A stochastic approach for the operation of a wind and pumped storage plant under a deregulated environment

To improve the competiveness in the energy market, it is necessary that the wind power plants provide guaranteed power generation, although, it is not possible to forecast power availability from wind power plant accurately. This paper presents a stochastic model and solution technique for the combined operation of wind and pumped storage power plants to improve the power availability and increasing the profit considering uncertainties of wind power generation. In this model, uncertainties in wind data have been forecasted for grid connected day-ahead market using Weibull distribution model. The imbalances in the forecasted wind data and the market demand have been reduced by operating the pumped storage power plant. In this stochastic mixed integer problem, pumped storage plant can take the supply either from the grid or from the wind power plant for the pumping operation to store the energy in order to utilize this energy during peak hours for increasing the overall revenue. The reliability of the pumped storage is improved by replacing the conventional unit with the adjustable speed type pumped storage unit. In order to prove the optimality of the solution, two case studies were considered. In case study–I, scheduling is provided by operating the conventional pumped storage unit, whereas in case study–II, adjustable speed pumped storage unit has been used. It has been found that the adjustable speed pumped storage unit has further reduced the imbalance between generated power and demand. The complete approach has been formulated and implemented using AMPL software.     

环境风险预测数学模型

本文基于环境风险预测分析的基本思想,应用模糊图、灰色系统、非线性回归、随机过程和可靠性系统工程理论和方法,探讨了环境风险预测的数学模型。给出了环境风险预测的双向模糊图模型、灰色马尔夫预测模型及非线性回归模型,这些模型的应用为环境风险评价和环境风险管理提供了科学依据。     

A hybrid model based on smooth transition periodic autoregressive and Elman artificial neural network for wind speed forecasting of the Hebei region in China

Wind energy, one of the most promising renewable and clean energy sources, is becoming increasingly significant for sustainable energy development and environmental protection. Given the relationship between wind power and wind speed, precise prediction of wind speed for wind energy estimation and wind power generation is important. For proper and efficient evaluation of wind speed, a smooth transition periodic autoregressive (STPAR) model is developed to predict the six-hourly wind speeds. In addition, the Elman artificial neural network (EANN)-based error correction technique has also been integrated into the new STPAR model to improve model performance. To verify the developed approach, the six-hourly wind speed series during the period of 2000–2009 in the Hebei region of China is used for model construction and model testing. The proposed EANN-STPAR hybrid model has demonstrated its powerful forecasting capacity for wind speed series with complicated characteristics of linearity, seasonality and nonlinearity, which indicates that the proposed hybrid model is notably efficient and practical for wind speed forecasting, especially for the Hebei wind farms of China.     

Modeling flood induced interdependencies among hydroelectricity generating infrastructures

This paper presents a new kind of integrated modeling method for simulating the vulnerability of a critical infrastructure for a hazard and the subsequent interdependencies among the interconnected infrastructures. The developed method has been applied to a case study of a network of hydroelectricity generating infrastructures, e.g., water storage concrete gravity dam, penstock, power plant and transformer substation. The modeling approach is based on the fragility curves development with Monte Carlo simulation based structural–hydraulic modeling, flood frequency analysis, stochastic Petri net (SPN) modeling, and Markov Chain analysis. A certain flood level probability can be predicted from flood frequency analysis, and the most probable damage condition for this hazard can be simulated from the developed fragility curves of the dam. Consequently, the resulting interactions among the adjacent infrastructures can be quantified with SPN analysis; corresponding Markov Chain analysis simulates the long term probability matrix of infrastructure failures. The obtained results are quite convincing to prove the novel contribution of this research to the field of infrastructure interdependency analysis which might serve as a decision making tool for flood related emergency response and management.     

Performance enhancement of a stand-alone induction generator-based wind energy system using neural network controller

ABSTRACT

The limitation of self-excited induction generator (SEIG) when used in the stand-alone wind energy system (WES) is poor voltage regulation at variable speed. The indirect vector control (IVC) technique is employed for both the generator-side converter (GSC) and load-side converter (LSC) to regulate the variation of SEIG speed, DC link voltage, and electromagnetic torque independently. Further performance of the proposed IVC technique has been analyzed independently with neural network controller (NNC) and fuzzy logic controller (FLC) as its components. The FLC is replaced by an NNC to improve the performance of the proposed system. IVC of SEIG-based WES has been simulated in MATLAB/SIMULINK software, and the prototype model of the proposed WES is developed to experimentally validate the performance using dSPACE DS-1104 R&D controller board.     

