Large Penetration Of Renewable Energy Research Articles

Implementation of AI for forecasting of wind speed and solar irradiation using different Machine Learning techniques

High penetration of solar and wind power in the electricity system provides a number of challenges to the grid such as grid stability and security, system operation, and market economics. Ones of the considerable problems of solar and wind systems, they depend on the weather, as compared to the conventional generation. As we know, the balance in managing load and generated power in energy system is very import ant. If the power which is supplied from solar and wind perfectly predictable, the extra cost of operating power system with a large penetration of renewable energy will be reduced. Since, the accurate and reliable forecasting system for renewable sources represents an important topic as a major contribution for increasing non-programmable renewable on over the world. The target of this research is to describe the advanced hybrid evolutionary techniques of computational intelligence applied for PV as well as wind power forecast. The evaluation of this investigation is obtained by comparing different definitions of the forecasting error. Moreover, the meaning of NWP (numerical weather prediction) values based on meteorological information on solar and wind power forecasting at Indore has been highlighted in this research.

Techno-economic analysis of a liquid air energy storage system combined with calcium carbide production and waste heat recovery

Liquid air energy storage is one of the most promising solutions for the large penetration of renewable energy, but its potential in future industrial scenarios should be explored more. In this regard, a novel energy storage system combined with a calcium carbide production process, a steam Rankine cycle, an organic Rankine cycle, and a hot water unit is proposed in the current study. The thermodynamic and economic performances of the reference system are investigated, and the impacts of the critical parameters on the system performance are reported. The results show that the proposed system has round-trip energy and exergy efficiencies of 45.3 % and 49.0 %, which are 3.1 % and 11.5 % higher than those of stand-alone energy storage systems in the same category of technology. The economic analysis presents attractive and promising results, including a payback period of 1.35 years (which is of course based on special considerations related to the specific case study of the project in China), a total profit of 168.8 million USD, and a levelized cost of storage of 382–888 USD/MWh during the life period of the proposed system. Meanwhile, the calcium carbide production process can save electricity costs by 4.6 % owing to the system integration. The implementation of the proposed system will be of great practical significance for advancing the functionality of energy storage systems, specifically liquid air energy storage units, in industrial processes.

A GIS-based optimization model finalized to the localization of new power-to-gas plants: The case study of Sicily (Italy)

In 2020 the European Commission approved the GND (Green New Deal), a strategic plan aimed at the decarbonization of the EU by 2050. In this scenario, the diffusion of alternative renewable energy sources (RESs) play a key role, particularly electric energy production from wind and photovoltaic power plants. Regardless, the nonprogrammable nature of these power sources led recent studies to focus the interest on the power-to-gas solution (PtG), consisting of the electrolytic transformation of excesses of unused electric energy into hydrogen. The complexity of this technology requires the development of strategic optimization models aimed at finding the best locations for new PtG plants in specific territorial scenarios. This paper presents the development of a GIS-based optimization model that combines an operational research approach with territorial services based on geographic information system (GIS) data. The study is located in Sicily (Italy), considering the large renewable energy penetration in the larger Mediterranean island. The developed model allows us to find the best location for new PtG installations in the considered area by combining GIS automated processing with cost function resolution. The results of this work could be useful in the years to come in light of the rapid spread of hydrogen energy production in Italy.

Energy storage reduces costs and emissions even without large penetration of renewable energy: The case of China Southern Power Grid

Variable renewable energy (VRE) and energy storage systems (ESS) are essential pillars of any strategy to decarbonize power systems. However, there are still questions about the effects of their interaction in systems where coal’s electricity generation share is large. Some studies have shown that in the absence of significant VRE capacity ESS can increase CO2 emissions. This paper shows that contrary to this intuition, ESS reduces operational costs and emissions even without higher penetration of VRE in power systems with large shares of coal. It also shows that when combined with VRE, ESS delivers higher benefits. These findings are based on the examination of China Southern Power Grid under seven VRE and ESS penetration scenarios. Results show that at the 2018 penetration levels, ESS alone reduced operational costs by 2.8% and CO2 emissions by 1% and that by being paired with VRE, these reductions increased to 8.1% and 6.5%, respectively. The results clarify the synergy between ESS and VRE and explain the underlying mechanism. While VRE lowers coal units’ economic efficiency and environmental performance (measured in RMB/MWh and kg CO2/MWh), ESS offsets this effect by increasing large coal units’ power generation and improving their efficiency. ESS reduces coal consumption and CO2 emissions by substituting power generation from low-efficiency coal units with electricity from high-efficiency units and allowing them to operate at levels closer to full capacity and avoid start-ups.

