Solar and Wind Power Forecasting with Optimal ARIMA Parameters

Power system flexibility analysis using net-load forecasting based on deep learning considering distributed energy sources and electric vehicles

This study evaluated a potential transition of India’s power sector to 100% wind and solar energy sources. Applying a macro-energy IDEEA (Indian Zero Carbon Energy Pathways) model to 32 regions and 114 locations of potential installation of wind energy and 60 locations of solar energy, we evaluated a 100% renewable power system in India as a concept. We considered 153 scenarios with varying sets of generating and balancing technologies to evaluate each intermittent energy source separately and their complementarity. Our analysis confirms the potential technical feasibility and long-term reliability of a 100% renewable system for India, even with solar and wind energy only. Such a dual energy source system can potentially deliver fivefold the annual demand of 2019. The robust, reliable supply can be achieved in the long term, as verified by 41 years of weather data. The required expansion of energy storage and the grid will depend on the wind and solar energy structure and the types of generating technologies. Solar energy mostly requires intraday balancing that can be achieved through storage or demand-side flexibility. Wind energy is more seasonal and spatially scattered, and benefits from the long-distance grid expansion for balancing. The complementarity of the two resources on a spatial scale reduces requirements for energy storage. The demand-side flexibility is the key in developing low-cost supply with minimum curtailments. This can be potentially achieved with the proposed two-level electricity market where electricity prices reflect variability of the supply. A modelled experiment with price signals demonstrates how balancing capacity depends on the price levels of guaranteed and flexible types of loads, and therefore, can be defined by the market.

Summary. With the continuous expansion of grid-connected power generation from renewable energy sources, such as wind and light, the forms of power sources are more diversified. The coupling and uncertainty of multiple energy sources will cause significant changes in the characteristics of the power system. Problems like the complexity of the power system lack a scientific and complete explanation. This paper comprehensively considers the regional weather conditions, the uncertainty of the output of wind and solar energy sources, and the time and space complementary characteristics of multiple power sources. Based on the theory of complex adaptive systems, a systematic and holistic optimization planning method is studied. Combining the idea of complementarity because of differences, a multipoint layout planning and design method for multienergy power systems is proposed to give full play to the synergistic effects of natural resources, achieve optimal resource allocation, and provide a theoretical basis for improving the consumption of wind and renewable energy. Taking an actual provincial power system in China as an example, through the comparison of production simulation calculations and multiscenario analysis and planning methods, the proposed method can significantly increase the consumption of wind and solar renewable energy.

Renewable energy sources like wind and solar energies can be combined to increase the total power generation and thereby increase the efficiency of the system. The combination also provides a means to overcome the intermittent nature of the solar and wind renewable energy sources, since one source can be used for power generation when the other is not available. AC-DC converters are used to convert the alternating voltage of the wind generator to a constant DC value which can be used to charge the batteries or later converted to AC voltage to drive AC loads. A Maximum Power Point Tracking (MPPT) system using a boost converter is designed to extract maximum possible power from the sun when it is available. This method provides better harmonic reduction since Harmonic content is detrimental for the generator lifespan, heating issues, and efficiency. Simulations are carried out in PSIM software and MATLAB.' Keywords: Boost converter, hybrid system, MATLAB, MPPT, PSIM software, renewable energy

A new hybrid decomposition-based multiobjective evolutionary algorithm is proposed for optimal power flow (OPF) including wind and solar generation uncertainty. This study recommends a novel constraint-handling method, which adaptively adds the penalty function and eliminates the parameter dependency on penalty function evaluation. The summation-based sorting and improved diversified selection methods are utilized to enhance the diversity of multiobjective optimization algorithms. The OPF problem is modeled as a multiobjective optimization problem with four objectives such as minimizing (i) total fuel cost (TC) including the cost of renewable energy source (RES), (ii) total emission (TE), (iii) active power loss (APL), and (iv) voltage magnitude deviation (VMD). The impact of RESs such as wind and solar energy sources on integration is considered in optimal power flow cost analysis. The costs of RESs are considered in the OPF problem to minimize the overall cost so that the impact of intermittence and uncertainty of renewable sources is studied in terms of cost and operation wise. The uncertainty of wind and solar energy sources is described using probability distribution functions (PDFs) such as Weibull and lognormal distributions. The efficiency of the algorithm is tested on IEEE 30-, IEEE 57-, and IEEE 118-bus systems for all possible conditions of renewable sources using Monte Carlo simulations.

Abstract–This study focuses on the integration of wind and solar energy sources to create hybrid power systems, with an emphasis on evaluating their performance through advanced control techniques. The increasing demand for sustainable energy solutions has driven the need for efficient utilization of renewable resources. Wind and solar energies, being prominent among these resources, offer substantial potential for power generation. The paper investigates the performance of hybrid systems that combine both wind and solar energy generation. These systems are designed to seamlessly switch between the two sources based on availability and prevailing environmental conditions. The integration is facilitated by advanced control mechanisms that ensure optimal power capture and distribution. The evaluation encompasses various aspects of performance, including efficiency, reliability, and grid adaptability. The hybrid system's ability to handle fluctuating conditions and its response to grid perturbations are studied comprehensively. Furthermore, the influence of different control strategies on overall system performance is analyzed.

