuating end-user demand by exchange of information between customer and utility. To accomplish this result, effort in research and development of storage devices and facilities on the small (e.g., batteries, capacitors) and large (e.g., pumped hydro, compressed air storage, electrolytic hydrogen) scale is needed. In the medium and long term, the expansion of electricity production will also likely lead to progressive replacement of internal combustion engines with electric motors in the automotive sector, accompanied by a shift from individual to mass transportation systems. We have still a long way out of the fossil fuel era, but this challenge can be won only if carbon-free electricity largely replaces the direct combustion of irreplaceable and climate-altering fossil fuel resources.

Abstract: Greenhouse gas emissions, air pollution in urban areas, and dependence on fossil fuels are among the challenges threatening the sustainable development of the transportation sector. Plug-in hybrid electric vehicle (PHEV) technology is one of the most promising solutions to tackle the situation. While PHEVs partially rely on electricity from the power grid, they raise concerns about their negative impacts on power generation, transmission, and distribution installations. On the other hand, they have the potential to be used as a distributed energy storage system for the grid. Therefore, they can pave the way for a more sustainable power grid in which renewable resources are widely employed. Positive and negative impacts of PHEVs on the power grid cannot be thoroughly examined unless extensive data on the utilization of each individual PHEV are available. For instance, in order to estimate the aggregated impact of PHEVs on the electricity demand profile, one needs to know 1) when each PHEV would begin its charging process, 2) how much electrical energy it would require, and 3) how much power would be needed. This paper extracts and analyzes the data that are available through national household travel surveys (NHTS). Three charging scenarios are considered in order to obtain various PHEV charging load profiles (PCLPs). Further, the characteristics of each developed PCLP are studied. Finally, the effects of three suggested policies on the derived PCLPs are examined.

Abstract: Twenty states plus the District of Columbia now have renewable portfolio standards (RPS) in place that requires a certain percentage of energy to come from renewable sources by a specific year. With renewable energy on the verge of massive growth, much research emphasis is put on enabling the implementation of these technologies. This paper presents a novel method of site selection for wind turbine farms in New York State, based on a spatial cost–revenue optimization. The algorithm used for this is built in ESRI ArcGIS Desktop 9.3.1 software and consists of three stages. The first stage excludes sites that are infeasible for wind turbine farms, based on land use and geological constraints. The second stage identifies the best feasible sites based on the expected net present value from four major cost and revenue categories that are spatially dependent: revenue from generated electricity, costs from access roads, power lines and land clearing. The third stage assesses the ecological impacts on bird and their habitats. The proposed spatial multi-criteria methodology is then implemented in New York State and the results were compared with the locations of existing wind turbine farms. The wind farm site selection tool presented in this paper provides insights into the most feasible sites for a large geographic area based on user inputs, and can assist the planning of wind developers, utilities, ISO's and State governments in attaining renewable portfolio standards.

Abstract: We present methods for analyzing commercial and industrial facility 15-min-interval electric load data. These methods allow building managers to better understand their facility's electricity consumption over time and to compare it to other buildings, helping them to “ask the right questions” to discover opportunities for demand response, energy efficiency, electricity waste elimination, and peak load management. We primarily focus on demand response. Methods discussed include graphical representations of electric load data, a regression-based electricity load model that uses a time-of-week indicator variable and a piecewise linear and continuous outdoor air temperature dependence and the definition of various parameters that characterize facility electricity loads and demand response behavior. In the future, these methods could be translated into easy-to-use tools for building managers.

Abstract: Various studies have attempted to consolidate published estimates of water use impacts of electricity generating technologies, resulting in a wide range of technologies and values based on different primary sources of literature. The goal of this work is to consolidate the various primary literature estimates of water use during the generation of electricity by conventional and renewable electricity generating technologies in the United States to more completely convey the variability and uncertainty associated with water use in electricity generating technologies.

Abstract: Over the past decade, state policies on renewable energy have been on the rise in the United States, providing states with various options for encouraging the generation of renewable electricity. Two promising policies, the Renewable Portfolio Standard (RPS) and the Mandatory Green Power Option (MGPO), have been implemented in many states but the evidence about their effectiveness is mixed. In this paper, we argue that recognizing the natural, social and policy context under which MGPO and RPS are adopted is necessary in order to measure their true effectiveness. This is because the context rather than the policy might lead to positive outcomes and there is the possibility for sample bias. When controlling for the context in which the policies are implemented, we find that RPS has a negative impact on investments in renewable capacity. However, we find that investor-owned utilities seem to respond more positively to RPS mandates than publicly owned utilities. By contrast, MGPO appears to have a significant effect on installed renewable capacity for all utilities regardless of the context in which it is implemented.

Abstract: Electricity demand forecasting is a central and integral process for planning periodical operations and facility expansion in the electricity sector. Demand pattern is almost very complex due to the deregulation of energy markets. Therefore, finding an appropriate forecasting model for a specific electricity network is not an easy task. Although many forecasting methods were developed, none can be generalized for all demand patterns. Therefore, this paper presents a pragmatic methodology that can be used as a guide to construct Electric Power Load Forecasting models. This methodology is mainly based on decomposition and segmentation of the load time series. Several statistical analyses are involved to study the load features and forecasting precision such as moving average and probability plots of load noise. Real daily load data from Kuwaiti electric network are used as a case study. Some results are reported to guide forecasting future needs of this network.

Abstract: Bioelectrochemical systems (BESs) are devices capable of converting organic waste fraction present in wastewaters into useful energy vectors such as electricity or hydrogen. In recent years a large amount of research has been done on these unique systems in order to improve their performance both in terms of waste treatment as well as electric current production. Already there are plans to upscale this technology to convince the end-users of its potential. However, there are not many studies available on the life cycle of these systems with the current state of the art. In this article a methodology has been proposed to perform the life cycle assessment (LCA) of the BESs and some recommendations have been given which may be useful in carrying out LCA of these systems. Not only the direct benefits in terms of energy saved in aerating the wastewater treatment plants, but also the resulting saving in cost and electric power produced should be factored as well. The results of LCA should show that with current knowledge and existing materials, how well the MFCs compares with the existing treatment methods such as anaerobic digestion. Further, given the amount of research going on in this field, it is expected that with cheaper materials and better microorganisms, the technology will breakthrough even soon.

Abstract: This study revisits the relationship between electricity consumption and economic growth in Pakistan by controlling and investigating the effects of two major production factors - capital and labor. The empirical evidence confirms the cointegration among the variables and indicates that electricity consumption has a positive effect on economic growth. Moreover, bi-directional Ganger causality between electricity consumption and economic growth has been found. The findings suggests that adoption of electricity conservation policies to conserve energy resources may unwittingly decline growth and the lower growth rate will in turn further decrease the demand for electricity. Therefore, governments contemplating such conservationist policies should instead explore and develop alternate sources of energy as a strategy rather than just increasing electricity production per se in order to meet the rising demand for electricity in their quest towards sustaining development in the country.

Abstract: With the development of power system deregulation and smart metering technologies, price-based demand response (DR) becomes an alternative solution to improving power system reliability and efficiency by adjusting the load profile. In this paper, we simulate an electricity market with DR from different types of commercial buildings by using agent-based modeling and simulation (ABMS) techniques. We focus on the consumption behavior of commercial buildings with different levels of DR penetration in different market structures. The results indicate that there is a noticeable impact from commercial buildings with price-responsive demand on the electricity market, and this impact differs with different scales of DR participation under different levels of market competitions.