Blockchain Technology Applied to Energy Demand Response Service Tracking and Data Sharing

Demand response (DR) services have the potential to enable large penetration of renewable energy by adjusting load consumption, thus providing balancing support to the grid. The success of such load flexibility provided by industry, communities, or prosumers and its integration in electricity markets, will depend on a redesign and adaptation of the current interactions between participants. New challenges are, however, bound to appear with the large scale contribution of smaller assets to flexibility, including, among others, the dispatch coordination, the validation of delivery of the DR provision, and the corresponding settlement of contracts, while assuring secured data access among interested parties. In this study we applied distributed ledger (DLT)/blockchain technology to securely track DR provision, focusing on the validation aspect, assuring data integrity, origin, fast registry, and sharing within a permissioned system, between all relevant parties (including transmission system operators (TSOs), aggregators, distribution system operators (DSOs), balance responsible parties (BRP), and prosumers). We propose a framework for DR registry and implemented it as a proof of concept on Hyperledger Fabric, using real assets in a laboratory environment, in order to study its feasibility and performance. The lab set up includes a 450 kW energy storage system, scheduled to provide DR services, upon a system operator request and the corresponding validations and verifications are done, followed by the publication on a blockchain. Results show the end to end execution time remained below 1 s, when below 32 requests/sec. The smart contract memory utilization did not surpass 1% for both active and passive nodes and the peer CPU utilization, remained below 5% in all cases simulated (3, 10, and 28 nodes). Smart Contract CPU utilization remained stable, below 1% in all cases. The performance of the implementation showed scalable results, which enables real world adoption of DLT in supporting the development of flexibility markets, with the advantages of blockchain technology.

Energy and environmental footprints of flywheels for utility-scale energy storage applications

Flywheel energy storage systems are feasible for short-duration applications, which are crucial for the reliability of an electrical grid with large renewable energy penetration. Flywheel energy storage system use is increasing, which has encouraged research in design improvement, performance optimization, and cost analysis. However, the system's environmental impacts for utility applications have not been widely studied. Evaluating the life cycle environmental performance of a flywheel energy storage system helps to identify the hotspots to make informed decisions in improving its sustainability; to make reasonable comparisons with other energy storage technologies, such as pumped hydro, compressed air, electro-chemical batteries, and thermal; and to formulate environmental policy in the energy sector. In this study, an engineering principles-based model was developed to size the components and to determine the net energy ratio and life cycle greenhouse gas emissions of two configurations of flywheel energy storage: steel rotor flywheel and composite rotor flywheel. The net energy ratio is a ratio of total energy output to the total non-renewable energy input over the life cycle of a system. Steel rotor and composite rotor flywheel energy storage systems were assessed for a capacity of 20 MW for short-duration utility applications. A consistent system boundary was considered for both systems with the life cycle stages of material production, operation, transportation, and end-of-life. Electricity from solar and wind was considered separately in the operation phase. The net energy ratios of the steel rotor and composite rotor flywheel energy storage systems are 2.5–3.5 and 2.7–3.8, respectively. The corresponding life cycle greenhouse gas emissions are 75.2–121.4 kg-CO2eq/MWh and 48.9–95.0 kg-CO2eq/MWh, depending on the electricity source. The net energy ratio and greenhouse gas emissions are highly influenced by the operation phase, which includes charging and standby modes. Uncertainty analysis shows that the life cycle greenhouse gas emissions are most sensitive to the solar, wind, and grid electricity mix emission factors. The results of this study will help to understand the carbon footprints of the various utility-scale energy storage systems.

