Multi-timescale robust dispatching for coordinated automatic generation control and energy storage

The increasing penetration of renewable energy into power grids is reducing the regulation capacity of automatic generation control (AGC). Thus, there is an urgent demand to coordinate AGC units with active equipment such as energy storage. Current dispatch decision-making methods often ignore the intermittent effects of renewable energy. This paper proposes a two-stage robust optimization model in which energy storage is used to compensate for the intermittency of renewable energy for the dispatch of AGC units. This model exploits the rapid adjustment capability of energy storage to compensate for the slow response speed of AGC units, improve the adjustment potential, and respond to the problems of intermittent power generation from renewable energy. A column and constraint generation algorithm is used to solve the model. In an example analysis, the proposed model was more robust than a model that did not consider energy storage at eliminating the effects of intermittency while offering clear improvements in economy and efficiency     

Study on multi‐objective optimization of load dispatch including renewable energy and CCS technologies

This paper mainly studies the multi‐objective optimization of load dispatch of power systems including renewable energy and CO₂ capture and storage (CCS) technologies. The improved environmental/economic load dispatch model for the power system is constructed, considering the renewable energy utilization and CCS technologies. A novel singular weighted method (SWM) has been proposed in this paper for solving this kind of multi‐objective and multi‐constraint optimization problem. A power system with five generators has been applied in one case study to test the model and SWM. It was concluded that the share that each unit takes is not linear; however, the optimal results are largely relevant to the characteristics of the units. In addition, the research results showed that with the increment of the weight coefficient for a certain objective function, the optimization result was closer to the single optimization result for that objective function; and with the increase of forecast demand load, a 35 MW wind energy unit and a 200 MW water energy unit should be built. Copyright © 2009 John Wiley & Sons, Ltd.     

GIS-based evaluation of multifarious local renewable energy sources: a case study of the Chigu area of southwestern Taiwan

The issue of regulating greenhouse gas emissions of developing countries is one of the main reasons for the US's retreat from ratifying the Kyoto Protocal, and this deserves particular attention in order to ensure that a robust international climate policy exists in the future. Enabling developing countries to move toward low-carbon energy systems would enhance the feasibility for their participation in mitigating greenhouse gas emissions. This study evaluates wind, solar, and biomass energy sources in a rural area of Chigu in southwestern Taiwan by means of analyzing technical, economic, environmental, and political implications in order to establish an evaluation model for developing local renewable energy sources. The adopted approach evaluates local potentials of renewable energy sources with the aid of a geographic information system according to actual local conditions, and allows the assessment to consider local potentials and restrictions such as climate conditions, land uses, and ecological environments, thus enabling a more-accurate assessment than is possible with evaluations on an approximate basis. These results may help build a developmental vision for sustainable energy systems based on locally available natural resources, and facilitate a transition of national energy and environmental policies towards sustainability.     

The renewable energy targets of the Maghreb countries: Impact on electricity supply and conventional power markets

Morocco, Algeria and Tunisia, the three countries of the North African Maghreb region, are showing increased efforts to integrate renewable electricity into their power markets. Like many other countries, they have pronounced renewable energy targets, defining future shares of “green” electricity in their national generation mixes. The individual national targets are relatively varied, reflecting the different availability of renewable resources in each country, but also the different political ambitions for renewable electricity in the Maghreb states. Open questions remain regarding the targets’ economic impact on the power markets. Our article addresses this issue by applying a linear electricity market optimization model to the North African countries. Assuming a competitive, regional electricity market in the Maghreb, the model minimizes dispatch and investment costs and simulates the impact of the renewable energy targets on the conventional generation system until 2025. Special emphasis is put on investment decisions and overall system costs.     

