Combining wind farms with concentrating solar plants to provide stable renewable power

We evaluate the extent to which a combination of wind power and concentrating solar power (CSP) may lead to stable and even baseload power by taking advantage of: 1) spatiotemporal balancing of solar and wind energy resources and 2) storage capabilities of CSP plants. A case study is conducted for the region of Andalusia in Spain. To this end, spatiotemporal variability of modeled CSP and wind capacity factors in a 3-km spatial resolution grid were analyzed based on principal component analysis (PCA) and canonical correlation analysis (CCA). Results reveal that renewable baseload power can be obtained in the study region by locating wind farms and CSP plants using balancing patterns derived from CCA and PCA. In addition, the power fluctuation reduction attained from these patterns was substantially higher than those obtained by interconnecting randomly-located wind farms and CSP plants across the study region. Results were particularly meaningful for the winter season. Upon considering storage capability of the CSP plants, results proved better. The main difference was a higher firm capacity value associated with spring and summer seasons. For the other seasons, the contribution of thermal storage capabilities of the CSP plants to stable power proved less relevant.     

Complementarity between solar and hydro power: Sensitivity study to climate characteristics in Northern-Italy

Climate related energy sources such as wind, solar and runoff sources are variable in time and space, following their driving weather variables. High penetration of such energy sources might be facilitated by using their complementarity in order to increase the balance between energy load and generation. This study presents the analysis of the effect of a 100% renewable energy mix composed by solar and run-of-the-river energy in Northern Italy where these two energy sources are the main alternative energy sources. Along a climate gradient from the Alpine crest (snow melt dominated area) to the Veneto plain (rainfall dominated area), solar power is generated in the flat plain, and run-of-the-river hydropower at two mountainous locations. Covering all possible mixes of these two sources, we analyze their complementarity across different temporal scales using two indicators: the standard deviation of the energy balance and the theoretical storage required for balancing generation and load. Results show that at small temporal scale (hourly), a high share of run-of-the-river power allows minimizing the energy balance variability. The opposite is obtained at larger temporal scales (daily and monthly) essentially because of lower variability of solar power generation, which also implies a lower storage requirement.     

Weather data and probability analysis of hybrid photovoltaic–wind power generation systems in Hong Kong

This paper describes a simulation model for analyzing the probability of power supply failure in hybrid photovoltaic–wind power generation systems incorporating a storage battery bank, and also analyzes the reliability of the systems. An analysis of the complementary characteristics of solar irradiance and wind power for Hong Kong is presented. The analysis of local weather data patterns shows that solar power and wind power can compensate well for one another, and can provide a good utilization factor for renewable energy applications. For the loss of power supply probability (LPSP) analysis, the calculation objective functions and restraints are set up for the design of hybrid systems and to assess their reliability. To demonstrate the use of the model and LPSP functions, a case study of hybrid solar–wind power supply for a telecommunication system is presented. For a hybrid system on the islands surrounding Hong Kong, a battery bank with an energy storage capacity of 3 days is suitable for ensuring the desired LPSP of 1%, and a LPSP of 0% can be achieved with a battery bank of 5 days storage capacity.     

Determining optimal electricity technology mix with high level of wind power penetration

Notwithstanding its variability and limited controllability, wind power is expected to contribute strongly to electricity generation from renewable energy sources in the coming decades. Treating wind power as non-dispatchable by subtracting its output from the original load profile, results in a net load profile, which must be covered by conventional power generation. The screening curve methodology is a first approximation to find the optimal generation technology mix, based on relative cost levels. However, increased variability of the net load profile, due to wind power generation, strongly influences system operation. Therefore a static linear programming investment model is developed to determine the optimal technology mix. This alternative methodology shows a reduced capacity of inflexible generation after including operational constraints to properly account for net load variability. In order to illustrate this methodology, an example is set up, showing the sensitivity with respect to ramp rates of conventional generation, transmission interconnection and energy storage. The comparison of those different sources of system flexibility suggests that energy storage facilities better facilitate the integration of wind power generation.     