Optimal planning of energy storage technologies considering thirteen demand scenarios from the perspective of electricity Grid: A Three-Stage framework

Planning rational and profitable energy storage technologies (ESTs) for satisfying different electricity grid demands is the key to achieve large renewable energy penetration in management. The complexity related to the planning of ESTs lies in diversities of different ESTs properties, uniqueness and varieties of electricity grid demands and uncertainties of the decision-making environment. However, existing research cannot solve above problems simultaneously. To fill such gap, this paper focuses on the optimal planning of various ESTs considering thirteen demand scenarios in electricity grid through establishing a three stage multi criteria decision making framework under the uncertain environment. Firstly, critical features of ESTs in technology and application conditions and constrains (TCC, ACC) are identified and deeply analyzed integrating with the characteristics of thirteen ESTs demand scenarios by cluster analysis and correlation text. Following that, a three-stage planning framework is established in TCC, ACC and comprehensive aspect through a Lagrange optimized comprehensive subjective and objective weight determination model based interval fuzzy number (IVFN) and interval intuitionistic fuzzy numbers (IVIFN) – PROMETHEE-II model. The results show that the optimal planning vary with the demand scenarios from electricity grid. This research has important guiding significance for overall planning and application management of renewable energy and ESTs.

Impact of Power-to-Gas on distribution systems with large renewable energy penetration

• A Power-to-Gas (PtG) model with electrolyser, H 2 buffer and methanation is set up. • The model is based on measurement carried out on an existing plant. • The PtG model is fully integrated into a distribution system power flow calculation. • Two network topologies and several penetrations of renewable sources are considered. • Annual simulations show positive impacts of PtG also with high share of renewables. The exploitation of the Power-to-Gas (PtG) technology can properly support the distribution system operation in case of large penetration of Renewable Energy Sources (RES). This paper addresses the impact of the PtG operation on the electrical distribution systems. A novel model of the PtG plant has been created to be representative of the entire process chain, as well as to be compatible with network calculations. The structure of the model with the corresponding parameters has been defined and validated on the basis of measurements gathered on a real plant. The PtG impact on the distribution systems has then been simulated on two network models representing a rural and a semi-urban environment, respectively. The testing has been carried out by defining a set of cases that contain critical situations for the distribution network, caused by RES plant placement. The objectives of the introduction of PtG are the reduction of the reverse power flow, as well as the reduction of the overcurrent and overvoltage issues in the distribution system. The results obtained from annual simulations lead to considerable reduction (from 78 to 100%) of the reverse power flow with respect to the base case, and to alleviating (or even solving) the overcurrent and overvoltage problems of the networks. These results indicate PtG as a possible solution for guaranteeing a smooth transition towards decarbonized energy systems. The capacity factors of the PtG plants largely vary depending on the network topology, the RES penetration, the number of the PtG plants and their sizes. From the test cases, the performance in a rural network (where the minimum capacity factor is about 50%) resulted better than in a semi-urban network (where the capacity factor values range between 21% and 60%).

Novel Conceptual Architecture for the Next-Generation Electricity Markets to Enhance a Large Penetration of Renewable Energy

A transition to a sustainable energy system is essential. In this context, smart grids represent the future of power systems for efficiently integrating renewable energy sources and active consumer participation. Recently, different studies were performed that defined the conceptual architecture of power systems and their agents. However, these conceptual architectures do not overcome all issues for the development of new electricity markets. Thus, a novel conceptual architecture is proposed. The transactions of energy, operation services, and economic flows among the agents proposed are carefully analysed. In this regard, the results allow setting their activities’ boundaries and state their relationships with electricity markets. The suitability of implementing local electricity markets is studied to enforce competition among distributed energy resources by unlocking all the potential that active consumers have. The proposed architecture is designed to offer flexibility and efficiency to the system thanks to a clearly defined way for the exploitation of flexible resources and distributed generation. This upgraded architecture hereby proposed establishes the characteristics of each agent in the forthcoming markets and studies to overcome the barriers to the large deployment of renewable energy sources.

Dependable Parallel Multi-Swarm C-DEEPSO with Migration for Voltage and Reactive Power Control

Abstract This paper proposes dependable parallel multi-swarm canonical differential evolutionary particle swarm optimization with migration (DPMS-CDEEPSOw/M) for voltage and reactive power control (Volt/Var Control: VVC). The proposed DPMS-CDEEPSOw/M is a general evolutionary computation technique for dependable and fast optimization applications. So far, applications of evolutionary computation methods such as Genetic Algorithm (GA), advanced PSOs, and Differential Evolution (DE) have been studied to VVC because VVC is a mixed integer nonlinear optimization programming (MINLP) problem. Considering recent progress of deregulated environment and large renewable energy penetration in power systems, Fast VVC is strongly needed. Utilization of parallel and distributed computing may solve the challenge. However, since power system is a social infrastructure, both fast computation and sustainable (dependable) control are eagerly awaited for VVC. A multi-swarm evolutionary computation technique is verified to improve quality of solution. Therefore, its application to VVC has a possibility to increase dependability. The simulation results indicate that the proposed DPMS-CDEEPSOw/M based method can speed up computation and improve dependability by comparison with the conventional dependable parallel C-DEEPSO based method.

Dependable Parallel Canonical Differential Evolutionary Particle Swarm Optimization for Voltage and Reactive Power Control

Abstract This paper proposes dependable parallel canonical differential evolutionary particle swarm optimization (C-DEEPSO) for voltage and reactive power control (Volt/Var Control: VVC). Since the problem can be formulated as a mixed integer nonlinear optimization problem (MINLP), various evolutionary computation techniques have been applied to the problem including PSO, differential evolution (DE), and DEEPSO. Considering large penetration of renewable energies and deregulated environments of power systems, VVC requires fast computation for larger-scale VVC problems. One of the solutions to speed-up the computation is to utilize parallel and distributed computing. Since power system is one of the infrastructures of social community, not only fast computation, but also sustainable control (dependability) is strongly required for VVC. The simulation results with with IEEE 14, 30, 57, and 118 bus systems indicate that parallel C-DEEPSO is superior to the conventional parallel DEEPSO from the dependability point of view.

Optimal location and rating of wind power plants in competitive electricity market

A large penetration of renewable energy in a sector plays a leading role in energy generation to counter the effect of global warming on the environment. The trend in liberalized power system scenarios presents the potential of the wind power generator (WPG) to become one of the major contributors in the alternative energy production sector. Environmental conditions significantly influence the performance of these WPGs, and thus, the optimal assessment of the potential location and rating of the WPG is crucial. This paper presents a generalized model for determining the optimal location and rating of the WPG in a competitive electricity market. The multi-objective optimization problem has been formulated with an objective of maximizing the social welfare and profitability of a wind generation company by minimizing the distribution losses by optimal location and rating of WPGs in the system. To investigate the effectiveness of the proposed approach, a 39-bus New England transmission system has been modified by introducing generator and demand-side bidding. To test the validity of the proposed approach over the interconnected system, a modified 30-node radial distribution system has been considered, which is assumed to be connected with a modified 39-bus New England transmission system. The results provide a single solution for optimal location and rating of the WPG as well as a preference order based on the combination of different attributes.

Frequency control by wide-area dispatching of short-term supply-demand imbalance in multi-area power system with a large penetration of renewable energy

AbstractRecently, a lot of distributed generations such as WT (Wind Power Generation) have been installed into power systems. However, the output of these generations is so unstable that the frequency fluctuation will increase. This paper aims at solving the short-term supply-demand imbalance in an area where a large amount of renewable energy has been introduced and proposes a new method of dispatching the fluctuations of renewable energy based power to another area through a tie line. For the frequency analysis, we use the two-area interconnected power system model with a large amount of WT. It was made clear that without the proposed control, the unexpected power flow deviation through the tie line is very large, however, the proposed control method can suppress such deviation effectively. It was also shown in this paper that the proposed method is effective in the frequency control with a large integration of renewable energy into grid.

Benefits of forecasting and energy storage in isolated grids with large wind penetration – The case of Sao Vicente

For electric grids that rely primarily on liquid fuel based power generation for energy provision, e.g. one or more diesel gensets, measures to allow a larger fraction of intermittent sources can pay-off since the displaced is high cost diesel powered generation. This paper presents a case study of Sao Vicente, located in Cape Verde where a particularly high fraction of wind capacity of 5.950 MW (75% of the average demand) is installed, with diesel gensets forming the dispatchable source of power. This high penetration of intermittent power is managed through conservative forecasting and curtailments. Two potential approaches to reduce curtailments are examined in this paper: 1) an improved wind speed forecasting using a rolling horizon ARIMA model; and 2) energy storage. This case study shows that combining renewable energy forecasting and energy storage is a promising solution which enhances diesel fuel savings as well as enables the isolated grid to further increase the annual renewable energy penetration from the current 30.4% up to 38% while reducing grid unreliability. In general, since renewable energy forecasting ensures more accurate scheduling and energy storage absorbs scheduling error, this solution is applicable to any small size isolated power grid with large renewable energy penetration.

Verification of Dependability on Parallel Differential Evolution Based Voltage and Reactive Power Control

Abstract: This paper evaluates dependability on parallel differential evolution (DE) based voltage and reactive power control (Volt/Var Control: VVC) Considering large penetration of renewable energies and deregulated environment of power systems VVC requires fast computation even for larger-scale problems One solutions to increase the computation speed is to use parallel and distributed computing. Since power system is one of the infrastructures of social community, not only fast computation, but also sustainable control (dependability) is strongly required for VVC. The simulation results with IEEE 14, 30, 57, and 118 bus systems indicate that parallel DE is superior to parallel Particle Swarm Optimization (PSO) especially for dependability on VVC.

Dynamic frequency response from electric vehicles in the Great Britain power system

With the large penetration of renewable energy, fulfilling the balance between electricity demand and supply is a challenge to the modern power system. According to the UK government, the wind power penetration will reach 30% by the year 2020. The role of electric vehicles (EVs) contributing to frequency response was investigated. A dynamic frequency control strategy which considers the comfort level of vehicle owners was developed for EVs to regulate their power consumption according to the deviation of system frequency. A simulation model of a population of EVs equipped with such control was implemented in Matlab/Simulink platform. In this paper, a simplified Great Britain power system model is used to study the contribution of EVs to dynamic frequency control. The case study showed that using EVs as a demand response resource can greatly reduce the frequency deviations. And the rapid response from EVs can help reduce the operation cost of conventional generators.

Regulating reserve with large penetration of renewable energy using midterm dynamic simulation

A novel renewable energy intermittency model and a new midterm dynamic simulation tool in power systems are developed for examining dynamic behavior along the load curve for different combinations of the system operation reserves and renewable portfolio standard (RPS) rates. The system’s import limits are considered. It is concluded that ignoring intermittency and governor effects is an inadequate method to assess intermittency impact. The intermittency midterm dynamic impact must be studied. For the studied system, the instability is expected to be about 25 % RPS with current reserves. Besides, the most vulnerable peak hour to instability is the afternoon peak hour when solar begins to drop off. This article stimulates further dynamic intermittency studies on the issues caused by renewable intermittency. The studies on the issues caused by renewable intermittency have not been revealed because of inadequate/incomprehensive study methodologies so that effective, mitigative solutions can be developed to guarantee the reliability of power grid when incorporating higher RPS if high operation reserves are impractical.

A Wind-Solar-Energy Storage System Leading to High Renewable Penetration in the Island System of Kinmen

Kinmen Island lacks fossil-fuel energy, However, it has rich potential for solar and wind energy resources because of its excellent climate and geographical location. Therefore, a large scale utilization of the renewable energy sources is favoured. In June 2004, the Kinmen County government published the Strategic Plan for the Sustainable Development of Kinmen, which focuses on maintaining the ecology of the islands. In the near future, a high penetration of renewable power can be predicted to be installed in this island. However, a large renewable energy penetration into a diesel power system would face technical and economic problems. Therefore, this study intends to discuss the system operation of the Kinmen system and investigates the original unit commitment scheduling. Based on the simulation results, a new unit commitment scheduling will be proposed in this work.

Lead–acid batteries in stationary applications: competitors and new markets for large penetration of renewable energies

With increasing deregulation of the European electricity market, the quality of supply is becoming an issue of growing importance. Grid-connected electricity storage systems (ESSs) can enhance the quality of supply by: (i) shortening black-out periods; (ii) shifting excess energy for use during periods of high demand; (iii) sustaining the grid for better power quality. These problems are being addressed by using technologies such as power electronics and ICT. But storage systems offer a cheap and efficient solution to such concerns. ESSs can also power high-value, ancillary services. This paper analyses the new potential markets for storage systems in the context of distributed energy resources with a high penetration of renewable energies in the electricity networks. While lead–acid batteries are the most used technology in all types of stationary applications, many different storage technologies are claimed to fulfil the technical requirements of the above applications, in particular the emerging ones. Therefore, a comparison is made of lead–acid technology and its competitors in terms of technical and economic considerations.