Hasil untuk "Renewable energy sources"

V. Khare, S. Nema, P. Baredar

Catarina R. Matos, J. Carneiro, P. P. Silva

Abstract The increasing integration of renewable energies in the electricity grid is expected to contribute considerably towards the European Union goals of energy and GHG emissions reduction. However, it also brings new challenges for the grid. Large-scale energy storage can provide means for a better integration of renewable energy sources, balancing supply and demand, increasing energy security, enhancing a better management of the grid and also allowing convergence towards a low carbon economy. One way to ensure large-scale energy storage is to use the storage capacity in underground reservoirs, since geological formations have the potential to store large volumes of fluids with minimal impact to environment and society. There are several technologies which can be viable options for underground energy storage, as well as several types of underground reservoirs can be considered. The underground energy storage technologies for renewable energy integration addressed in this article are: Compressed Air Energy Storage (CAES); Underground Pumped Hydro Storage (UPHS); Underground Thermal Energy Storage (UTES); Underground Gas Storage (UGS) and Underground Hydrogen Storage (UHS), both connected to Power-to-gas (P2G) systems. For these different types of underground energy storage technologies there are several suitable geological reservoirs, namely: depleted hydrocarbon reservoirs, porous aquifers, salt formations, engineered rock caverns in host rocks and abandoned mines. Specific site screening criteria are applicable to each of these reservoir types and technologies, determining the viability of the reservoir itself, and of the technology for that site. This paper presents a review of the criteria applied to identify suitable technology-reservoir couples.

Aamer Ali, R. A. Tufa, F. Macedonio et al.

S. Loh

Yashwant Sawle, S. Gupta, Aashish Kumar Bohre

H. Bevrani, A. Ghosh, G. Ledwich

Ichiro Toyoshima, Pierre-Louis Poirion, Tomohide Yamazaki et al.

Power company operators make power generation plans one day in advance, in what is known as the Unit Commitment (UC) problem. UC is exposed to uncertainties, such as unknown electricity load and disturbances caused by renewable energy sources, especially PVs. In previous research, we proposed the Renewable Energy Robust Optimization Problem (RE-RP), which solves these uncertainties by considering suppression. In this paper, we propose a new model called RE-RP with fairness (RE-RPfair), which aims to achieve fair allocation among PVs allocation. This model is an expansion of the original RE-RP, and we prove its effectiveness through simulation. To measure the degree of fairness, we use the Gini Index, which is well-known in social science.

O. Edenhofer

Siddharth Suman

Vishwamitra Oreea, Sayed Z. Sayed Hassena, Peter J. Flemingb

Generation expansion planning consists of finding the optimal long-term plan for the construction of new generation capacity subject to various economic and technical constraints. It usually involves solving a large-scale, non-linear discrete and dynamic optimisation problem in a highly constrained and uncertain environment. Traditional approaches to capacity planning have focused on achieving a least-cost plan. During the last two decades however, new paradigms for expansion planning have emerged that are driven by environmental and political factors. This has resulted in the formulation of multi-criteria approaches that enable power system planners to simultaneously consider multiple and conflicting objectives in the decision-making process. More recently, the increasing integration of intermittent renewable energy sources in the grid to sustain power system decarbonisation and energy security has introduced new challenges. Such a transition spawns new dynamics pertaining to the variability and uncertainty of these generation resources in determining the best mix. In addition to ensuring adequacy of generation capacity, it is essential to consider the operational characteristics of the generation sources in the planning process. In this paper, we first review the evolution of generation expansion planning techniques in the face of more stringent environmental policies and growing uncertainty. More importantly, we highlight the emerging challenges presented by the intermittent nature of some renewable energy sources. In particular, we discuss the power supply adequacy and operational flexibility issues introduced by variable renewable sources as well as the attempts made to address them. Finally, we identify important future research directions.