Large-scale baseload wind power in China

This paper presents a novel strategy for developing wind power in large-scale (multi-GW) wind farms in China. It involves combining oversized wind farms, large-scale electrical storage and long-distance transmission lines to deliver 'baseload wind power' to distant electricity demand centers. Baseload wind power is typically more valuable to the electric utility than intermittent wind power, so that storage can be economically attractive even in instances where the cost per kWh is somewhat higher than without storage.
The prospective costs for this approach to developing wind power are illustrated by modifying an oversized wind farm at Huitengxile, Inner Mongolia. The site has an average power density of 580 W/m² at 50 m hub heights and is located 500 km north of Beijing. Using locally mass-produced wind turbines there are good prospects that wind power would be cost-competitive with coal power, on a lifecycle cost basis, while providing substantial net environmental benefits.
Finally, the institutional challenges related to the prospect of large-scale wind energy development are addressed. Especially important are policies aimed at developing the capacity for mass production of as much of this technology in China as is feasible. Promising instruments for speeding up the introduction of this technology include: (i) international joint ventures between foreign vendors and developers and Chinese manufacturers; and (ii) wind resource development concessions.     

A convective wind resource model for Solar Vortex power generation

ABSTRACT

Climate change has increased the need for clean, nonpolluting energy sources to decrease dependence on fossil fuels. Alternative energy sources, mainly solar and horizontal wind, have been the primary focus for producing clean energy. New technologies are being developed, such as the Solar Vortex (SoV), which was developed at the Georgia Institute of Technology, and relies on a vertical wind resource to generate power. The National Renewable Energy Lab (NREL) has resource models representing solar and horizontal wind resources across the 48 United States. This research developed a vertical wind resource model that is comparable in resolution to NREL’s solar and horizontal wind resource models and uses the model for estimating power output for the SoV. This model complements NREL’s existing resource models and supports the deployment of an additional clean energy generation technology. The model was applied to Mesa, Arizona to find feasible sites for a small-scale vertical wind farm.     

AN EARLY WARNING SYSTEM FOR DROUGHT MANAGEMENT USING THE PALMER DROUGHT INDEX1

ABSTRACT: The Palmer Drought Severity Index (PDSI) is used in a non-homogeneous Markov chain model to characterize the stochastic behavior of drought. Based on this characterization an early warning system in the form of a decision tree enumerating all possible sequences of drought progression is proposed for drought management. Besides yielding probabilities of occurrence of different drought severity classes, the method associates a secondary measure in terms of likely cumulative precipitation deficit to provide timely guidance in deciding drought mitigation actions. The proposed method is particularly useful for water availability task forces in various states for issuing drought warnings in advance. The applicability of the technique is illustrated for the Tidewater climatic division of Virginia.     

Discourses of on-farm wind energy generation in the UK farming press

As the owners of the majority of land in the U.K., farmers are well placed to contribute to renewable energy targets. Media coverage can both drive and reflect farmers’ views about renewable energy but has been largely unexplored to date. This article uses discourse analysis to examine the evolution of coverage of one form of renewable energy – on-farm wind – in the U.K. farming press from 1980 to 2013. We identified a diverse debate with five major discourses. On-farm wind turbines are alternatively represented as: profitable farm diversification opportunities; producers of clean energy; important for rural development and sources of conflict. Although press coverage predominantly encourages wind energy production, a further discourse advises farmers to ‘Proceed with Caution’. While emphasising images and values which have widespread affinity among U.K. farmers, the press have increasingly employed an economic frame, constructing wind energy generation as a farm diversification strategy. The most recent farming press coverage predominantly encourages an instrumental approach to wind energy, crowding out other (non-economic) rationales and marginalising local community concerns. This appears to reflect the financial orientation of recent policy support (particularly Feed-in Tariffs), and may have long-term costs in enabling sustainable energy production systems.     

Risk-based optimal operation of hybrid power system using multiobjective optimization

ABSTRACT

This paper solves an optimal generation scheduling problem of hybrid power system considering the risk factor due to uncertain/intermittent nature of renewable energy resources (RERs) and electric vehicles (EVs). The hybrid power system considered in this work includes thermal generating units, RERs such as wind and solar photovoltaic (PV) units, battery energy storage systems (BESSs) and electric vehicles (EVs). Here, the two objective functions are formulated, i.e., minimization of operating cost and system risk, to develop an optimum scheduling strategy of hybrid power system. The objective of proposed approach is to minimize operating cost and system risk levels simultaneously. The operating cost minimization objective consists of costs due to thermal generators, wind farms, solar PV units, EVs, BESSs, and adjustment cost due to uncertainties in RERs and EVs. In this work, Conditional Value at Risk (CVaR) is considered as the risk index, and it is used to quantify the risk due to intermittent nature of RERs and EVs. The main contribution of this paper lies in its ability to determine the optimal generation schedules by optimizing operating cost and risk. These two objectives are solved by using a multiobjective-based nondominated sorting genetic algorithm-II (NSGA-II) algorithm, and it is used to develop a Pareto optimal front. A best-compromised solution is obtained by using fuzzy min-max approach. The proposed approach has been implemented on modified IEEE 30 bus and practical Indian 75 bus test systems. The obtained results show the best-compromised solution between operating cost and system risk level, and the suitability of CVaR for the management of risk associated with the uncertainties due to RERs and EVs.     

Improving the dynamic response of frequency and power in a wind integrated power system by optimal design of compensated superconducting magnetic energy storage

The frequency deviation and power fluctuation need to be controlled in a wind-integrated power system (WIPS) for keeping the balance between system power generation and demand, which support the quality and stability of overall power system. The present paper addresses this problem while concerning the integration of intermittent wind power and load disturbance into the WIPS. With this intent, it proposes the compensated superconducting magnetic energy storage (CSMES) system with proportional integral derivative (PID) controller for improving the frequency and power deviation profile. A novel swarm intelligence-based artificial bee colony (ABC) algorithm is used for optimal design of PID-CSMES system. Robustness of the proposed ABC-based PID-CSMES control strategy is tested in WIPS under various disturbance patterns of load and wind power. To demonstrate the improved dynamic response, their simulation results are compared with particle swarm optimization-based PID-CSMES, PID with SMES, and only PID controller technique. The performance indices and transient response characteristics of frequency and power deviation are used to evaluate and compare the accuracy and efficiency of each controller. Stability of various system configurations is analyzed using eigenvalue location. Comparing the results of different controller in WIPS indicates a substantial improvement in the dynamic response of system frequency and power deviations by utilizing the proposed control strategy.     

A case study of an isolated wind powered electricity system meeting 100% of local demand

Using meteorological and electricity demand data for a 4-year period, electricity demand in Shetland was modeled to provide an estimate of the demand over a 30-year period from 1 January 1981. That modeled demand was then compared to estimated wind power output over the same period using the WAsP model. The wind farm output was estimated for a range of sizes of wind farm up to the consented 370 MW Viking Wind Farm in Shetland. Some wind power was available for 94% of the time and the 370 MW wind farm would meet 100% of demand for nearly 80% of the time. The statistics of single and accumulated deficits were calculated for a range of wind farms and estimates of the amount of additional generation capacity and additional power requirements were assessed. The study suggests that with storage, wind power in Shetland could meet all electricity demand in Shetland at around £130 to £150/MWh (excluding subsidy) and with a grid connection allowing the sale of excess power, those costs could be reduced.     

Quantized control settings based tuning of a heaving wave energy converter in irregular seas

The increasing awareness of environmental issues attracts more attention on environmentally friendly energy sources. This leads to increasing research on effective use of renewable energy sources. Among them, wave energy offers a high potential. The wave energy converter systems used for transforming the wave energy into electrical energy have been a main research topic for decades. However, only a few of these systems has been successfully implemented. There seems to be some technical problems one of which is on their control applications. It has been reported that by means of appropriate control implementation, the performance of the wave energy converter system could be improved considerably. In literature, many different control techniques are reported. They appear to be weak due to implementation related restrictions. The present study proposes a novel control technique that is far more practical based on quantization of control settings. Various quantization levels and their effect on system power capture performance are studied. The technique assumes use of realistic off-the-shelf components with realistic features. The proposed method utilizes time-series-analysis technique with online parameter estimation feature. This new method does not require any knowledge of previous or future states of any of the system or sea state parameters, but only the currently available and measurable ones. The approach of the new control technique sets it apart from most of the previously reported ones. Therefore, the proposed technique is not only very much practical but also very much useful in improvement of the system power performance relative to passive techniques.     

Economic dispatch of power system containing wind power and photovoltaic considering carbon trading and spare capacity variation

The drying up of the fossil energy sources and the damage from unchecked carbon emissions demand the development of low carbon economy, which promotes the development of new energy sources, such as wind power and photovoltaic. However, the direct connections of wind/photovoltaic power into power grid bring great impacts on power systems, thus affecting the security and stability of power system operations, which challenges the power system dispatching. In despite of many methods for power system dispatch, lack of the models, for power system containing wind power and photovoltaic considering carbon trading and spare capacity variation (PSCWPCCTSCV), restricts the further optimal operations of power systems. This paper studies the economic dispatch modeling problem of power system containing wind power and photovoltaic, establishes the model of economic dispatch of PSCWPCCTSCV. On this basis, adaptive immune genetic algorithm is applied to conduct the economic operation optimization, which can provide the optimal carbon trading price and the optimal power distribution coefficient. Finally, simulations based on the newly proposed models are made to illustrate the economic dispatch of PSCWPCCTSCV. The results show that optimization with the proposed model can not only weaken the volatility of the new energy effectively, but also reduce carbon emissions and reduce power generation costs.     

Disruption to place attachment and the protection of restorative environments: A wind energy case study

Deepening understanding of public responses to large-scale renewable energy projects is of academic and practical importance, given policies to lessen fossil fuel use in many countries. Although the NIMBY (Not In My Back Yard) concept is commonly used to explain public opposition, the concept has been extensively critiqued. This study applies an alternative approach based upon the notion of disruption to place attachment, and the theory of social representations, with a focus upon the symbolic meanings associated with a proposed project and the places affected by it. Empirical data is provided from a case study of a proposed 750 MW offshore wind farm in North Wales, using group discussions and questionnaires distributed to local residents in two coastal towns (n = 488). Results indicate significant differences between each town's residents in their responses to the project, and how opposition arises from nature/industry symbolic contradictions: between a place represented in terms of scenic beauty that provides a restorative environment for residents and visitors, and a wind farm that will industrialise the area and ‘fence’ in the bay. In one of the towns, the data suggests that contradiction between project and place was experienced as a threat to identity for those with strong place attachment, leading to negative attitudes and oppositional behaviour. Levels of trust in key actors moderated the relation between place attachment and negative attitudes to the wind farm. The results provide further evidence of the role of place attachment in shaping so-called ‘NIMBY’ responses to development proposals, and challenge the assumption that offshore wind farms will prove less controversial than those onshore.     

Conditions for a 100% renewable energy supply system in Japan and South Korea

In the wake of the Fukushima nuclear accident, alternative energy paths have been discussed for Japan, but except for a few studies the assumption is usually made that Japan is too densely populated to be suited for a near-100% sustainable, indigenous energy provision. The studies emphasizing renewable energy have proposed the use of photovoltaic power as the main source of electricity supply, in combination with diurnal battery storage and supplemented by other renewable sources such as wind, hydro, and geothermal power. Here, an alternative approach is explored, with wind and derived hydrogen production as the main energy source, but still using solar energy, biofuels, and hydropower in a resilient combination allowing full satisfaction of demands in all sectors of the economy, i.e., for dedicated electricity, transportation energy as well as heat for processes and comfort. Furthermore, the possible advantage of establishing a regional energy system with energy interchange and coordinated management of the mix of renewable energy resources across a wider region is discussed. As the closest neighbor, the energy system of South Korea is considered, first regarding the possibility of a similar full renewable energy reliance, and then for possible synergetic effects of connecting the Korean and the Japanese energy systems, in order to be able to better cope with the intermittency of renewable energy source flows.     

Environmental indices in irrigation management

Irrigation management calls for objective criteria capable of representing the economy, reliability, and productivity of irrigation systems. These criteria must be compatible with long-term sustainability and conservation goals. The criteria representing the above goals are the economic effect of management on yield reduction, economic effect, and reliability referring to plant growth and operation of the network. In this study environmental indices are introduced to express the above criteria in quantitative terms. The inclusion of these indices at the farm and network level create a multicriteria framework for decision-making based on composite programming. An experimental study was conducted during the irrigation periods of 1989 and 1990 in Chania, Greece, concerning water delivered to 40 experimental plots, soil moisture content at the rootzone, and irrigation system operational failures. The data collected in real time were used for the calculation of the corresponding environmental indices. The variation in time and space is high and resulted in up to 62% of yield loss and low system performance (up to 7% of system temporal reliability). The study indicated that environmental indices could be incorporated to select alternatives and also to develop policies on water delivery. The final decision involves a trade-off analysis between cost of application and desired system performance. Measures of both primary objectives can be obtained using environmental indices that represent system operation aggregation at its basic levels (on farm and network).     

A comparative analysis of wind resource parameters using WAsP and windPRO

This paper investigates the accuracy of the wind resource estimation for a site in a central India region using a latest licensed version of WAsP 11 and windPRO 3.1. Whole one year measured met mast wind data has been taken using anemometer and wind vane at 10 m and 25 m height, respectively above ground level. The digitized elevation and roughness model of the corresponding site shows the roughness class 4 (roughness length 1.2525 m). The wind data has been extrapolated up to 80 m height by using power and log law models which provide the power density near about 120 W/m². As per the micro sitting guidelines for the virtual wind farm installation 5D X 7D mapping has been selected which Indicates the total power output by installing 8 Vestas V-90 1.8 MW wind turbine from WAsP is 31.561 GWh and from windPRO is 28.083 GWh.     

RURAL ELECTRIFICATION: AN ALTERNATIVE FOR THE THIRD WORLD

Rural electrification is an essential element in development planning in developing countries. In the past, the conventional approach to rural electrification has been either to extend national grids from central power stations, or to install small diesel generators. This article explores a third alternative, namely the harnessing of such renewable sources of energy as solar, wind and biomass for the production of local electric power. The author outlines the concept of the Rural Energy Centre in comparison with the structure of energy needs, and responds to critics of this integrated approach to the problem of rural electrification.