Combined hydro-wind generation bids in a pool-based electricity market

Present regulatory trends are promoting the irect participation of wind energy in electricity markets. The final result of these markets sets the production scheduling for the operation time, including a power commitment from the wind generators. However, wind resources are uncertain, and the final power delivered usually differs from the initial power committed. This imbalance produces an overcost in the system, which must be paid by those who produce it, e.g., wind generators among others. As a result, wind farm revenue decreases, but it could increase by allowing wind farms to submit their bids to the markets together with a hydro generating unit, which may easily modify its production according to the expected imbalance. This paper presents a stochastic optimization technique that maximizes the joint profit of hydro and wind generators in a pool-based electricity market, taking into account the uncertainty of wind power prediction.En prens

Forecasting wind speed data by using a combination of ARIMA model with single exponential smoothing

Wind serves as natural resources as the solution to minimize global warming and has been commonly used to produce electricity. Because of their uncontrollable wind characteristics, wind speed forecasting is considered one of the best challenges in developing power generation. The Autoregressive Integrated Moving Average (ARIMA), Simple Exponential Smoothing (SES) and a hybrid model combination of ARIMA and SES will be used in this study to predict the wind speed. The mean absolute percentage error (MAPE) and the root mean square error (RMSE) are used as measurement of efficiency. The hybrid model provides a positive outcome for predicting wind speed compare to the single model of ARIMA and SES

Using conditional kernel density estimation for wind power density forecasting

Of the various renewable energy resources, wind power is widely recognized as one of the most promising. The management of wind farms and electricity systems can benefit greatly from the availability of estimates of the probability distribution of wind power generation. However, most research has focused on point forecasting of wind power. In this paper, we develop an approach to producing density forecasts for the wind power generated at individual wind farms. Our interest is in intraday data and prediction from 1 to 72 hours ahead. We model wind power in terms of wind speed and wind direction. In this framework, there are two key uncertainties. First, there is the inherent uncertainty in wind speed and direction, and we model this using a bivariate VARMA-GARCH (vector autoregressive moving average-generalized autoregressive conditional heteroscedastic) model, with a Student t distribution, in the Cartesian space of wind speed and direction. Second, there is the stochastic nature of the relationship of wind power to wind speed (described by the power curve), and to wind direction. We model this using conditional kernel density (CKD) estimation, which enables a nonparametric modeling of the conditional density of wind power. Using Monte Carlo simulation of the VARMA-GARCH model and CKD estimation, density forecasts of wind speed and direction are converted to wind power density forecasts. Our work is novel in several respects: previous wind power studies have not modeled a stochastic power curve; to accommodate time evolution in the power curve, we incorporate a time decay factor within the CKD method; and the CKD method is conditional on a density, rather than a single value. The new approach is evaluated using datasets from four Greek wind farms

Financial viability of offshore wind on the Texas Gulf Coast

Offshore wind is already a significant component of the electricity generation mix in Europe, and improvements in technology and cost are enabling increased offshore wind penetration in new markets around the world. Thus far, the US has struggled to materially participate in this industry, with only a single 30 MW offshore project in operation. Navigating a complicated regulatory framework, the lack of a coherent national policy, and facing local opposition, the industry has experienced some spectacular failures in recent years. However, the US now has an opportunity to take advantage of the lessons learned from years of (primarily) European development and combine them with excellent offshore wind resources close to transmission-constrained load centers. By far the leader of the US onshore wind industry, and with a long history of offshore oil and gas development, Texas has some major advantages when it comes to offshore wind. Wind resources in the Gulf of Mexico are more than adequate for economic production. With shallow depths and relatively calm seas, the Texas Gulf Coast is also well suited to offshore wind construction. These factors, coupled with a pro-development state regulatory scheme and extended jurisdiction over submerged lands, suggest that Texas is an ideal candidate for offshore wind development. With no currently active projects in the pipeline, this thesis examines the economic viability of offshore wind development on the Texas Gulf Coast at the project level. Using an ideal location and cost data from National Renewable Energy Laboratory (NREL), the Energy Information Administration (EIA), and industry sources, a hypothetical “test project” was developed and evaluated against three cost estimate cases and ten regulatory scenarios. These inputs were fed into a Discounted Cash Flow model to determine potential competitiveness in the Power Purchase Agreement (PPA) market in the ERCOT region. Results indicate that without significant cost reductions or major changes to either market conditions or federal/state incentive schemes, Texas Gulf Coast offshore wind cannot compete with other forms of onshore renewable generation. With ever-decreasing costs, it is not impossible that offshore wind could become viable at some point in the future, but given current conditions, it is not likely that any projects are on the near-term horizon.Energy and Earth Resource

Renewable energy integration into the Australian National Electricity Market: Characterising the energy value of wind and solar generation