André LeClair

We explore the idea that quantum vacuum energy $ρ_{\rm vac} $ is at the origin of Gravity. We formulate a gravitational version of the electromagnetic Casimir effect, and provide an argument for how gravity can arise from $ρ_{\rm vac} $ by showing how Einstein's field equations emerge in the form of Friedmann's equations. This leads to the idea that Newton's constant $G_N$ is environmental, namely it depends on the total mass-energy of the Universe $M_\infty $ and its size $R_\infty $, with $G_N = c^2 R_\infty /2 M_\infty$. This leads to a new interpretation of the Gibbons-Hawking entropy of de Sitter space, and also the Bekenstein-Hawking entropy for black holes, wherein the quantum information bits are quantized massless particles at the horizon with wavelength $λ= 2 πR_\infty$. We assume a recently proposed formula for $ρ_{\rm vac} \sim m_z^4/\mathfrak{g}$, where $m_z$ is the mass of the lightest particle, and $\mathfrak{g}$ is a marginally irrelevant coupling. This leads to an effective, induced RG flow for Newton's constant $G_N$ as a function of an energy scale, which indicates that $G_N$ decreases at higher energies until it reaches a Landau pole at a minimal value of the cosmological scale factor $a(t) > a_{\rm min}$, thus avoiding the usual geometric singularity at $a=0$. The solution to the scale factor satisfies an interesting symmetry between the far past and far future due to $a(t) = a(-t + 2 t_{\rm min})$, where $a(t_{\rm min}) = a_{\rm min}$. We propose that this energy scale dependent $G_N$ can explain the Hubble tension and we thereby constrain the coupling constant $\mathfrak{g}$ and its renormalization group parameters. For the $Λ{\rm CDM}$ model we estimate $a_{\rm min} \approx e^{-1/\hat{b} }$ where $\hat{b} \approx 0.02$ based on the Hubble tension data.

Xuyuan Kang, Xiao Wang, Jingjing An et al.

Thermal energy storage (TES) is an effective method for load shifting and demand response in buildings. Optimal TES control and management are essential to improve the performance of the cooling system. Most existing TES systems operate on a fixed schedule, which cannot take full advantage of its load shifting capability, and requires extensive investigation and optimization. This study proposed a novel integrated load prediction and optimized control approach for ice-based TES in commercial buildings. A cooling load prediction model was developed and a mid-day modification mechanism was introduced into the prediction model to improve the accuracy. Based on the predictions, a rule-based control strategy was proposed according to the time-of-use tariff; the mid-day control adjustment mechanism was introduced in accordance with the mid-day prediction modifications. The proposed approach was applied in the ice-based TES system of a commercial complex in Beijing, and achieved a mean absolute error (MAE) of 389 kW and coefficient of variance of MAE of 12.5%. The integrated prediction-based control strategy achieved an energy cost saving rate of 9.9%. The proposed model was deployed in the realistic building automation system of the case building and significantly improved the efficiency and automation of the cooling system.

Murat Çolak, I. Kaya

Fırat Emir, F. Bekun

This study empirically examines the relationship between energy intensity, carbon emissions, renewable energy consumption, and economic growth for the case of Romania given the conflicting evidences in the literature between 1990 and 2014 on a quarterly basis. To this end, our study employs an autoregressive distributive lag (ARDL) model for cointegration, while direction of causality was achieved via the Toda–Yamamoto model. Empirical findings reveal cointegration among the variables under consideration. The causality results show feedback causality between energy intensity and economic growth while uni-directional causality is seen running from renewable energy consumption to economic growth. Thus, this study affirms the energy-led growth hypothesis. Therefore, our study corroborates with the current success story of Romania attaining her energy targets within two decades. However, there is need to sustain this milestone by further diversification of her energy portfolio into other cleaner energy sources.

Alpaslan Demirci, Said Mirza Tercan, Eihab E. E. Ahmed et al.

Prosumer communities are integrating renewable energy sources to reduce energy costs and carbon emissions for sustainable and clean energy awareness. However, increasing solar photovoltaic penetration in low-voltage distribution networks leads to serious power quality challenges, such as overvoltage for grid operators and prosumers. Integrating electric vehicles (EVs) as deferable loads can reduce prosumer costs and maximize environmental benefits as EV charging is managed. Therefore, this paper proposes a novel EV charging management that maximizes prosumer communities’ power quality and benefits PV-rich prosumers by applying a dynamic active power curtailment framework. The methodology calculates each prosumer’s maximum power injection into the grid based on their voltage sensitivities. The performance of the developed charging management is examined on the European 906 bus low-voltage distribution networks under unmanaged, managed, and vehicle-to-grid (V2G)-empowered scenarios. The prosumers’ individual and aggregated economic cost-benefit results are analyzed considering increasing EV penetration. The results show that the proposed method considering fair active power curtailment could increase self-consumption and renewable fraction for prosumers. It is observed that increasing EV penetration could reduce the curtailed energy by 14.6%. The V2G-empowered method also increased up to 20% more renewable energy for charging EVs, improved self-consumption and renewable fraction up to 11% and 19.4%. Moreover, the V2G option reduced total costs by up to 37.93%. This work can potentially promote renewable energy sources by modifying consumers’ charging behaviors to be more sustainable and environmentally friendly.

