Variability Of Wind Energy Research Articles

A probabilistic determination of required reserve levels in an energy and reserve co-optimized electricity market with variable generation

The determination of the required reserve levels due to the incremental trend of injecting wind energy into the power grid with a high level of wind energy penetration is complicated because of the variability of wind energy. This study proposes a method, based on the logarithmic barrier interior point method for optimal power flow and Monte Carlo analysis, to evaluate the required reserve levels for a grid with variable generation. A Gaussian distribution was used to model the dynamic load demand, while a unique linearized least-square approximation was used to model the wind turbines. In order to demonstrate the capability of the proposed algorithm, the methodology was applied to a modified IEEE 30-bus system with two wind-farms. The simulation results showed that the determined reserve requirement was considerably reduced compared with that obtained with classical approaches. The proposed method also satisfies all the considered constraints and maintains system reliability.

Scaling of wind energy variability over space and time

We use a large data set of simulated wind energy production in the United States to quantify the geographic and temporal scaling of energy output variability reduction when multiple sites are aggregated. We add to the existing literature on “geographic smoothing” by (i) quantifying the scaling of geographic smoothing over multiple spatial and temporal scales; (ii) bounding such smoothing through the use of an algorithm that produces minimum-variance sets of wind energy production sites; and (iii) quantifying inherent tradeoffs in optimizing wind energy site selection to minimize output variability along a specific frequency. The number of wind farms required to minimize output variability increases linearly with spatial scale of aggregation, but the scaling factor is small, on the order of 10-6 relative to geographic distances. These scaling factors increase by a factor of two as the frequency considered increases by three orders of magnitude (minutes to months). Our analysis indicates that optimizing wind deployment over one particular frequency increases output variability over other frequencies by nearly 30% in some cases.

지역 기후 앙상블 예측을 활용한 한반도 풍력 에너지의 시·공간적 변동성 연구

지역 기후 앙상블 예측을 활용한 한반도 풍력 에너지의 시·공간적 변동성 연구

Combined Heat and Power Dispatch Considering Pipeline Energy Storage of District Heating Network

The regional integration of variable wind power could be restricted by a strong coupling of electric power generation dispatch and heat supply of combined heat-and-power (CHP) units. The coupling in cold seasons precludes CHPs from providing the necessary flexibility for managing the wind power dispatch. The lack of flexibility problem can be tackled by exploiting the energy storage capability of a district heating network (DHN) which decouples the strong linkage of electric power and heat supplies. In this paper, a combined heat and power dispatch (CHPD) is formulated to coordinate the operation of electric power system (EPS) and district heating system (DHS). The proposed CHPD model which is solved by an iterative method considers the temperature dynamics of DHN for exploiting energy storage as an option for managing the variability of wind energy. The simulation results are discussed for several test systems to demonstrate the potential benefits of the proposed method in terms of operation economics, wind power utilization, as well as the potential benefits for real systems.

Coordination of Interdependent Natural Gas and Electricity Infrastructures for Firming the Variability of Wind Energy in Stochastic Day-Ahead Scheduling

In this paper, the coordination of constrained electricity and natural gas infrastructures is considered for firming the variability of wind energy in electric power systems. The stochastic security-constrained unit commitment is applied for minimizing the expected operation cost in the day-ahead scheduling of power grid. The low cost and sustainable wind energy could substitute natural gas-fired units, which are constrained by fuel availability and emission. Also, the flexibility and quick ramping capability of natural gas units could firm the variability of wind energy. The electricity and natural gas network constraints are considered in the proposed model (referred to as EGTran) and Benders decomposition is adopted to check the natural gas network feasibility. The autoregressive moving average (ARMA) time-series model is used to simulate wind speed forecast errors in multiple Monte Carlo scenarios. Illustrative examples demonstrate the effectiveness of EGTran for firming the variable wind energy by coordinating the constrained electricity and natural gas delivery systems.

Quantifying the variability of wind energy

Wind by its very nature is a variable element. Its variation is different on different timescales and spatially its magnitude can change dramatically depending on local climatology and terrain. This has implications in a variety of sectors, not least in the wind energy sector. The accuracy of weather forecasting models has increased significantly in the last few decades and these models are able to give an insight into variability on the hourly and daily timescales. On shorter timescales, predicting chaotic turbulent fluctuations is far more challenging. Similarly, the ability to make seasonal forecasts is extremely limited. General circulation models (GCMs) can give insights into possible future decadal fluctuations, but there are still large uncertainties. Observational data can give useful information concerning variation on a variety of timescales, but data quality and spatial coverage can be variable. An understanding of local scale spatial variations in wind is extremely important in wind farm siting. In the last 40 years, there have been significant advances in predicting these variations using computer models, although there remain significant challenges in understanding the behavior of the wind in certain environments. Both the spatial and temporal variations of wind are important considerations when wind power is integrated into electricity networks, and this will become an ever more important consideration as wind generation makes an increasing contribution to our global energy needs. WIREs Energy Environ 2014, 3:330–342. doi: 10.1002/wene.95This article is categorized under: Wind Power > Climate and Environment Energy Infrastructure > Economics and Policy

Changes in the economic value of wind energy and flexible resources at increasing penetration levels in the Rocky Mountain Power Area