计及风火系统聚合特性的虚拟电厂经济调度研究

提出一个VPP(虚拟发电厂)聚合出力特性的含新能源电网的两阶段经济调度模型。第一阶段基于包含若干风场与火电机组的VPP聚合出力特性决策VPP的总出力;第二阶段将总出力在VPP内部各发电单元之间进行分配。上述两个阶段都采用线性规划方法求解。基于IEEE—6母线电网的数值算例的计算结果表明,与传统经济调度方法相比,本研究提出的模型能降低风电弃风量近50%。     

A hybrid optimization technique for proficient energy management in smart grid environment

Electrical energy is one of the key components for the development and sustainability of any nation. India is a developing country and blessed with a huge amount of renewable energy resources still there are various remote areas where the grid supply is rarely available. As electrical energy is the basic requirement, therefore it must be taken up on priority to exploit the available renewable energy resources integrated with storage devices like fuel cells and batteries for power generation and help the planners in providing the energy-efficient and alternative solution. This solution will not only meet electricity demand but also helps reduce greenhouse gas emissions as a result the efficient, sustainable and eco-friendly solution can be achieved which would contribute a lot to the smart grid environment. In this paper, a modified grey wolf optimizer approach is utilized to develop a hybrid microgrid based on available renewable energy resources considering modern power grid interactions. The proposed approach would be able to provide a robust and efficient microgrid that utilizes solar photovoltaic technology and wind energy conversion system. This approach integrates renewable resources with the meta-heuristic optimization algorithm for optimal dispatch of energy in grid-connected hybrid microgrid system. The proposed approach is mainly aimed to provide the optimal sizing of renewable energy-based microgrids based on the load profile according to time of use. To validate the proposed approach, a comparative study is also conducted through a case study and shows a significant savings of 30.88% and 49.99% of the rolling cost in comparison with fuzzy logic and mixed integer linear programming-based energy management system respectively.     

考虑低谷调峰限制和环境成本的发电容量规划

提出一种考虑低谷调峰限制的含可再生能源电力系统发电容量规划模型,该模型能确保通过运行调度最优发电容量组合满足规划年中每一天的低谷调峰限制,然后结合筛选曲线法和拉格朗日松弛法进行求解。而且,为了研究环境成本对发电容量规划和系统调峰性能的影响,在发电成本中增加CO₂排放成本。最后,算例分析验证所提方法的合理性和有效性,结果表明了在高渗透率可再生能源电力系统发电容量规划中综合考虑低谷调峰限制和环境成本的必要性。     

Status and outlook of China's free-carbon electricity

Global warming, increased energy demand, and tremendous air pollution are forcing China to revise its energy structure of electricity generation dominated by coal (80% of total electricity) towards low-carbon electricity. Vigorous development of carbon-free energy resources of electricity is a practical way towards low-carbon electricity in China. In this paper, we shall outline renewable power generation (hydropower, wind power, solar energy, biomass energy, nuclear power, ocean energy and geothermal) together with nuclear power for China, present a reserves assessment, the current status, and barriers for further development, and finish with an outlook towards the future. In our view, China has plenty of free-carbon energy resources to revolutionize its electricity structure and redirect it towards low-carbon electricity systems. Needed are the effective energy policies to get to the way.     

Technico-economic analysis of off grid solar PV/Fuel cell energy system for residential community in desert region

A technico-economic analysis based on integrated modeling, simulation, and optimization approach is used in this study to design an off grid hybrid solar PV/Fuel Cell power system. The main objective is to optimize the design and develop dispatch control strategies of the standalone hybrid renewable power system to meet the desired electric load of a residential community located in a desert region. The effects of temperature and dust accumulation on the solar PV panels on the design and performance of the hybrid power system in a desert region is investigated. The goal of the proposed off-grid hybrid renewable energy system is to increase the penetration of renewable energy in the energy mix, reduce the greenhouse gas emissions from fossil fuel combustion, and lower the cost of energy from the power systems. Simulation, modeling, optimization and dispatch control strategies were used in this study to determine the performance and the cost of the proposed hybrid renewable power system. The simulation results show that the distributed power generation using solar PV and Fuel Cell energy systems integrated with an electrolyzer for hydrogen production and using cycle charging dispatch control strategy (the fuel cell will operate to meet the AC primary load and the surplus of electrical power is used to run the electrolyzer) offers the best performance. The hybrid power system was designed to meet the energy demand of 4500 kWh/day of the residential community (150 houses). The total power production from the distributed hybrid energy system was 52% from the solar PV, and 48% from the fuel cell. From the total electricity generated from the photovoltaic hydrogen fuel cell hybrid system, 80.70% is used to meet all the AC load of the residential community with negligible unmet AC primary load (0.08%), 14.08% is the input DC power for the electrolyzer for hydrogen production, 3.30% are the losses in the DC/AC inverter, and 1.84% is the excess power (dumped energy). The proposed off-grid hybrid renewable power system has 40.2% renewable fraction, is economically viable with a levelized cost of energy of 145 $/MWh and is environmentally friendly (zero carbon dioxide emissions during the electricity generation from the solar PV and Fuel Cell hybrid power system).     