This paper examines how key characteristics of the underlying wind and solar resources may impact on their energy value within the Australian National Electricity Market(NEM). Analysis has been performed for wind generation using half hour NEM data for South Australia over the 2008-9 financial year. The potential integration of large scale solar generation has been modelled using direct normal solar radiant energy measurements from the Bureau of Meteorology for six sites across the NEM. For wind energy, the level and variability of actual wind farm outputs in South Australia is analysed. High levels of wind generation in that State have been found to have a strong secondary effect on spot prices. Wind generation's low operating costs will see it displacing higher operating cost fossil-fuel plant at times of high wind. At the same time, the increased variability of wind may impose additional challenges and costs on conventional plant which will also be reflected in wholesale spot market prices. It is shown that this is proving particularly important during high wind penetration periods, which are contributing to an increased frequency of low or even negative prices. The solar resource in South Australia is shown to be highly variable; however, as seen with wind power, geographical dispersion of generators can significantly reduce power variability, even with as few as six sites. The correlation of the solar resource with spot prices also appears to be superior to wind generation. Modelling using the Adelaide solar resource showed that, for electricity sold into the spot market, two-axis tracking solar generators would achieve an average price that is over twice that received by wind generators over the year 2008-9 analysed. Of course, significant solar generation deployment might drive similar price impacts as seen with wind generation, thereby reducing this advantage. Considering the potential implications of both major wind and solar generation within South Australia, the solar and wind resources within the State appear, on average, to be non-correlated for the magnitude, and the change in magnitude, across half an hour. The analysis shows that solar and wind resources within the NEM have key characteristics that can markedly impact on their energy value within the wholesale electricity market. High levels of renewable electricity are already affecting spot prices, highlighting the need for low bidding renewable generators to attain power purchase contracts and for developers to consider this effect when choosing a site location for renewable generators. Other generators within the NEM may also be significantly impacted by major renewable energy deployment. The long-term success of renewable generation will likely depend on maximising the energy value that it contributes to the electricity industry.Energy value, Integration, NEM, Solar, Variability, Wind, Environmental Economics and Policy, Resource /Energy Economics and Policy,

Wind Energy in Egypt: Economic Feasibility for Cairo

Motivated by the rise of the electricity tariffs applied on industrial customer and the frequent electricity cut offs recently experienced in Egypt, this paper assesses the economic feasibility of installing a stand alone wind energy technology by an industrial customer who seeks to reduce his dependency on the national grid. For this purpose, the wind energy potential at the wind regime of Cairo was chosen to be assessed using half an hour wind speed data for a full one-year period (2009). The Weibull parameters of the wind speed distribution function were estimated by employing the maximum likelihood approach. The estimation revealed that Cairo has poor wind resources. Despite the poor resources, the financial analysis has shown that under certain parameters the wind project can prove to be financially viable. Thus harnessing wind energy through stand alone systems can help in meeting the industries electric power needs.Renewable energy, wind resources, Weibull distribution, electricity

Incorporating geostrophic wind information for improved space-time short-term wind speed forecasting

Accurate short-term wind speed forecasting is needed for the rapid development and efficient operation of wind energy resources. This is, however, a very challenging problem. Although on the large scale, the wind speed is related to atmospheric pressure, temperature, and other meteorological variables, no improvement in forecasting accuracy was found by incorporating air pressure and temperature directly into an advanced space-time statistical forecasting model, the trigonometric direction diurnal (TDD) model. This paper proposes to incorporate the geostrophic wind as a new predictor in the TDD model. The geostrophic wind captures the physical relationship between wind and pressure through the observed approximate balance between the pressure gradient force and the Coriolis acceleration due to the Earth's rotation. Based on our numerical experiments with data from West Texas, our new method produces more accurate forecasts than does the TDD model using air pressure and temperature for 1- to 6-hour-ahead forecasts based on three different evaluation criteria. Furthermore, forecasting errors can be further reduced by using moving average hourly wind speeds to fit the diurnal pattern. For example, our new method obtains between 13.9% and 22.4% overall mean absolute error reduction relative to persistence in 2-hour-ahead forecasts, and between 5.3% and 8.2% reduction relative to the best previous space-time methods in this setting.Comment: Published in at http://dx.doi.org/10.1214/14-AOAS756 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Co-located wave and offshore wind farms: A preliminary approach to the shadow effect

In recent years, with the consolidation of offshore wind technology and the progress carried out for wave energy technology, the option of combine both technologies has arisen. This combination rest mainly in two main reasons: in one hand, to increase the sustainability of both energies by means of a more rational harnessing of the natural resources; in the other hand, to reduce the costs of both technologies by sharing some of the most important costs of an offshore project. In addition to these two powerful reasons there are a number of technology synergies between wave and wind systems which makes their combination even more suitable. Co-located projects are one of the alternatives to combine wave-wind systems, and it is specially for these project were so-called shadow effect synergy becomes meaningful. In particular, this paper deals with the co-location of Wave Energy Conversion (WEC) technologies into a conventional offshore wind farm. More specifically, an overtopping type of WEC technology was considered in this work to study the effects of its co-location with a conventional offshore wind park. This study aims to give a preliminary approach to the shadow effect and its implications for both wave and offshore wind energies

NIGERIA’S ENERGY CHALLENGE AND POWER DEVELOPMENT: THE WAY FORWARD

The ever increasing demand and meager supply of energy in Nigeria has been a great challenge to her development. This situation is becoming critical, with increasing population not balanced by an adequate energy development programme. The incessant power generation failure has grossly affected the economy, seriously slowing down development in rural and sub-rural settlements, with present energy policy mainly benefiting urban dwellers. Globally, energy projections stipulate that between 2002 and 2025, global energy needs may rise by over 34%, with that of developing nations doubling this percentage. A robust solution must be found to end the nation’s energy crises. This Viewpoint compares the energy potential of Nigeria with the challenges faced. Nigeria receives a huge amount of solar radiation, has abundant wind energy resources, and large deposits of fossil fuel, as well as enormous hydro-power resources from Niger and Benue Rivers. However, of these about 80% of hydro-power remains untapped, the total 5.5KW-hr/m2/day of solar radiation is not utilized and wind energy resources remain unexploited. The solution lies in creating a mixed supply of energy in which as yet untapped renewable resources are combined with abundant nonrenewable fossil fuel, including the massive quantities of gas wasted from crude oil exploitation