Including Wind Power Research Articles

Robust Scheduling Optimization Model for Combined Cooling, Heating and Power System in Industrial Parks

The multi energy complementary system is a new power energy technology Firstly, we studied renewable energy and load uncertainties of an operation optimization system, and established the industrial park energy system, which includes wind power, photovoltaic power, a combined cooling, heating and power system, and an energy storage tank. Secondly, given the renewable energy uncertainties of unit output and load, we introduced a robust multi-objective operation optimization method for industrial park energy supply systems while considering conservative system operation. Thirdly, we examined the synergetic and game relationship among multiple objectives. The particle swarm optimization algorithm is was used to optimize the system operation scheme, reduce the feasible domain, and improve the efficiency of the solution. Finally, the simulation results show that the operation optimization method effectively uses the demand response to optimize economic and environmental objectives and ensure the optimal operation efficiency of the system under multiple uncertainties.

풍력발전원을 포함한 AC와 DC 송전시스템 신뢰도 산정

The supply of renewable energy is expanding around the world, and Korea plans to expand the amount of wind power plants among renewable energy. As wind power complexes are added, the reliability of the system is important. The failure rate of the entire system may vary depending on the failure rate of the component.<BR> In this paper, the serial and parallel structures of HVAC and VSC-HVDC were composed and the failure rate for each component was calculated. Then, the failure rate of wind power generators was calculated through the failure rate data for each component of the wind power generator failure rate was calculated. The system failure rate from generators to power-linked point including wind power generators was assessed and the power transmission system failure rate was compared depending on the number of wind power generators.

Day-ahead interval optimization for CCHP system considering uncertainty of wind power and PV

To address the uncertainty of renewable energy and different load demands under different seasons in combined cooling, heating, and power (CCHP) system, a day-ahead interval scheduling optimization method is proposed for the CCHP system taking into account the uncertainty of wind power and photovoltaic (PV). Based on the interval theory, the uncertainty of wind power and PV are expressed by intervals. The total operating cost of carbon oxide emissions treatment cost and energy purchase cost is minimized as an objective function. A day-ahead interval optimization model of the CCHP system including wind power, PV, and energy storage is established considering different load demands in four seasons. The established nonlinear integer programming model is converted into the mixed-integer linear programming (MILP) model. The model is solved by interval linear programming. The CCHP system of a park is studied and compared with robust optimization. The simulation results verify the effectiveness of the method in this paper to achieve effective cooperative operation of the economy and environmental protection.

Improved Symbiotic Organisms Search Algorithm for Optimal Operation of Active Distribution Systems Incorporating Renewables and Emerging Data‐Center Resources

AbstractThe optimal operation analysis plays an important role in estimating the expected return of investment for power systems. However, this work could be highly challenging under the context of active distribution network, where a variety of renewable energy sources and emerging active loads (such as Internet data centers) could be penetrated that introduce a high level of nonlinearity and nonconvexity characteristics into the system modeling. To overcome such challenge, this paper presents a new methodological framework based on the improvements of symbiotic organisms search (SOS) algorithm to address the optimal operation problem of active distribution systems containing renewable energy sources and datacenter resources, aiming to provide a practical tool for system analysis, particularly subject to nonconvexity nature of system components. For this purpose, a generic model for the distribution system including wind power, PV, and datacenter resources is first developed, which not only captures the uncertain nature of system components but also accounts for their spatiotemporal flexibility during operation. On this basis, in order to improve the computation efficiency of the problem, the SOS algorithm is improved by designing the selection strategy of random parameters. By using the penalty function method, the concerned problem is expressed as a nonlinear unconstrained optimization problem. The performance of the proposed model and algorithm is examined through comparative studies. It is shown that the proposed method is able to schedule the renewable energy resources and flexible demand of datacenters coordinately to reduce the operation cost of the system significantly in the case study. In addition, the proposed algorithm demonstrates a higher level of accuracy as well as better convergence efficiency compared to other conventional techniques.

Managing the Volatility Risk of Renewable Energy: Index Insurance for Offshore Wind Farms in Taiwan

Renewable energy is produced using renewable natural resources, including wind power. The Taiwan government aims to have renewable energy account for 20% of its total power supply by 2025, in which offshore wind power plays an important role. This paper explores the application of index insurance to renewable energy for offshore wind power in Taiwan. We employ autoregressive integrated moving average models to forecast power generation on a monthly and annual basis for the Changhua Demonstration Offshore Wind Farm. These predictions are based on an analysis of 39 years of hourly wind speed data (1980–2018) from the Modern-Era Retrospective analysis for Research and Applications, Version 2, of the National Aeronautics and Space Administration. The data analysis and forecasting models describe the methodology used to design the insurance contract and its index for predicting offshore wind power generation. We apply our forecasting results to insurance contract pricing.