Multiobjective optimal dispatch of microgrid based on analytic hierarchy process and quantum particle swarm optimization

Owing to the rapid development of microgrids (MGs) and growing applications of renewable energy resources, multiobjective optimal dispatch of MGs need to be studied in detail. In this study, a multiobjective optimal dispatch model is developed for a standalone MG composed of wind turbines, photovoltaics, diesel engine unit, load, and battery energy storage system. The economic cost, environmental concerns, and power supply consistency are expressed via subobjectives with varying priorities. Then, the analytic hierarchy process algorithm is employed to reasonably specify the weight coefficients of the subobjectives. The quantum particle swarm optimization algorithm is thereafter employed as a solution to achieve optimal dispatch of the MG. Finally, the validity of the proposed model and solution methodology are confirmed by case studies. This study provides reference for mathematical model of multiojective optimization of MG and can be widely used in current research field.     

太阳能光热发电技术综述

从经济、环境和社会角度来看,目前的能源供应和使用趋势明显不是可持续的。太阳能聚光光热发电（CSP）技术给拥有充足光照资源的地区带来了希望。太阳能聚光光热发电（CSP）技术可为法向直接日射辐照度（DNI）强的地区提供低碳、可再生能源。该文在简要分析太阳能光热发电技术现状基础上,介绍了太阳能光热发电当前的主要技术以及如何提高太阳能热发电实用性的相关技术。通过使用储热系统、后备燃料或带燃料的混合动力发电可以提高太阳能热发电的实用性。     

Electricity network planning targeting Low-Carbon energy transition

Electricity sector, as one of the major emission sources of carbon dioxide (CO₂), is responsible for reducing carbon emissions and is a major player that addresses global climate change. In the efforts to mitigate the impacts of climate change over the coming decades, decarbonizing power systems is critical. To achieve this goal, power generation systems need a transition from a high reliance on coal-fired power stations to a low-carbon energy mix. This paper proposes a transition planning method that includes the retirement of coal-fired generators and the integration of large-scale renewable power plants. Hence, transmission systems need to be upgraded simultaneously with the changing of generation mix to ensure system reliability. This paper also considers carbon emission cost and introduces and compares two models, which include carbon trading and carbon tax. Furthermore, issues related to the ramping of renewable power systems that are caused by the large penetration of renewable power generators are taken into account by adding the cost related to the sudden change of renewable generation (ramping cost) in the objective function. The proposed model is demonstrated on a modified IEEE 24-bus RTS system.     

Nash-Q learning-based collaborative dispatch strategy for interconnected power systems

The large-scale utilization and sharing of renewable energy in interconnected systems is crucial for realizing “instrumented, interconnected, and intelligent” power grids. The traditional optimal dispatch method can not coordinate the economic benefits of all the stakeholders from multiple regions of the transmission network, comprehensively. Hence, this study proposes a large-scale wind-power coordinated consumption strategy based on the Nash-Q method and establishes an economic dispatch model for interconnected systems considering the uncertainty of wind power, with optimal wind- power consumption as the objective for redistributing the shared benefits between regions. Initially, based on the equivalent cost of the interests of stakeholders from different regions, the state decision models are respectively constructed, and the noncooperative game Nash equilibrium model is established. The Q-learning algorithm is then introduced for high-dimension decision variables in the game model, and the dispatch solution methods for interconnected systems are presented, integrating the noncooperative game Nash equilibrium and Q-learning algorithm. Finally, the proposed method is verified through the modified IEEE 39-bus interconnection system, and it is established that this method achieves reasonable distribution of interests between regions and promotes large-scale consumption of wind power.     