Thore Wietzke, Jan Gall, Knut Graichen

This paper presents a new approach to predict the occupancy for building energy systems (BES). A Gaussian Process (GP) is used to model the occupancy and is represented as a state space model that is equivalent to the full GP if Kalman filtering and smoothing is used. The combination of GPs and mechanistic models is called Latent Force Model (LFM). An LFM-based model predictive control (MPC) concept for BES is presented that benefits from the extrapolation capability of mechanistic models and the learning ability of GPs to predict the occupancy within the building. Simulations with EnergyPlus and a comparison with real-world data from the Bosch Research Campus in Renningen show that a reduced energy demand and thermal discomfort can be obtained with the LFM-based MPC scheme by accounting for the predicted stochastic occupancy.

Charalampos Symeonidis, Nikos Nikolaidis

Electricity generated from renewable energy sources has been established as an efficient remedy for both energy shortages and the environmental pollution stemming from conventional energy production methods. Solar and wind power are two of the most dominant renewable energy sources. The accurate forecasting of the energy generation of those sources facilitates their integration into electric grids, by minimizing the negative impact of uncertainty regarding their management and operation. This paper proposes a novel methodology for deterministic wind and solar energy generation forecasting for multiple generation sites, utilizing multi-location weather forecasts. The method employs a U-shaped Temporal Convolutional Auto-Encoder (UTCAE) architecture for temporal processing of weather-related and energy-related time-series across each site. The Multi-sized Kernels convolutional Spatio-Temporal Attention (MKST-Attention), inspired by the multi-head scaled-dot product attention mechanism, is also proposed aiming to efficiently transfer temporal patterns from weather data to energy data, without a priori knowledge of the locations of the power stations and the locations of provided weather data. The conducted experimental evaluation on a day-ahead solar and wind energy forecasting scenario on five datasets demonstrated that the proposed method achieves top results, outperforming all competitive time-series forecasting state-of-the-art methods.

J. Blázquez, Rolando Fuentes-Bracamontes, C. Bollino et al.

Abstract One major avenue for policymakers to meet climate targets is by decarbonizing the power sector, one component of which is raising the share of renewable energy sources (renewables) in electricity generation. However, promoting renewables --in liberalized power markets-- creates a paradox in that successful penetration of renewables could fall victim to its own success. With the current market architecture, future deployment of renewable energy will necessarily be more costly and less scalable. Moreover, transition towards a full 100% renewable electricity sector is unattainable. Paradoxically, in order for renewable technologies to continue growing their market share, they need to co-exist with fossil fuel technologies. Ignoring these findings can slow adoption and increase the costs of deploying new renewable technologies. This paper spots the incompatibility between electricity liberalization and renewable policy, regardless of the country, location or renewable technologies. The Paradox holds as long as market clear prices with short term marginal costs, and renewable technology's marginal cost is close to zero and not dispatchable.

Meer A.M. Khan, S. Rehman, F. Al-Sulaiman

The water needs of the inhabitants of Saudi Arabia are met by desalination powered by electricity generated from fossil fuel. Excessive burning of fossil fuels results in faster depletion and causes an adverse impact on the local environment. Reverse osmosis (RO) desalination based on a hybrid renewable energy system (HRES) has emerged as a cleaner alternative. The primary objective of this review is to assess the current status of utilizing renewable energy for small and large-scale water desalination plants. An overview of the expansion of domestic and global desalination plant capacities is presented with the evaluation of Saudi Arabia’s renewable energy potential. Numerous studies on coupling various combinations of renewable energy sources to power desalination processes are reviewed. A comprehensive analysis of the trends and technical developments of PV-RO, Wind-RO, and hybrid PV-Wind-RO for a wide range of capacities over the past three decades is provided. Designing and modeling HRES-RO desalination systems using different combinations of renewable energy sources are thoroughly analyzed and the technical aspects of their performance are presented. The application of a range of optimization and sizing software tools available for conducting pre-feasibility analysis and the comparison of the available software tools for HRES-RO desalination are also presented. The study also demonstrated that the replacement of fossil fuel with renewable energy for desalination will significantly decrease greenhouse gas emissions. The review also highlights the effect of solar and wind profiles on the economics of desalination powered by renewables. The economic analysis indicates a significant decrease in the cost of water production by hybrid PV-wind-RO systems, implying good prospects for the technology in the near future. Finally, the study provides a flowchart depicting the steps involved in installing a hybrid PV-wind-RO system in KSA.

A. Angelis-Dimakis, M. Biberacher, J. Domínguez et al.