How Policies Guide and Promoted Wind Power to Market Transactions in China during the 2010s

Chinese wind power policies have productively promoted the development of wind power and also promoted the process of wind power participation in electricity market transactions. However, with policy emphasis on investment and neglect of utilization, there have been some difficulties in the development of Chinese wind power. To highlight the guiding role of policy and improve the wind power policy system, an analysis of Chinese wind power policies is conducted in this paper. First, aiming at the main components of wind power chain, including wind power construction, grid connection, transmission, and sales, a comprehensive and systematic frame of Chinese wind power policy system is proposed from the three aspects of development planning, administrative management and market transactions. Second, the indicator system of Chinese wind power development effectiveness is extracted, including installed capacity, power generation, power utilization hours, carbon emission reduction, investment, on-grid power price, wind curtailment rate, etc., and the effectiveness of policy implementation is verified. Third, new policy recommendations are proposed from parts of transmission, consumption, and market, for the development of Chinese wind power industry in the 14th Five-Year Plan period and the goal to reach the crest value of carbon dioxide emissions by 2030 and achieve carbon neutrality by 2060. In this paper, advice to supplement and improve the Chinese wind power policy system is provided, which may it promote better development of Chinese wind power in the following decade from the policy point of view.

Optimization and performance enhancement of concentrating solar power in a hot and arid desert environment

The Concentrating Solar Power - Parabolic Trough (CSP-PT) technology with dry-cooled condenser system is an alternative option for arid climate locations such as Kuwait. In this work, the performance of various CSP-PT design configurations is evaluated, including 19 configurations that have been reported in the literature as being optimal. These have optimal Solar Multiple (SM) values based on the lowest Levelised Cost of Electricity (LCOE).Furthermore, an evaluation of CSP-PT with Thermal Energy Storage (TES), including wind power potential, is performed. It is revealed that coinciding peaks of electrical load, solar, and wind resources promote co-generation from CSP-PT/TES and wind power with significant benefits. Also, the wind speed is found to be at maximum levels at high altitudes in the early daytime and late nighttime. Whereas in the afternoon, it reaches maximum values at low altitudes. The calculated wind shear exponent is between 0.14-0.18 and showing a cyclic behavior. Such findings promote mega-scale wind power generation.From the techno-economic assessment, it is concluded that the SM value for optimal CSP-PT/TES configuration increases with an increasing number of full load hours of storage (NhTES). In addition, the NhTES has significant effects on the annual energy generation, capacity factor, and LCOE. However, the impact of NhTES on the annual overall plant efficiency is insignificant. Furthermore, the optimal SM and lowest LCOE values are determined. Also, the periods of 24 h continuous electricity generation from CSP-PT/TES without fossil backup have been identified.

Research on Decision Optimization Model of Microgrid Participating in Spot Market Transaction

The development of electricity spot trading provides an opportunity for microgrids to participate in the spot market transaction, which is of great significance to the research of microgrids participating in the electricity spot market. Under the background of spot market construction, this paper takes the microgrid including wind power, photovoltaic (PV), gas turbine, battery storage, and demand response as the research object, uses the stochastic optimization method to deal with the uncertainty of wind and PV power, and constructs a decision optimization model with the goal of maximizing the expected revenue of microgrids in the spot market. Through the case study, the optimal bidding electricity of microgrid operators in the spot market is obtained, and the revenue is USD 923.07. Then, this paper further investigates the effects of demand response, meteorological factors, market price coefficients, and cost coefficients on the expected revenue of microgrids. The results demonstrate that the demand response adopted in this paper has better social–economic benefits, which can reduce the peak load while ensuring the reliability of the microgrid, and the optimization model also ensure profits while extreme weather and related economic coefficients change, providing a set of scientific quantitative analysis tools for microgrids to trade electricity in the spot market.

THE FUTURE STRATEGIES OF THE WIND POWER DEVELOPMENT IN ALBANIA: CASE STUDY: “QAFE THANE,” POGRADEC, ALBANIA

The development of the electricity sector in Albania continues to be fenced by high rates of inefficiencies, insufficient security of supply, low rate of RES investment including wind power plants and the need to further unbundle and liberalise the energy market following the adoption of the legal basis, including GHG credits is inevitable. A lot of issues are set to face the challenges of energy transition, oriented by the Albanian government’s endeavor to maintain a sustainable, secure, flexible in time, efficiently supplied, climate-friendly and affordable energy supply system is required. The most critical aspects to attain 2030 energy goals and beyond cannot be achieved without the promotion of carbonless power technologies reducing (GHG) emissions. As a consequence, huge investments in RES energy based power generation systems and related RES technologies are required. To subjugate the barriers to clean energy technology implementation especially at the preliminary feasibility stage, the latest model, RETScreen Expert 8 added the ability to rapidly analyze the feasibility of multiple wind power plant options at real site condition. This fast feature of the model enables us to assess the real potential of the proposed 27 MW wind farm by choosing a set of 16 different turbine types and models combined into 14 possible scenarios with the aim to expand the capacity in the future is applied. From the simulation executed in RETScreen Expert the technical and economic optimization of the proposed energy system is achieved. Sector-specific actions are explored in the paper, but at the higher level of specific investment costs and a number of cross-cutting actions that should be addressed with urgency from policy makers in the country are identified. Keywords: Wind Power Plant, HPP, RETScreen Expert, Net Present Value, Internal Rate of Return, Cash Flow JEL Classifications: Q4, Q42, Q47, Q48, Q58 DOI: https://doi.org/10.32479/ijeep.11228

An integrated energy system scheduling optimization method considering economy, stability and environmental protection

In this paper, first, an energy efficiency evaluation method including economy, stability and environmental protection was given. Second, a mathematical model of the integrated energy system and a single-objective economic optimization model under different operation conditions, which add renewable energy and power storage equipment and could be solved based on the greedy algorithm, were given to improve the energy efficiency. Finally, an integrated energy system including wind power, photovoltaics, power storage equipment and conventional loads was taken as an example. Considering the time-of-use electricity price and the full utilization of energy storage, 4 optimization plans were set up for comprehensive energy efficiency evaluation and comparison. The result shows that the energy efficiency evaluation method proposed in this paper is practical and feasible, and the optimization method proposed plays a guiding role in the operation of similar parks.

PENGARUH JUMLAH DAN SUDUT PEMASANGAN SUDU TERHADAP DAYA TURBIN ANGIN SAVONIUS

&#x0D; &#x0D; &#x0D; The problem in Energy conservation is finding new opportunities for high-efficiency energy generation including wind power generating machines. This study aims to determine the effect of the number and curv angle of blade mounting on the output power of a Savonius type wind turbine. This low speed wind turbine is intended to get energy at the top of a multi-storey building in an urban area. Tests were carried out on a laboratory scale, using savonius wind turbines with a diameter of 400 mm and a height of 500 mm. The driving wind speed of the turbine is set between 1.5 to 8.5 m / s. While the number of blades used is 2 types, namely rotor with three blades and rotor with 4 blades, each of which is tested on 3 different types of curv angle blade. The investigation results are expected to show that the wind tubing from each experiment will give different characteristics. The results showed that there was an increase in efficiency in the savonius turbine with blades. The highest rotation and power occur when the turbine uses 2 blades and -50 curv angle of blade mounting&#x0D; &#x0D; &#x0D;

Optimal economic power and heat dispatch in Cogeneration Systems including wind power

Economic Dispatch in Cogeneration Systems (EDCS) provides the optimal scheduling of heat and power of generation units. This can be achieved by minimizing the total cost of fuel (TCF) of the cogeneration units taking into consideration their operational limits. A manta ray foraging MRF optimizer, in this paper, is developed to solve the EDCS problem including the valve point impacts, and wind power. MRF optimizer is designed with adaptive penalty functions for acquiring the most feasible and best operational points for the EDCS problem. Infeasible solutions are handled with various degrees and penalized depending on their remoteness from the closest possible point. The overall power and heat loading are completely achieved by the equality constraints. Also, the cogeneration units’ dynamic operating limits are not adversely affected since its concerning limitations of heat-only and power-only units are fulfilled. Two test systems of small 5 and large 96-units, are analyzed. In addition to this, an assessment of the recent optimization techniques, which are applied on to EDCS, has been developed and discussed. The applications are carried out for two scenarios at peak and daily variation in the power and heat loading condition. The wind power inclusion is assessed for each scenario in terms of the overall reduction in the total fuel costs. It was proven also; the inclusion of wind power achieves more economical solution at different scenarios with reduction up to 8%. It is crystal clear that the outputs obtained illustrate MRF optimizer efficiency, feasibility, and capability to obtain better solutions in minimizing the fuel cost compared to other optimization techniques at acceptable convergence rates. Moreover, the solutions demonstrate the ability of MRF optimizer application on the large-scale 96-unit systems.

Model Rangkaian-T Pembangkit Listrik Tenaga Bayu untuk Analisis Aliran Daya Tiga-Fase

Akhir-akhir ini, penetrasi Pembangkit Listrik Tenaga Bayu (PLTB) pada sistem distribusi tenaga listrik mengalami peningkatan yang cukup signifikan. Penetrasi PLTB ini dapat memengaruhi kondisi keadaan mantap dan dinamik sistem tersebut. Lebih lanjut, sistem distribusi tenaga listrik biasanya tidak seimbang, sehingga harus dianalisis secara tiga-fase. Oleh karena itu, agar kondisi-kondisi sistem dapat dievaluasi dengan baik, pembentukan model tiga-fase dari komponen-komponen sistem (termasuk PLTB) merupakan hal yang sangat penting. Makalah ini mengusulkan metode sederhana dalam memodelkan dan mengintegrasikan PLTB kecepatan tetap untuk analisis keadaan mantap (atau analisis aliran daya) sistem distribusi tiga-fase. Metode yang diusulkan tersebut didasarkan pada model rangkaian-T yang sebelumnya telah berhasil diaplikasikan pada sistem fase-tunggal. Pada makalah ini, model rangkaian-T fase-tunggal tersebut dimodifikasi dan diperluas sehingga dapat memfasilitasi analisis aliran daya tiga-fase pada kondisi sistem tak-seimbang. Aplikasi usulan model pada dua sistem distribusi tiga-fase, yaitu sistem 33-simpul dan 25 simpul, juga diselidiki dan disajikan pada makalah ini. Hasil-hasil penyelidikan yang dilakukan pada sistem tersebut memperlihatkan bahwa metode yang diusulkan valid dan akurat.

Feature selection for energy system modeling: Identification of relevant time series information

Heuristic or clustering based time series aggregation methods are often used to reduce temporal complexity of energy system models by selecting representative days. However, these methods potentially neglect relevant information of time series (e.g., distribution parameters). To identify relevant time series parameters, feature selection algorithms can be applied. The present research contributes by (a) developing a new feature selection approach based on clustering, nested modeling and regression (CNR) which is designed for applications requiring high selectivity and using different data sets, (b) comparing and evaluating CNR with feature selection methods available from the literature (e.g., LASSO) and (c) identifying relevant information of the time series applied in energy system models, in particular those of demand, photovoltaic and wind. Results show that CNR achieves on average up to 101 % lower mean absolute errors when methods are directly compared. Thus, CNR better identifies relevant information when the number of selected features is restricted. The disadvantage of CNR, however, is its high computational effort. A potential remedy to counter this is the combination with another method (e.g., as pre-feature selection). In terms of relevant information, energy systems including photovoltaic are mainly characterized by the correlation between demand and photovoltaic time series as well as the range and the 35 % quantile of demand. When energy systems include wind power, the minimum and mean of wind as well as the correlation between demand and wind time series are relevant characteristics. The implications of these findings are discussed.

PENGARUH JUMLAH DAN SUDUT PEMASANGAN SUDU TERHADAP DAYA TURBIN SAVONIUS

The problem in Energy conservation is finding new opportunities for high-efficiency energy generation including wind power generating machines. Aims of this study to determine the effects of blade number and curv angle of blade mounting on the output power of a Savonius type wind turbine. This low speed wind turbine is intended to get energy at the top of a multi-storey building in an urban area. Tests were carried out on a laboratory scale, using savonius wind turbines with 400 mm diameter and 500 mm height. The driving wind speed of the turbine is set between 1.5 to 8.5 m / s. While the number of blades used is 2 types, namely rotor with three blades and rotor with 4 blades, each of which is tested on 3 different types of curv angle blade.&#x0D; The investigation results are expected to show that the wind tubing from each experiment will give different characteristics. This investigation results that there was increasing in efficiency in the savonius turbine with blades. The highest rotation and power occur when the turbine uses 2 blades and -50 curv angle of blade mounting

Research on calculation of spinning reserve capacity of wind power system considering multiple uncertainties

With the development of artificial intelligence technology, power system has gradually adopted this technology. In order to better promote the application of artificial intelligence in power system, various algorithms for power system need to be further optimized and improved.After a large-scale wind power grid-connected, its random fluctuation characteristics significantly increase the uncertainty of power system operation. The traditional deterministic reserve capacity determination method has been difficult to meet the needs of the safe and economic operation of the system. It is necessary to comprehensively consider all kinds of uncertain factors that may change the operation state of the system, so as to accurately obtain the rotational reserve demand of the system. Based on this, considering the multiple uncertainties of wind power forecasting error, load forecasting error and conventional outage, this paper proposes a method to determine the reserve capacity of power system including wind power, and deduces the quantitative relationship between upper reserve capacity and loss of load probability (LOLP), lower reserve capacity and wind curtailment probability (WCP). Finally, a case study is given. The research in this paper can be used as the basis of coordinated dispatching and reserve sharing of interconnected power systems.