Multi-objective optimal power flow of thermal-wind-solar power system using an adaptive geometry estimation based multi-objective differential evolution

Attention paid to energy efficiency in datacenters has been increasing significantly in the last decade. One of the latest trends on this issue is supplying datacenters with renewable energy, and reducing the carbon footprint of datacenters is a major step towards green computing. Following this trend, more and more datacenters are built in cold climate areas for cheaper cooling and increased energy efficiency of the facilities. However, such geographical locations have a very varying availability of renewable energy (especially solar energy), depending on the annual month and fitting the datacenters completely with renewable energy is hence more difficult. This paper analyzes the feasibility of using renewable energies for a datacenter located on the 60° latitude north. We analyze the energy consumption caused by the server workload and the cost-to-energy trade-off related to available wind and solar energy sources. A wind and solar power model is built based on real weather data for the city of Turku, Finland, and a feasibility study is conducted for fitting a datacenter with renewable energy sources on such a location. The available monthly and annual renewable energy is analyzed for different scenarios and compared with the energy consumption of a simulated datacenter. We also analyze the ratio between number of wind turbines and m2 solar panel to achieve a desired fraction of renewable energy sources for a given datacenter.

PurposeThe purpose of this paper is to investigate the social acceptance of renewable and non-renewable energies in Iran using the social acceptance pyramid.Design/methodology/approachToday, social acceptance is considered a very important phenomenon in the development, implementation and achievement of energy policy goals. Low acceptance will make it difficult to achieve energy development goals; therefore, social acceptance must be taken into account when making policy. Firstly, the model criteria, using data obtained from questionnaires, are weighted by the Shannon entropy method and, finally, four sources of fossil, nuclear, wind and solar energy were ranked by means of VIKOR, Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS).FindingsThe results show that, in Iran, the social acceptance criterion and trust sub-criterion are the most important criteria for energy acceptance. The results of the ranking of options based on multiple-criteria decision-making (MCDM) techniques show that, given Iran's specific energy requirements, social acceptance of fossil energy is higher than wind, solar and nuclear, and wind, solar and nuclear energy come later in the rankings.Originality/valueThis research contributes to the literature in two ways: Firstly, social acceptance is considered a very important phenomenon in the development, implementation and achievement of energy policy goals; thus social acceptance must be taken into account when making policy. The results of the ranking of options based on MCDM techniques show that, given Iran's specific energy requirements, social acceptance of fossil energy is higher than wind, solar and nuclear, and wind, solar and nuclear energy come later in the rankings. Also, the social acceptance criterion and trust sub-criterion are the most important criteria for energy acceptance in Iran.

A deep learning-based forecasting model for renewable energy scenarios to guide sustainable energy policy: A case study of Korea

Solar power from deserts can contribute significantly to a future renewable energy system. The technically accessible solar potential in deserts exceeds the global energy demand by a factor of 20. In the DESERTEC concept, a smart super grid based on HVDC technology interconnects wind, solar and other renewable energy sources with distant consumers on a scale of several thousand kilometres. The large grid averages out the natural fluctuations of renewable energy sources to a large extend. Remaining fluctuations have to be compensated by storage systems. Two competing technologies, CSP and PV, are available for large-scale solar power production in desert countries. CSP technology can be combined with thermal energy storage and water desalination. A large-scale production of solar energy in desert countries has important socio-economic implications. The interconnection of continents by large power grids introduces new economical interdependencies, which can help to reduce the North-South gradient of economic wealth.

The increase in energy demand due to the deployment of conventional sources makes shift towards Renewable Energy Sources. As Renewable energy cannot be tapped for continuous time, it is very convenient to add another source of energy to solar and wind energy sources. RES when added with other temporary sources of energy is called Hybrid Energy Source System. Hybrid System helps in meeting the peak demand during peak hours by using load generated at that point as main supply and the other source as secondary source. In this paper two renewable energy sources like Solar and Biomass energy is combined to form Hybrid Energy Source. In India solar energy is available abundantly and in villages where agriculture is the main source of income creates Biomass. For a particular region both these energy resources are combined and studied in this paper. The advantages of combining both the plants and the applications, usability of these sources depending upon the peak hours and the off peak hours are studied in this paper. These combinations helps us to reduce pollution, as garbage obtained from the agriculture plants will be utilized to generate power and also free availability of carbon free solar energy.

Feasibility of using renewable energy to supply data centers in 60[formula omitted] north latitude

With the policy of prioritizing the development of renewable energy sources, the total capacity of renewable energy sources in Vietnam is increasing day by day. However, there are a few issues that need to be resolved. Wind and solar energy sources are highly dependent on weather conditions, but the weather is inherently erratic, so these energy sources are always unstable with changes in weather. Because solar and wind power systems are non-inertial power systems, so it is necessary to have inertia power systems such as thermal power (coal, LNG), hydroelectricity, atomic electricity to maintain a stable continuous power supply. The problem is to moderate these power sources to meet the economic and emission optimization goals. This paper focuses on researching optimization algorithms to find the best solutions for the economic and emission problem in Microgrid system including 2 generators, 1 Combined heat and power (CHP), 1 Photovoltaic (PV), 1 WT (Wind Turbine). Applying Symbiotic Organisms Search Algorithm to search for optimal solutions for the above problems, the paper gives better results than other algorithms up to 20%.

Paper describes and analyses new and innovative concept for possible integration of solar photovoltaic (PV) energy in urban water supply system (UWSS). Proposed system consists of PV generator and invertor, pump station and water reservoir. System is sized in such a manner that every his part is sized separately and after this integrated into a whole. This integration is desirable for several reasons, where the most important is the achievement of the objectives of sustainable living in urban areas i.e. achieving of sustainable urban water supply system. The biggest technological challenge associated with the use of solar, wind and other intermittent renewable energy sources RES is the realization of economically and environmentally friendly electric energy storage (EES). The paper elaborates the use of water reservoires in UWSS as EES. The proposed solution is still more expensive than the traditional and is economically acceptable today in the cases of isolated urban water system and special situations. Wider application will depend on the future trends of energy prices, construction costs of PV generators and needs for CO2 reduction by urban water infrastructure.