A regime-dependent artificial neural network technique for short-range solar irradiance forecasting

Solar power can provide substantial power supply to the grid; however, it is also a highly variable energy source due to changes in weather conditions, i.e. clouds, that can cause rapid changes in solar power output. Independent systems operators (ISOs) and regional transmission organizations (RTOs) monitor the demand load and direct power generation from utilities, define operating limits and create contingency plans to balance the load with the available power generation resources. ISOs, RTOs, and utilities will require solar irradiance forecasts to effectively and efficiently balance the energy grid as the penetration of solar power increases. This study presents a cloud regime-dependent short-range solar irradiance forecasting system to provide 15-min average clearness index forecasts for 15-min, 60-min, 120-min and 180-min lead-times. A k-means algorithm identifies the cloud regime based on surface weather observations and irradiance observations. Then, Artificial Neural Networks (ANNs) are trained to predict the clearness index. This regime-dependent system makes a more accurate deterministic forecast than a global ANN or clearness index persistence and produces more accurate predictions of expected irradiance variability than assuming climatological average variability.     

Analyzing major challenges of wind and solar variability in power systems

Ambitious policy targets together with current and projected high growth rates indicate that future power systems will likely show substantially increased generation from renewable energy sources. A large share will come from the variable renewable energy (VRE) sources wind and solar photovoltaics (PV); however, integrating wind and solar causes challenges for existing power systems. In this paper we analyze three major integration challenges related to the structural matching of demand with the supply of wind and solar power: low capacity credit, reduced utilization of dispatchable plants, and over-produced generation. Based on residual load duration curves we define corresponding challenge variables and estimate their dependence on region (US Indiana and Germany), penetration and mix of wind and solar generation. Results show that the impacts of increasing wind and solar shares can become substantial, and increase with penetration, independently of mix and region. Solar PV at low penetrations is much easier to integrate in many areas of the US than in Germany; however, some impacts (e.g. over-production) increase significantly with higher shares. For wind power, the impacts increase rather moderately and are fairly similar in US Indiana and Germany.     

Evaluation of distributed building thermal energy storage in conjunction with wind and solar electric power generation

Energy storage is often seen as necessary for the electric utility systems with large amounts of solar or wind power generation to compensate for the inability to schedule these facilities to match power demand. This study looks at the potential to use building thermal energy storage as a load shifting technology rather than traditional electric energy storage. Analyses are conducted using hourly electric load, temperature, wind speed, and solar radiation data for a 5-state central U.S. region in conjunction with simple computer simulations and economic models to evaluate the economic benefit of distributed building thermal energy storage (TES). The value of the TES is investigated as wind and solar power generation penetration increases. In addition, building side and smart grid enabled utility side storage management strategies are explored and compared. For a relative point of comparison, batteries are simulated and compared to TES. It is found that cooling TES value remains approximately constant as wind penetration increases, but generally decreases with increasing solar penetration. It is also clearly shown that the storage management strategy is vitally important to the economic value of TES; utility side operating methods perform with at least 75% greater value as compared to building side management strategies. In addition, TES compares fairly well against batteries, obtaining nearly 90% of the battery value in the base case; this result is significant considering TES can only impact building thermal loads, whereas batteries can impact any electrical load. Surprisingly, the value of energy storage does not increase substantially with increased wind and solar penetration and in some cases it decreases. This result is true for both TES and batteries and suggests that the tie between load shifting energy storage and renewable electric power generation may not be nearly as strong as typically thought.     

A current and future state of art development of hybrid energy system using wind and PV-solar: A review

The wind and solar energy are omnipresent, freely available, and environmental friendly. The wind energy systems may not be technically viable at all sites because of low wind speeds and being more unpredictable than solar energy. The combined utilization of these renewable energy sources are therefore becoming increasingly attractive and are being widely used as alternative of oil-produced energy. Economic aspects of these renewable energy technologies are sufficiently promising to include them for rising power generation capability in developing countries. A renewable hybrid energy system consists of two or more energy sources, a power conditioning equipment, a controller and an optional energy storage system. These hybrid energy systems are becoming popular in remote area power generation applications due to advancements in renewable energy technologies and substantial rise in prices of petroleum products. Research and development efforts in solar, wind, and other renewable energy technologies are required to continue for, improving their performance, establishing techniques for accurately predicting their output and reliably integrating them with other conventional generating sources. The aim of this paper is to review the current state of the design, operation and control requirement of the stand-alone PV solar–wind hybrid energy systems with conventional backup source i.e. diesel or grid. This Paper also highlights the future developments, which have the potential to increase the economic attractiveness of such systems and their acceptance by the user.     

Economic and technical challenges of flexible operations under large-scale variable renewable deployment

Fundamental characteristics of solar and wind power have generated controversy about their economic competitiveness and appropriate techniques for assessing their value. This research presents an approach to quantify the economic value of variable renewable capacity and demonstrates its dependence on renewable deployment levels, regional resource endowments, fleet flexibility, and trade assumptions. It assesses economic and technical impacts of large-scale renewable penetration by linking two models, representing electric-sector investments and detailed operations. Model results for California and Texas suggest that operational constraints and costs of dispatchable generators (e.g., minimum load levels, ramping limits, startup costs) can impact renewable integration costs, but the temporal and spatial variability of solar and wind are larger determinants of their value. Restrictions on transmission and regional coordination in capacity planning and dispatch decrease the economic value of variable renewable energy, highlighting the potential roles of market design and trade. Energy storage is shown to be a valuable balancing asset at higher solar and wind penetration levels, but potential revenues diminish with increased storage deployment.     

Impact of hydrogen energy storage on California electric power system: Towards 100% renewable electricity

Decarbonization of the power sector is a key step towards greenhouse gas emissions reduction. Due to the intermittent nature of major renewable sources like wind and solar, storage technologies will be critical in the future power grid to accommodate fluctuating generation. The storage systems will need to decouple supply and demand by shifting electrical energy on many different time scales (hourly, daily, and seasonally). Power-to-Gas can contribute on all of these time scales by producing hydrogen via electrolysis during times of excess electrical generation, and generating power with high-efficiency systems like fuel cells when wind and solar are not sufficiently available. Despite lower immediate round-trip efficiency compared to most battery storage systems, the combination of devices used in Power-to-Gas allows independent scaling of power and energy capacities to enable massive and long duration storage. This study develops and applies a model to simulate the power system balance at very high penetration of renewables. Novelty of the study is the assessment of hydrogen as the primary storage means for balancing energy supply and demand on a large scale: the California power system is analyzed to estimate the needs for electrolyzer and fuel cell systems in 100% renewable scenarios driven by large additions of wind and solar capacities. Results show that the transition requires a massive increase in both generation and storage installations, e.g., a combination of 94 GW of solar PV, 40 GW of wind, and 77 GW of electrolysis systems. A mix of generation technologies appears to reduce the total required capacities with respect to wind-dominated or solar-dominated cases. Hydrogen storage capacity needs are also evaluated and possible alternatives are discussed, including a comparison with battery storage systems.     

Matching Western US electricity consumption with wind and solar resources

The variability of wind and solar is perceived as a major obstacle in employing otherwise abundant renewable energy resources. On the basis of the available geographically dispersed data for the Western USA, we analyze to what extent the geographic diversity of these resources can offset their variability. We determine the best match to loads in the western portion of the USA that can be achieved with wind power and photovoltaics (PV) with no transmission limitations. Without storage and with no curtailment, wind and PV can meet up to 50% of loads in Western USA. It is beneficial to build more wind than PV mostly because the wind contributes at night. When storage is available, the optimal mix has almost 75% as much nominal PV capacity as wind, with the PV energy contribution being 32% of the electricity produced from wind. With only 10 GW of storage (twice the pumped hydro storage capacity that already exists in the Western Electric Coordinating Council), up to 82% of the load can be matched with wind and PV, while in the same time curtailing just 10% of the renewable energy throughout the year. Copyright © 2012 John Wiley & Sons, Ltd.     

Study on electrical energy and prospective electricity generation from renewable sources in Australia

Nowadays renewable sources are being used as clean sources to generate electricity and to reduce the dependency on fossil fuels. The uses of renewable sources are being increased in electricity generation and contributed to reduce the greenhouse gas emission. The function of any electrical power system is to connect everyone sufficiently, clean electric power anywhere and anytime of the country. This can be achieved through a modern power system by integrating electrical energy from clean renewable sources into the nation's electric grid to enhance reliability, efficiency and security of the power system. The paper on the status of review the driving force of the generation of renewable energy and proposing electrical energy generation from renewable sources to be ensured at least 20% of total energy of Australia. This paper has been studied the existing electricity generation capacity of Australia from renewable and non-renewable sources. Optimal electricity generation from renewable sources has been examined. The environmental impact of electricity generation from renewable sources has been considered. Under this paper the yearly average wind data of past 20 years and above for some meteorological stations of Australia have been used. The prospective electricity generation from wind turbines and solar photovoltaic panels has been proposed in the paper that will increase electrical energy of the power grid of Australia. It was estimated the capital cost of prospective electricity generation farms from wind and solar PV sources.     

Solar forecasting methods for renewable energy integration

The higher penetration of renewable resources in the energy portfolios of several communities accentuates the need for accurate forecasting of variable resources (solar, wind, tidal) at several different temporal scales in order to achieve power grid balance. Solar generation technologies have experienced strong energy market growth in the past few years, with corresponding increase in local grid penetration rates. As is the case with wind, the solar resource at the ground level is highly variable mostly due to cloud cover variability, atmospheric aerosol levels, and indirectly and to a lesser extent, participating gases in the atmosphere. The inherent variability of solar generation at higher grid penetration levels poses problems associated with the cost of reserves, dispatchable and ancillary generation, and grid reliability in general. As a result, high accuracy forecast systems are required for multiple time horizons that are associated with regulation, dispatching, scheduling and unit commitment. Here we review the theory behind these forecasting methodologies, and a number of successful applications of solar forecasting methods for both the solar resource and the power output of solar plants at the utility scale level.     

Efficient storage capacity in power systems with thermal and renewable generation

Power systems with high shares of wind and solar power have to balance their intermittent nature. Pumped-hydro storage plants can provide the required flexibility, while thermal backup plants offer an alternative. This paper proposes a capacity planning model to describe the efficient technology portfolio. Drawing on a residual load duration curve, we derive the efficient storage capacity and discuss its dependence on cost parameters, as well as the effect of periods with renewable generation in excess of load. A case study for Germany applies the model and highlights the impact of CO₂ prices on storage efficiency.     

Future security of power supply in Germany—The role of stochastic power plant outages and intermittent generation

Many power plants in Germany and Europe are approaching the end of their technical lifetime. Moreover, the increasing wind and solar power generation reduces the operation times of thermal power plants, making future investments in new generation capacity uncertain under current market conditions. Consequently, the future development of security of power supply is unclear. In this paper, we assess the impact of stochastic fluctuations in power plant availability, renewable generation, and grid load on the future security of supply in Germany. We model variations in power plant availability by application of a combined Mean‐reversion Jump‐diffusion approach. On the basis of that and using Monte‐Carlo methods, we simulate 300 different time series of availability. These profiles are fed into the fundamental power system model REMix, applied to evaluate the appearance of supply shortfalls in hourly resolution. We assess 6 scenarios for the year 2025, differing in renewable generation and demand profiles, as well as grid infrastructure. Geographical focus of the analysis is Germany, but the electricity exchange with its European neighbours is modelled as well. Our results show that the choice of the power plant availability profile can change the loss of load expectation and loss of load hours by up to 50%. However, the influence of load and renewable generation profiles is found to be significantly higher. Assuming that no new conventional power plants are built and existing plants are decommissioned at the end of their empirical lifetime, we identify supply gaps of up to 2.7 GW in Germany.     

A methodology for analysis of impacts of grid integration of renewable energy

Present electricity grids are predominantly thermal (coal, gas) and hydro based. Conventional power planning involves hydro-thermal scheduling and merit order dispatch. In the future, modern renewables (hydro, solar and biomass) are likely to have a significant share in the power sector. This paper presents a method to analyse the impacts of renewables in the electricity grid. A load duration curve based approach has been developed. Renewable energy sources have been treated as negative loads to obtain a modified load duration curve from which capacity savings in terms of base and peak load generation can be computed. The methodology is illustrated for solar, wind and biomass power for Tamil Nadu (a state in India). The trade-offs and interaction between renewable sources are analysed. The impacts on capacity savings by varying the wind regime have also been shown. Scenarios for 2021–22 have been constructed to illustrate the methodology proposed. This technique can be useful for power planners for an analysis of renewables in future electricity grids.     

Seasonal optimal mix of wind and solar power in a future,highly renewable Europe

The renewable power generation aggregated across Europe exhibits strong seasonal behaviors. Wind power generation is much stronger in winter than in summer. The opposite is true for solar power generation. In a future Europe with a very high share of renewable power generation those two opposite behaviors are able to counterbalance each other to a certain extent to follow the seasonal load curve. The best point of counterbalancing represents the seasonal optimal mix between wind and solar power generation. It leads to a pronounced minimum in required stored energy. For a 100% renewable Europe the seasonal optimal mix becomes 55% wind and 45% solar power generation. For less than 100% renewable scenarios the fraction of wind power generation increases and that of solar power generation decreases.     

储能对可再生能源并网发电的支撑作用

可再生能源发电并网对于电力系统的节能减排具有关键作用,选择合理的储能容量,并分析储能对可再生能源并网发电的支撑作用具有重要意义。从节能减排和供电可靠性角度建立具有储能装置的单母线电力系统和剩余电力系统的随机规划模型,并通过蒙特卡罗模拟算法对国外某地区的风力发电和储能联合运行系统进行模拟分析。结果表明,适度规模的储能容量不仅能有效解决可再生能源发电的功率波动问题、减小系统停电损失概率,而且能够降低系统的环境成本,但其减少程度与储能的全过程效率有关。     

Energy storage for enhancing transmission capacities and trans-regional reserves of a UHV AC/DC power grid

探索应用储能为弱受端电网提供故障后大功率支撑以提升特高压交直流输电线稳态输送能力,同时兼作送端电网调峰的跨区备用源以增加新能源发电空间,以有效促进新能源跨区外送降低弃风弃光率。基于特高压交直流馈入受端电网的功率缺额与频率变化间的对应关系,提出在电网频率最低点满足要求的前提下,电网受电能力提升程度与储能容量配置间的数学模型;依据送端电网典型日各时段负荷特性建立可释放的新能源发电空间与所需储能备用调峰容量间的数学模型。结合考虑事故功率支撑与跨区调峰备用的容量需求特性及优先级别,探索两种功能联合应用下的容量需求方案和技术经济可行性。以交直流馈入的弱受端河南电网及新能源富集的送端新疆电网为例,验证了该新能源消外送纳能力提升方案的有效性。     

Analysis and characterization of wind-solar-constant torque spring hybridized model

Solar and wind are the most promising renewable energy resources. But their unpredictable and varying nature prevents them from being used as the sole resource for power generation. This paper presents a model of wind and solar thermal hybrid power plant with a spring storage system which is expected to play an efficient role in combating with the drawbacks related to renewable power generation. In the proposed scheme, wind energy is harnessed by a hybrid vertical axis wind turbine, solar energy is utilized by a Stirling engine, and the surplus energy is stored in a winding spring. The paper discusses the working methodologies and analyses the performance of such 2.6 kW hybrid power plant model. It has been observed that the plant is capable of consistently generating 50% of its rated capacity irrespective of limitations in solar and wind resources.