Research on frequency Control Strategy of micro grid including wind power and hybrid energy storage system

In view of the frequency fluctuation of the micro-grid system containing wind power, hybrid energy storage system composed of batteries and supercapacitors is adopted to coordinate the output, so as to maintain the frequency stability of the micro-grid and provide the possibility for the micro-grid to further absorb wind power and other clean energy. Firstly, by analyzing the characteristics of wind power output, the power deviation signal of the system is decomposed into low-frequency and high-frequency parts through wavelet packet decomposition, so as to maximize the consumption of wind power output power on the premise of meeting the stability of the system. Then, the high frequency part of the power gap is further divided to determine the initial FM power distribution scheme of the energy storage system. Finally, the energy storage output is modified by the Logistic regression function to take into account both the energy storage adaptive frequency modulation and the energy storage charged state self-recovery. Example analysis shows that the proposed control strategy can realize the optimal distribution of wind power, ensure the full utilization of wind farm output, improve wind power grid connection capacity, and increase efficiency and economy.

Integrated Optimal Dispatching Strategy Considering Power Generation and Consumption Interaction

The rapid development of renewable energy and the continuous growth of peak load bring new challenges to the dispatching capacity of generation side. In view of the possible mismatch between power generation of renewable energy and the load, we propose an integrated optimal dispatching strategy model of power generation and consumption interaction in this paper. Among them, the generation side resources include wind power, photovoltaic and battery energy storage and the load side dispatching resources include transferable load, interruptible load and electric vehicles. The model takes the benefits of generation side and the benefits of load side as objectives. Moreover, three different dispatching orders are put forward, which are random dispatching, interruption and transfer of load before electric vehicles charging and discharging, electric vehicles charging and discharging before interruption and transfer of load. In addition, we propose seven different dispatching combinations based on the optimal dispatching order to analyse the response ability of different load side dispatching resources. Multi-objective Genetic Algorithm and the method of technique for order preference by similarity to an ideal solution are applied in this study to obtain the optimal results. It can be identified that the response ability of different load side dispatching resources is different, and the overall dispatching can improve the benefits of generation side and the benefits of load side. Meanwhile, the proposed strategy considers the willingness of the load to the greatest extent and effectively improves the utilization rate of wind and solar power generation.

Optimal Unit Commitment Problem Considering Stochastic Wind Energy Penetration

Wind energy has attracted much attention as a clean energy resource with low running cost over the last decade,. However, due to the unpredictable nature of wind speed, the Unit Commitment (UC) problem including wind power becomes more difficult. Therefore, engineers and researchers are required to seek reliable models and techniques to plan the operation of thermal units in presence of wind farms. This paper presents a new attempt to solve the stochastic UC including wind energy sources. In order to achieve this, the problem is modeled as a chance-constrained optimization problem. Then, a method based on the here-and-now strategy is used to convert the uncertain power balance constraint into a deterministic constraint. The obtained deterministic problem is modeled using Mixed Integer Programming (MIP) on GAMS interface whereas the CEPLEX MIP solver is employed for its solution.

Multi-level interactive unit commitment of regional power system

Distributed energy resource (DER) including wind power, solar energy and energy storage system (ESS) are connected to the active distribution network (ADN) in various combination ways, which makes the distribution network have interaction. As a bridge connecting the transmission grid (TG) and micro grid (MG), ADN breaks the traditional operation pattern of TG + ADN + MG. Considering the physical connections and shared information among TG, ADN and MG, this paper proposes a decentralized and parallel analytical target cascading (ATC) algorithm for interactive unit commitment (UC) implementation in regional power systems. To explore the synergistic ability of the TG + ADN + MG coping with uncertainties of DER, i.e., wind power, the primary and secondary frequency regulation of TG are implemented to cope with uncertainties. Furthermore, the distributional uncertainty of wind power is well modeled by data driven, which is proposed in our previous work (Zhang et al., 2019) [1]. Both the startup/shutdown variables of the thermal units and the variables in TG + ADN + MG are integrated into the multi-level interactive UC model to optimize simultaneously, thus realizing the optimal goal of the whole network, resources complementary and optimal allocation of power system. An improved 6-bus system is used to test the proposed model, the numerical results show that the proposed decentralized algorithm is a fully parallelized procedure. And it also demonstrates the parallel implementation significantly enhances computations efficiency of the ATC algorithm.