Solar PV is expected to become the most cost-competitive renewable energy owing to the rapidly decreasing cost of the system.On the other hand, hydropower is a high-quality and reliable regulating power source that can be bundled with solar PV to improve the economic feasibility of long-distance transmitted power.In this paper, a quantification model is established taking into account the regulating capacity of the reservoir, the characteristics of solar generation, and cost of hydro and solar PV with long-distance transmission based on the installed capacity ratio of hydro-solar hybrid power.Results indicate that for hydropower stations with high regulating capacity and generation factor of approximately 0.5, a hydro-solar installed capacity ratio of 1:1 will yield overall optimal economic performance, whereas for hydropower stations with daily regulating capacity reservoir and capacity factor of approximately 0.65, the optimal hydro-solar installed capacity ratio is approximately 1:0.3.In addition, the accuracy of the approach used in this study is verified through operation simulation of a hydro-solar hybrid system including ultra high-voltage direct current (UHVDC) transmission using two case studies in Africa.

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Traditional seawater desalination requires high amounts of energy, with correspondingly high costs and limited benefits, hindering wider applications of the process.To further improve the comprehensive economic benefits of seawater desalination, the desalination load can be combined with renewable energy sources such as solar energy, wind energy, and ocean energy or with the power grid to ensure its effective regulation.Utilizing energy internet (EI) technology, energy balance demand of the regional power grid, and coordinated control between coastal multi-source multi-load and regional distribution network with desalination load is reviewed herein.Several key technologies, including coordinated control of coastal multi-source multi-load system with seawater desalination load, flexible interaction between seawater desalination and regional distribution network, and combined control of coastal multi-source multi-load storage system with seawater desalination load, are discussed in detail.Adoption of the flexible interaction between seawater desalination and regional distribution networks is beneficial for solving water resource problems, improving the ability to dissipate distributed renewable energy, balancing and increasing grid loads, improving the safety and economy of coastal power grids, and achieving coordinated and comprehensive application of power grids, renewable energy sources, and coastal loads.

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As water scarcity is becoming a growing threat to human development, finding effective solutions has become an urgent need.To make better use of water resources, seawater desalination and storage systems using renewable energy sources (RES) are designed and implemented around the world.In this paper, an optimal capacity planning method for RES-pumped storage-seawater desalination (RES-PS-D) system is introduced.The configuration of the RES-PS-D system is clarified first, after which a cost-benefit analysis is performed using all cost and benefit components.A function for determining maximum economic benefits of the RES-PS-D system is then established, and the constraints are proposed based on various limitations.The mixed-integer linear programming algorithm is applied to solve the optimal function.A case study is introduced to validate the feasibility and effectiveness of the method.The conclusion shows that the strategy is suitable for solving the configuration optimization problem, and finally both merits and defects of the method are discussed.

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With the increasing proportion of wind power integration, the volatility of wind power brings huge challenges to the safe and stable operation of the electric power system.At present, the indexes commonly used to evaluate the volatility of wind power only consider its overall characteristics, such as the standard deviation of wind power, the average of power variables, etc., while ignoring the detailed volatility of wind power, that is, the features of the frequency distribution of power variables.However, how to accurately describe the detailed volatility of wind power is the key foundation to reduce its adverse influences.To address this, a quantitative method for evaluating the detailed volatility of wind power at multiple temporal-spatial scales is proposed.First, the volatility indexes which can evaluate the detailed fluctuation characteristics of wind power are presented, including the upper confidence limit, lower confidence limit and confidence interval of power variables under the certain confidence level.Then, the actual wind power data from a location in northern China is used to illustrate the application of the proposed indexes at multiple temporal (year-season-month-day) and spatial scales (wind turbine-wind turbines-wind farm-wind farms) using the calculation time windows of 10 min, 30 min, 1 h, and 4 h.Finally, the relationships between wind power forecasting accuracy and its corresponding detailed volatility are analyzed to further verify the effectiveness of the proposed indexes.The results show that the proposed volatility indexes can effectively characterize the detailed fluctuations of wind power at multiple temporal-spatial scales.It is anticipated that the results of this study will serve as an important reference for the reserve capacity planning and optimization dispatch in the electric power system which with a high proportion of renewable energy.

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Fieldbus, industrial Ethernet that is simple, reliable, economical, and practical, is widely used in Wind Energy Conversion Systems (WECSs).These techniques belong to the field of networked control systems.Network embedding to Wind Energy Conversion Systems brings many new challenges.Implementing a control system over a communication network causes inevitable time delays that may degrade performance and can even cause instability.This work addresses challenges related to the reliable control of wind energy conversion systems, based on the theoretical framework of networked control systems.A type of WECS with network-induced delay and packet dropout is modeled and adjustable deadbands are explored as a solution to reduce network traffic in WECSs.A method to study the reliable control of WECSs is presented, which takes into account system response as well as the network environment.After detailed theoretical analysis, simulation results are provided, which further demonstrate the feasibility of the proposed scheme.

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The nuclear power plant is suitable for base-load operation, while the pumped-storage unit mainly gives play to capacity benefit in the electric power system; hence, the integrated development and hybrid operation mode of the two can better meet the needs of the electric power system.This article first presents an analysis of the necessity and superiority of such mode, then explains its meaning and analyzes the working routes.Finally, it proposes the business modes as follows: low price pumping water electricity plus nuclear power in the near term; nuclear power shifted to pumped storage power participating in market competition in the middle term; and, in the long term, nuclear power shifted to pumped storage power as primary and serving as an electric power system when needed.

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Large-capacity hydropower transmission from southwestern China to load centers via ultra-high voltage direct current (UHVDC) or ultra-high voltage alternating current (UHVAC) transmission lines is an important measure of the accommodation of large-scale hydropower in China.The East China Grid (ECG) is the main hydropower receiver of the west-east power transmission channel in China.Moreover, it has been subject to a rapidly increasing rate of hydropower integration over the past decade.Currently, large-scale outer hydropower is one of the primary ECG power sources.However, the integration of rapidly increasing outer hydropower into the power grid is subject to a series of severe drawbacks.Therefore, this study considered the load demands and hydropower transmission characteristics for the analysis of several major problems and the determination of appropriate solutions.The power supply-demand balance problem, hydropower transmission schedule problem, and peakshaving problem were considered in this study.Correspondingly, three solutions are suggested in this paper, which include coordination between the outer hydropower and local power sources, an inter-provincial power complementary operation, and the introduction of a market mechanism.The findings of this study can serve as a basis to ensure that the ECG effectively receives an increased amount of outer hydropower in the future.

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Maximum power point tracking (MPPT) techniques are used to maintain photovoltaic modules operating points at the local maximum power points under non-uniform irradiance conditions (NUIC).For global maximum power point tracking (GMPPT) within an appropriate period, a hybrid artificial fish swarm algorithm (HAFSA) is proposed in this paper, which was developed using particle swarm optimization (PSO) to reformulate AFSA and improve its principal parameters.Simulation results show that under NUIC, compared with PSO and AFSA, the proposed algorithm has better performance with respect to convergence speed and convergence accuracy.Under NUIC, the average convergence times for 1000 simulation experiments completed with PSO, AFSA, and HAFSA are 0.4830 s, 0.4003 s and 0.3152 s respectively, and the average tracking time of the HAFSA algorithm is reduced by 34.74% and 21.26% compared with PSO and AFSA, respectively.The convergence times of the velocity inertia ω relative constant and linear decrement method decreased by 35.48% and 8.19%, the convergence time of the Visual relative constant mode decreased by 10.16%, and the convergence time of the Step relative constant mode decreased by 17.88%.The proposed GMPPT algorithm is simulated in MATLAB, and the algorithm tracks GMPP with excellent efficiency and fast speed.

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An integrated energy service company in an industrial park or commercial building is responsible for managing all energy sources in their local region, including electricity, water, gas, heating, and cooling.To reduce energy wastage and increase energy utilization, it is necessary to perform efficiency analyses and diagnoses on integrated energy systems (IESs).However, the integrated energy data necessary for energy efficiency analyses and diagnoses come from a wide variety of instruments, each of which uses different transmission protocols and data formats.This makes it challenging to handle energy-flow data in a unified manner.Thus, we have constructed a unified model for diagnosing energy usage abnormalities in IESs.Using this model, the data are divided into working days and non-working days, and benchmark values are calculated after the data have been weighted to enable unified analysis of several types of energy data.The energy-flow data may then be observed, managed, and compared in all aspects to monitor sudden changes in energy usage and energy wastage.The abnormal data identified and selected by the unified model are then subjected to big-data analysis using technical management tools, enabling the detection of user problems such as abnormalities pertaining to acquisition device, metering, and energy usage.This model facilitates accurate metering of energy data and improves energy efficiency.The study has significant implications in terms of fulfilling the energy saving.

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Due to the intermittency and instability of Wind-Solar energy and easy compensation of hydropower, this study proposes a Wind-Solar-Hydro power optimal scheduling model.This model is aimed at maximizing the total system power generation and the minimum ten-day joint output.To effectively optimize the multi-objective model, a new algorithm named non-dominated sorting culture differential evolution algorithm (NSCDE) is proposed.The feasibility of NSCDE was verified through several well-known benchmark problems.It was then applied to the Jinping Wind-Solar-Hydro complementary power generation system.The results demonstrate that NSCDE can provide decision makers a series of optimized scheduling schemes.

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