考虑新能源多时间尺度不确定性的低碳电源规划方法

随着低碳电力的发展,低碳经济已成为大势所趋.合理的低碳电源规划对于碳减排和低碳经济至关重要.本文提出了一种考虑新能源多时间尺度不确定性的双层低碳电源规划方法.首先,基于Copula函数和新能源出力概率分布生成考虑多时间尺度随机性的新能源出力序列;进一步,建立了考虑碳交易和碳捕集技术的双层电源规划模型.其中,上层模型为考...     

Modelling of hybrid energy system—Part II: Combined dispatch strategies and solution algorithm

Computer simulation is an increasingly popular tool for determining the most suitable hybrid energy system type, design and control for an isolated community or a cluster of villages. This paper presents the development of the optimum control algorithm based on combined dispatch strategies, to achieve the optimal cost of battery incorporated hybrid energy system for electricity generation, during a period of time by solving the mathematical model, which was developed in Part I of this tri-series paper.The main purpose of the control system proposed here is to reduce, as much as possible, the participation of the diesel generator in the electricity generation process, taking the maximum advantage of the renewable energy resources available.The overall load dispatch scenario is controlled by the availability of renewable power, total system load demand, diesel generator operational constraints and the proper management of the battery bank. The incorporation of a battery bank makes the control operation more practical and relatively easier.     

Lift-and-project MVEE based convex hull for robust SCED with wind power integration using historical data-driven modeling approach

This paper presents an adjustable robust security constrained economic dispatch (SCED) model with wind power uncertainties. First, the scenario based adjustable robust SCED model is presented. It considers multiple scenarios from historical data as well as the spatial correlation among wind farms. Then, the proposed SCED model becomes an optimization problem with a large amount of constraints which is skillfully solved using a lift-and-project minimum volume enclosing ellipsoid (MVEE) based convex hull. Furthermore, the proposed model is transformed into a second order cone programming (SOCP) model by the use of participation factors to generate adjustable generation outputs and thus guarantee the energy balance. In order to further reduce the computational complexity, the inactive constraints reduction strategy is proposed to quickly eliminate inactive SOC security constraints before solving the model. Numerical results of IEEE 14-bus and 118-bus test systems as well as the practical Polish power systems with several wind farms show that the proposed model can achieve better economies. Moreover, more than 82% of security constraints are identified as inactive in various cases of the simulation, and the proposed inactive constraints reduction strategy is promising for improving the computational performance.     

基于条件期望价值的风险规避调度方法

短期风水火电联合系统经济调度对于减少化石燃料消耗、提高清洁能源利用效率具有重要意义,然而风电的随机不确定性、水电的多级耦合性及火电的出力非线性等给电力系统经济调度带来新的挑战.对此,综合考虑风电不确定性的风险和效益,从风险规避的角度构建了基于条件期望价值的风险规避调度模型.在此基础上,考虑调度模型多模态、非线性、复杂约...     

发展可再生能源对浙江省节能减排的意义

分析了浙江省可再生能源资源条件和发展现状,提出了发展可再生能源是浙江省优化能源结构、降低能耗强度、保护生态环境、实现低碳经济发展的重要保障措施。     

多时间尺度下计及光热—储热的主动配电网主辅联合优化调度

为解决可再生能源弃风、弃光现象与不平衡功率惩罚较重等问题,提出了一种多时间尺度下考虑光热—储热的主动配电网主辅联合调度策略.该策略在满足内部负荷前提下参与电能与备用日前市场,考虑含光热—储热的主动配电网协调调度风电、光伏、需求响应,在促进风光消纳、减少不平衡功率的同时提高主动配电网运行经济性.首先根据含储热的光热电站与...     

Green hydrogen: A new flexibility source for security constrained scheduling of power systems with renewable energies

Green hydrogen, i.e. the hydrogen generated from renewable energy sources (RES) will significantly contribute to a successful energy transition. