Participation Of Renewable Energy Sources Research Articles

Performance analysis and scheduling study of hybrid CAES system operating jointly with wind and solar

Hybrid compressed air energy storage (H-CAES) system can effectively reduce the heat loss in the compression process, which is one of the important methods to solve the problem of renewable energy volatility. Based on the H-CAES system that combines adiabatic compression and isothermal compression, this paper proposes a liquid piston compressor arrangement to adapt to the input power fluctuation and proposes a power allocation calculation method to solve the adiabatic compression and isothermal compression in the H-CAES system, with an emphasis on analyzing the impact of the participation of renewable energy sources on the system performance. In addition, the H-CAES system is placed under wind-solar-storage conditions, and scheduling strategies judged by time-sharing electricity price are proposed for different scenarios to explore the actual operating effects of the H-CAES system. The results show that the arrangement of liquid piston compressors from large tanks with fewer groups to small tanks with more groups can better adapt to the power change while maintaining a better isothermal compression effect. On the basis of using the power allocation calculation method proposed in this paper, it is found that higher compressor outlet pressure and lower storage pressure can improve the system efficiency and economic benefits. The system is able to achieve 59.71% efficiency and 0.2261 annual return on investment at the compressor outlet pressure of 4 MPa. Finally, it is demonstrated that the combined operation of H-CAES and wind energy can serve to increase the operating income of the power plant, and a maximum of 8909.236 yuan in daily electricity generation revenue can be achieved.

Optimization Scheduling of Virtual Power Plants Considering Source-Load Coordinated Operation and Wind–Solar Uncertainty

A combined approach of Latin hypercube sampling and K-means clustering is proposed in this study to address the uncertainty issue in wind and solar power output. Furthermore, the loads are categorized into three levels: primary load, secondary load, and tertiary load, each with distinct characteristics in terms of demand. Additionally, a load demand response characteristic model is developed by incorporating the dissatisfaction coefficient of electric and thermal loads, which is then integrated into the system’s operational costs. Moreover, an electricity–hydrogen–thermal power system is introduced, and a source-load coordination response mechanism is proposed based on the different levels of demand response characteristics. This mechanism enhances the interaction capability between the power sources and loads, thereby further improving the economic performance of the virtual power plant. Furthermore, the operation economy of the virtual power plant is enhanced by considering the participation of renewable energy sources in carbon capture devices and employing a tiered carbon-trading mechanism. Finally, the CPLEX algorithm is employed to solve the optimization model of the virtual power plant, thereby validating the effectiveness of the proposed models and algorithms.

A reinforcement-probability Bayesian approach for strategic bidding and market clearing for renewable energy sources with uncertainty

With the participation of renewable energy sources (RESs) in the electricity market, the inherent uncertainty brings new challenges for strategic bidding and market clearing in the electricity market. In this paper, the market structure is formulated as a non-cooperative game among power suppliers, consumers, and the market operator. A reinforcement-probability Bayesian approach is proposed to obtain the optimal bidding strategy of RESs and achieve maximal social welfare at the market clearing, considering uncertain cost types of RESs and incomplete market information. First, a reinforcement-probability model is presented to obtain the optimal agent-type-strategy combination considering the uncertainty of cost type selection. A agent-type-probability algorithm is proposed for the model to update the mean of probability density function of cost types according to the expected profit. Second, an incremental-cost-based distributed algorithm is proposed to solve the market clearing problem, which accelerates the convergence rate without violating the system constraints via feedback from the scheduled power. Finally, a Bayesian probability model is proposed for RESs to learn the hidden information of the market and transform the incomplete information electricity market into a complete one. A Bayesian Nash equilibrium is reached in the model. To coordinate the information among market participants, the output of the Bayesian probability model is calculated by the Hysteretic Q-learning algorithm and used as the reward to update the agent-type-probability in the reinforcement-probability model. An illustrative example is presented to demonstrate the effectiveness of the proposed approach, which shows that the proposed approach has a better convergence performance and has a 2–6 times faster learning speed compared with the policy gradient and deep Q-network.

The Asymmetric Impact of Energy’s Paradigm Transition on Environmental Degradation: a Macroeconomic Evidence from Latin American and the Caribbean Countries

The main objective of this study is to identify the impact of the energy paradigm transition on the environmental degradation of eighteen Latin American and Caribbean (LAC) countries. To this end, a panel non-linear autoregressive distributed lag (PNARDL) in the form of an unrestricted error correction model (UECM) and a period from 1990 to 2019 were used. The empirical results indicated that the variable economic growth in both the short- and long-run have an increase of 0.6994 and 0.3192, respectively, and the variable public capital stock in the short-run has an increase of 0.0176 in CO2 emissions. However, the positive and negative asymmetry of the variable ratio of renewable energy in the short-and long-run has a decrease of −0.1320 (on positive variations) and −0.1131 (on negative variations) in the short run and −0.0364 (on positive variations) and −0.0783 (on negative variations) in the long run on CO2 emissions. The capacity of the ratio of renewable/fossil energy consumption to reduce environmental degradation is compatible with the renewable energy technological efficiency that produces more clean energy and fewer emissions. That was also in line with the increasing participation of renewable energy sources in the energy matrix in the LAC countries.

Microgrid Frequency Regulation Based on a Fractional Order Cascade Controller

Nowadays, the participation of renewable energy sources (RESs) and the integration of these sources with traditional power plants in microgrids (MGs) for providing demand-side power has rapidly grown. Although the presence of RESs in MGs reduces environmental problems, their high participation significantly affects the system’s whole inertia and dynamic stability. This paper focuses on an islanded MG frequency regulation under the high participation of RESs. In this regard, a novel fractional order cascade controller (FOCC) is proposed as the secondary frequency controller. In the proposed FOCC controller structure, a fractional order proportional-integral controller is cascaded with a fractional order tilt-derivative controller. The proposed FOCC controller has a greater degree of freedom and adaptability than integer order controllers and improves the control system’s efficiency. The adjustable coefficients of the proposed controller are tuned via the kidney-inspired algorithm. An energy storage system equipped with virtual inertia is also employed to improve the system inertia. The proposed FOCC controller efficiency is compared with proportional-integral-derivative (PID), tilt-integral-derivative (TID), and fractional order proportional-integral-derivative (FOPID) controllers under different disturbances and operating conditions. The results demonstrate that the presented controller provides better frequency responses compared to the other controllers. Moreover, the sensitivity analysis is performed to show the proposed controller robustness versus the parameters’ changes in the system.

A Mathematical Programming Approach for the Optimal Operation of Storage Systems, Photovoltaic and Wind Power Generation

The ever-growing participation of Renewable Energy Sources (RES) in modern distribution networks is replacing an important portion of Conventional Generation (CG), which brings along new challenges in the planning and operation of distribution grids. As RES such as Photovoltaic Energy (PV) and Wind Power Generation (WPG) increase in distribution networks, studies regarding their integration and coordination become more important. In this context, the purpose of this paper is to propose a Multi-period Optimal Power Flow (MOPF) model for the optimal coordination of Battery Energy Storage Systems (BESSs) with PV, WPG, and CG in modern distribution networks. The model formulation was developed in A Modeling Language for Mathematical Programming (AMPL) and solved through the Knitro solver within a time horizon of 24 h. A distinctive feature and one of the main contributions of the proposed approach is the fact that BESSs can provide both active and reactive power. The proposed optimization model reduces power losses and improves voltage profiles. To show the applicability and effectiveness of the proposed model, several tests were carried out on the 33-bus distribution test system and a real distribution system of 141 buses located in the metropolitan area of Caracas. Power loss reductions of up to 58.4% and 77% for the test systems of 33 and 141 buses were obtained, respectively, when BESSs provided both active and reactive power. The results allow us to conclude that the proposed model for optimal coordination of BESSs with RES is suitable for real-life applications, resulting in important reductions of power losses and flattening of voltage profiles.

Participation of Renewable Energy Sources in the Frequency Regulation Issues of a Five-Area Hybrid Power System Utilizing a Sine Cosine-Adopted African Vulture Optimization Algorithm

In this article, a novel methodology is proposed by utilizing a technique which, in light of the change in the African vulture optimization known as Sine Cosine, adopted an African vulture optimization algorithm (SCaAVOA)-based tilt integral derivative (TID) regulator for the load frequency control (LFC) of a five-area power system with multi-type generations. At first, the execution of the Sine Cosine-adopted calculation is tried by contrasting it with the standard AVOA calculation while considering different standard benchmark functions. To demonstrate the superiority of the proposed SCaAVOA algorithm, the results are contrasted using different standard approaches. In the next stage, the proposed method is used in a five-area thermal power system and is likewise applied to a five-area, ten-unit system comprising different conventional sources as well as some renewable energy sources. The performance analysis of the planned regulator is completed for various system boundaries and loading conditions. It is seen that the said regulator is more viable in comparison to the other standard controllers.

Controlling the Frequency Response in AC/DC Microgrid using an Energy Storage Device

This paper deals with the issue of frequency regulation in a small insulated low inertia grid with a large participation of renewable energy sources (RESs). A strong decentralized control strategy is used, allowing various RESs such as batteries, supercapacitors, and fuel cells to provide additional frequency recovery service. A small grid with a synchronous machine, photovoltaic cells, and fuel cells was developed as generation units to test the effectiveness of the suggested technique. Furthermore, the battery and supercapacitors were added to the system to give additional service to suppliers. Simulating the system response to numerous uncertainty is used to evaluate the controller's performance.  the controller's efficiency is displayed in Graphical form. This paper will show how a decentralized method that allows all units to provide active power supports not only adjusts frequency nadir points but also minimizes the amount of active power required in the process. As a result, the electrical pressure on each element that supports the network against the heavy usage of RESs is reduced.

Assessment of the impact of the industrial enterprise on the environment by determining the integrated (generalized) energy efficiency performance indicator

The article summarizes the efficiency indicators. The authors have developed comprehensive efficiency indicators of the enterprise for a complete assessment of the efficiency of energy use. The comprehensive efficiency index of the enterprise is divided into three stages: generation of energy, energy transmission and energy consumption. In this case, the efficiency of using primary energy resources in the enterprise was accepted as a priority criterion. The integrated (generalized) energy efficiency indicator of the industrial enterprise was developed taking into account the participation of renewable energy sources in the energy consumption of the enterprise and the impact of energy consumption on the environment. The most effective way to green production and reduce carbon emissions per unit of product is through energy efficiency testing. Capturing and reducing carbon emissions per product can be achieved through energy efficiency research. It has good energy efficiency in terms of production quality and ease of production methods. The article describes in detail not only the evaluation methodology for evaluating the impact of production on the environment, but also the energy intensive in the production of unit of product and the coefficient of efficiency work in energy production and transmission in generalized indicators.

Dynamic Virtual Power Plant: A New Concept for Grid Integration of Renewable Energy Sources

The concept of Virtual Power Plant (VPP) has arisen over a decade ago from the relatively low competitiveness of the back then emerging non-dispatchable RES. A set of smaller generators imitates the behavior of large synchronous generators. So far, static aspects such as generation or slow dynamics have been of interest, as it is the case for the zonal secondary frequency control scheme in Spain, which can be viewed as a VPP. However, considering dynamic aspects is of high importance, especially to further increase the current penetration level of Renewable Energy Sources (RES). Indeed, one should deal with the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">full</i> participation of RES in grid ancillary services. This means not only to get some positive impact on grid voltage and frequency dynamics but to bring concepts which allow integrating RES to existing secondary regulation schemes on the same level as classic synchronous generators. For that, we propose here a new concept called Dynamic VPP (DVPP) which fully integrates the dynamic aspects at all levels: locally (for each RES generator), globally (for grid ancillary services and interaction with other close-by elements of the grid) and economically (for internal optimal dispatch and participation in electricity markets). A DVPP is a set of dispatchable and non-dispatchable RES along with a set of common control and operation procedures. The latter procedures include the choice of dispatchable and non-dispatchable RES constituting the DVPP, the control of DVPP generators for local objectives and participation of the DVPP as a single unit in ancillary services (especially in case of loss of natural resources - e.g., wind, sun - on a part of the DVPP), the limitation of the risk of adversely interaction with close-by elements and the feasibility in both current power systems scenarios and future ones with large share of RES. This new DVPP framework and approaches developed for its implementation allows ensuring optimal operation of a mixed portfolio of dispatchable and non-dispatchable RES generators for planning, participation to the markets and real-time control. For the control, all time-scale dynamics are considered to improve RES management (internal re-dispatch inside the DVPP to take advantage of dispatchable/non-dispatchable nature of each RES and to optimally manage the lack of natural resources in some regions of the DVPP) and their participation to grid ancillary services. Concrete structures of DVPP as well as ways to address the other control and economical aspects will be shown. This new DVPP concept is now under development in the H2020 POSYTYF project (https://posytyf-h2020.eu/).

Enhancing the transient performance and dynamic stability of microgrid using PI inertia injection controller

In power sector, the participation of Renewable Energy Sources (RES) is important from an energy, economic, and environmental point of view. But from the grid’s perspective, dynamic performance is crucial for deciding the participation level of RES. Currently, the Derivative Control Technique (DCT) based virtual inertia systems are quite popular. However, the use of DCT improves the transient performance but degrades the steady state parameters (settling time and steady-state frequency error). To improve the overall performance, a novel PI-based Inertia Injection controller has been proposed in this paper. This controller advances the Photovoltaic (PV) based virtual inertia model and improves the transient stability without compromising the steady state one. Further, the effectiveness of the proposed controller has been proved by performing the time-domain simulations under different practical scenarios.

Optimal Multi-Operation Energy Management in Smart Microgrids in the Presence of RESs Based on Multi-Objective Improved DE Algorithm: Cost-Emission Based Optimization

Today, in various leading power utilities in developing countries, achieving optimal operational energy management and planning, taking into account the costs reduction of generation, transmission and distribution of electricity, and also reducing the emission of an environmental pollutant becomes more and more important. Optimal use of renewable energy sources (RESs) is an effective way to achieve these goals. In this regard, in this research article, an improved multi-objective differential evolutionary (IMODE) optimization algorithm is suggested and performed to dispatch electricity generations in a smart microgrid (MG) system, taking into account economy and emission as competitive issues. In this paper, a nonlinear equation of multi-objective optimization issue with various equality and inequality limitations is formulated in order to lower the total operational costs of the MG considering environmental pollution effects simultaneously. In order to address the issue of optimal operation of the MG in single-objective and multi-objective forms, an intelligent method according to the improved differential evolutionary (IDE) optimization is utilized and performed and the proposed algorithm is implemented on different problems. First, it is assumed that there is no limit to the exchange of power overhead, and secondly, the limitation of power exchange with the upstream grid is considered. In multi-objective mode, these two modes are also considered. In order to show the impact of renewable energy on the cost, in the third part of the simulations, the operation is solved with maximum participation of renewable energy sources. In the final section, the sensitivity analysis on the number of populations in this problem is performed. The obtained results of the simulation are compared to differential evolutionary (DE) and particle swarm optimization (PSO) techniques. The effectiveness of the suggested multi-operational energy management method is confirmed by applying a study case system.

The characteristics of energy security in decentralised zones and autonomous objects of electrification

The article aims to develop a set of objective criteria for assessing the state of energy security in decentralised remote regions of the north, Arctic zones and autonomous energy supply complexes. The authors assessed the potential of renewable energetics, which determines the effectiveness of decentralised energy complexes based on renewable energy sources, in improving the energy security of such entities. The indicators for assessing the energy security of research objects were developed on the basis of an analysis of the ratio of the most significant threats, as well as territorial and situational factors of the autonomous energy of the north and Arctic zones. A study of the security of the research objects allowed the development of a set of criteria for territorial segments and autonomous electrification objects, forming an objective assessment of the energy security of isolated hard-to-reach areas. An analysis of the possibilities of renewable energy sources in achieving certain positions (resource sufficiency, environmental acceptability, technological attainability and reliability) of the energy security of the considered level was conducted. Groups of properties and processes within the territorial framework of a decentralised region, separated by the directions of monitoring the energy security of local energy zones are proposed as objects of indicative analysis. The differentiation of the developed criteria by the levels of the energy zone and decentralised energy complex allowed consideration of all the specific features of these objects and cover the factors of mutual influence with accompanying systems in the formation of the state of energy security. When considering a possible option for the participation of renewable energy sources in the structural and resource provision of autonomous electricity supply, it was found that such diversification will affect both the improvement of some criteria of energy security of the considered level, as well as the deterioration of others.

Mapping concentrated solar power site suitability in Algeria

The investment in solar thermal power technologies has become increasingly attractive, despite their still perceived high costs. Algeria presented an ambitious plan for increasing the participation of renewable energy sources (RES) in the power system, with significant investments foreseen for solar power technologies. To achieve this objective, it is necessary to identify optimal sites for the implementation of these plants, as well as others where implementation is highly inadvisable from the economic, social, or environmental points of view. The main goal of this study is to present and apply a methodology to identify adequate locations for the installation of solar power plants in Algeria. The study addressed the particular case of concentrated solar power (CSP) and proposed a hybrid approach combining multi-criteria decision making and Geographic Information System. The approach allowed mapping and visualizing unfeasible areas and ranking the feasible sites. The results showed that more than 51% of the territory of the country is unfeasible for the implementation of CSP, mainly due to criteria related to topographic aspects, water availability, and distance to the grid. The results demonstrated that relying only on Direct Normal Irradiation (DNI) values may result in a reductionist vision for energy planning and thus other criteria can play a fundamental role in the decision process. The model allowed also to identify the best regions for CSP investment and opens routes for more detailed studies for the exact site selection.

ANALYSIS OF THE LEVEL OF IMPLEMENTATION OF PROGRAMS FOR THE EFFICIENT USE OF ENERGY AND UNCONVENTIONAL SOURCES: CASE STUDY COLOMBIA

At the First Extraordinary Meeting of the Forum of Ministers of the Environment of Latin America and the Caribbean, Johannesburg, August 2002. An initiative for sustainable development in Latin America and the Caribbean was presented. This proposes that the countries of the region should show in their energy distribution minimum participation of 10% of renewable energy sources in the Total Primary Energy Supply (OTEP). The mechanism of action of this initiative is not based on penalizing countries that their natural conditions are not favorable for energy sustainability, but on promoting greater participation of renewable energy sources. Through the analysis of the country's energy demand and energy sources and according to the initiative, the Colombian government, through its entities, organizes programs to improve its energy efficiency and the participation of renewable energy sources and technologies, not conventional. This paper shows the statistics of energy distribution and energy sources in Colombia. Based on this information, we seek to identify the deficient sectors with their problems to implement strategies at the national level that allows them to meet the proposed goals.Keywords: Efficiency, Energy, Renewable Sources, Sustainability, Total Primary Energy Supply.JEL Classifications: L78, L90, O31, Q20DOI: https://doi.org/10.32479/ijeep.9713

Optimal reinforcement framework for distribution system based on life cycle cost and considering uncertainties

ABSTRACT Recently, renewable energy sources have been applied in distribution systems because of climate change and environmental pollution. However, the integration of these sources in the distribution systems is a complex problem because most of their output power is naturally intermittent and depending on the primary energy resources. Additionally, electricity prices and loads are uncertainties. Therefore, this paper proposes a novel multi-scenario optimisation solution to the optimal reinforcement of the distribution systems considering uncertainties of renewable energy sources, electricity prices and loads by a mixed-integer nonlinear programming model with the aim of minimising life cycle cost. A combined model with the clustering technique is utilised to integrate all uncertainty parameters of the distribution systems. The proposed methodology is verified with a modified 9-node test system by a program implemented in the general algebraic modeling system. Results with and without the participation of renewable energy sources are analysed and compared to validate the high performance of the proposed approach.

Analysis of economic viability with the use of monte carlo simulation for microgeneration of photovoltaic energy

A series of public policies are being adopted worldwide to seek greater participation of renewable energy sources in the energy matrix. Brazil is a country that has a predominantly renewable energy source, with hydroelectric energy being responsible for the largest portion, but with enormous potential to be exploited for solar energy. The objective of this study was to carry out an analysis of the economic viability of a photovoltaic matrix in the distributed microgeneration model from the residential consumer perspective. Through the Monte Carlo simulation, 10.000 iterations were performed and the NPV was calculated in each of them, then counted to recover the corresponding output probability distribution and verified the NPV probability to be greater than zero. The developed method has proved to be a reliable tool to support decision making and can be applied to several scenarios. The scenario adopted for the design of the photovoltaic system presented a 95.2% probability of returning with an NPV above zero and this makes it economically feasible. The main contribution of this paper is the replicability of the methodology used for other economic analysis studies.

Load Frequency Control of Hybrid Power System Incorporating Vehicle-to-Grid Technology Considering AC Transmission Links

In modern power system, the participation of Vehicle-to-grid (V2G) in contributing to ancillary services like frequency regulation is probable to increase due to their fast charging/discharging capabilities. Renewable energy sources (RES) also play an important role in meeting the power demand and indirectly, minimizing the utilization of fossil fuels by the conventional power plants, but their behavior is very intermittent in nature which may cause frequency fluctuations. V2G technology can be used for meeting the imbalance in demand and generation. In view of these points, this paper proposes a load frequency control scheme with the participation of RES and V2G which can enhance the system dynamics under load fluctuations. For this, a multi-source system is designed with a solar-thermal power plant (STPP) and a thermal unit in Area-1, gas and thermal unit along with an electric vehicle (EV) fleet in Area-2, and two thermal units and an EV fleet in Area-3. The application of wind driven optimized two degree of freedom proportional–integral–derivative controller as secondary controller has been attempted in this work. The impact of addition of STPP and EVs into the system is verified in terms of reduction of magnitude and numbers of oscillations of the system responses.

Robust model for optimal allocation of renewable energy sources, energy storage systems and demand response in distribution systems via information gap decision theory

Considering increasing distributed energy resources and responsive loads in smart grid paradigm, this study proposes a new approach for robust hourly energy scheduling of distribution systems at the presence of severe uncertain renewable energy sources (RES). Wind and photovoltaic power generations are considered as the RESs. The aim is to minimise the total energy procurement cost, while considering the participation of RESs, by their optimal allocation in the network. The inherent uncertainty of RESs is handled via information gap decision theory. One of the features of the proposed model is to consider the impact of demand response and energy storage system as the effective tools to reduce unintended costs due to uncertainty of RESs. Also, the proposed model handles the uncertainty of multiple RESs in a way that maximum tolerable uncertainty of RESs is achieved for a given worsening of total energy procurement cost. The proposed model is formulated as a mixed integer nonlinear optimisation problem and is implemented in general algebraic modelling system environment. The model is applied on the IEEE standard 33-bus radial test system, and the obtained results substantiate that the utilisation of ESS and DR can reduce the impact of RESs' uncertainty on the energy cost.

Solar Energy in Cuba: Current Situation and Future Development

Cuba, a small island in the Caribbean Sea with a total land area of 109.884 km2 and a population of around 11.423 million, has no significant proved oil, gas and coal reserves. Also use, in a very limited manner, some of the four main renewable energy sources available in the country for electricity production, generating just 50,1 GW/h or 4,04% of the total electricity consumed in 2015 (20.288 GW/h). In 2016, electricity consumption fell to 15.182 GW/h; this means a reduction of 25% in comparison to 2015. In 2016, the participation of renewable energy sources in the energy mix of the country reached 4,65%. The different renewable energy sources available in the country are hydropower, wind power, solar photovoltaic, and bioenergy. In 2015, out of Cuba’s total 566 MW of renewable energy capacity installed, 83% of the total was in the bioenergy sector. In 2016, the renewable energy capacity installed in the country reached 642 MW. According to the decision adopted by the Cuban government, the participation of renewable energy sources in the energy mix of the country should reach 24% in 2030, an increase of almost 20% compared to the level reported in 2016. Among the different renewable energy sources available in the country, solar energy is one of the main contributors to the national energy system, and also one of the leading supplier of energy to independent users all over the country.