ABSTRACTWe use a consistent economic framework to estimate the long‐run economic value of wind while including operational constraints for conventional generation and hourly variation in wind and load. Day‐ahead forecast errors in wind are corrected in the real‐time, after commitment decisions for many thermal generators have already been made. The framework is used to estimate the change in the marginal economic value of wind with increasing penetration in the Rocky Mountain Power Area of the USA. We also evaluate the marginal economic benefit to wind energy of implementing several strategies to manage wind energy variability and uncertainty: more flexible conventional generation, real‐time pricing, low cost bulk energy storage, and increased geographic diversity of wind plant siting. Without mitigation, the marginal economic value of wind is found to decrease by $21 MWh (37% of the marginal value of wind at 0% penetration) as wind penetration increases from 0% to 30%. The decline is largely because of the hourly profile of wind output and day‐ahead wind energy forecast errors; factors whose impact is reduced by the mitigation strategies. With mitigation, the marginal value of wind at the 30% penetration level is $6‐$11 MWh greater than the value without the measures (17‐31% increase in value). Although the marginal value of wind energy decreases with increasing penetration in this region, several different types of mitigation strategies are available and should be investigated in more detail. Copyright © 2013 John Wiley & Sons, Ltd.

Enhancing the Dispatchability of Variable Wind Generation by Coordination With Pumped-Storage Hydro Units in Stochastic Power Systems

The ever-increasing penetration of variable wind energy in power systems affects the hourly dispatch of thermal power generation in electricity markets. The variability of wind energy, which makes the wind energy non-dispatchable and difficult to control, could bring significant challenges to power system operators. The hourly coordination of wind power generation units with pumped-storage hydro (PS) generation could relieve the variability of wind energy and increase its dispatchability. The wind-PS coordination is based on the application of stochastic security-constrained unit commitment (stochastic SCUC). In this study, the coordinated hourly bus-level scheduling of wind-PS is compared with the coordinated system-level operation strategies in the day-ahead scheduling of power systems.

Regional integration of renewable energy systems in Ireland – The role of hybrid energy systems for small communities

Due to a lack of indigenous fossil energy resources, Ireland’s energy supply constantly teeters on the brink of political, geopolitical, and geographical unease. The potential risk to the security of the energy supply combined with the contribution of anthropogenic greenhouse gas emissions to climate change gives a clear indication of Ireland’s need to reduce dependency on imported fossil fuels as primary energy source. A feasibility analysis to investigate the available renewable energy options was conducted using HOMER software. The net present cost, the cost of energy, and the CO2 emissions of each potential energy combination were considered in determining the most suitable renewable and non-renewable hybrid energy system. Wind energy was shown to have the greatest potential for renewable energy generation in Ireland: wind energy was a component of the majority of the optimal hybrid systems both in stand-alone and grid-connected systems. In 2010 the contribution of wind energy to gross electricity consumption in Ireland approximated 10%, and the results of this feasibility study indicate that there is great potential for wind-generated energy production in Ireland. Due to the inherent variability of wind energy the grid-connected system results are particularly relevant, which show that in more than half of the analyses investigating electrical energy demand the incorporation of wind energy offset the CO2 emissions of the non-renewable elements to such a degree that the whole system had negative CO2 emissions, which has serious implications for Kyoto Protocol emissions limits. Ireland also has significant potential for hydropower generation despite only accounting for 2% of the gross electricity consumption in 2010. Wind and hydro energy should therefore be thoroughly explored to secure an indigenous primary energy source in Ireland.

Electricity systems with near-zero emissions of CO 2 based on wind energy and coal gasification with CCS and hydrogen storage

Emissions from electricity generation will have to be reduced to near-zero to meet targets for reducing overall greenhouse gas emissions. Variable renewable energy sources such as wind will help to achieve this goal but they will have to be used in conjunction with other flexible power plants with low-CO 2 emissions. A process which would be well suited to this role would be coal gasification hydrogen production with CCS, underground buffer storage of hydrogen and independent gas turbine power generation. The gasification hydrogen production and CO 2 capture and storage equipment could operate at full load and only the power plants would need to operate flexibly and at low load, which would result in substantial practical and economic advantages. This paper analyses the performances and costs of such plants in scenarios with various amounts of wind generation, based on data for power demand and wind energy variability in the UK. In a scenario with 35% wind generation, overall emissions of CO 2 could be reduced by 98–99%. The cost of abating CO 2 emissions from the non-wind residual generation using the technique proposed in this paper would be less than 40% of the cost of using coal-fired power plants with integrated CCS.

Optimal Expansion Planning for the Deployment of Wind Energy

With the growing concern regarding climate change, the integration of renewable electric technologies into the grid has taken on increased importance over the past decade. In particular, the integration of wind energy is increasing the attention paid to power transmission investment planning, generation adequacy, and secure system operation. This attention calls for the development of new tools that can simultaneously address the economics, transmission, ancillary services, and reserve requirements associated with wind energy. This paper proposes a method for choosing the optimal plan for expanding transmission and generation considering optimal power flow, discrete plant sizes, and the resource variability of wind energy. The method minimizes total cost, i.e., the sum of the construction cost and the operation cost, to fulfill expected load. Due to the nature of transmission expansion planning and the economies of scale associated with conventional power plants, finding the expansion plan is an integer p...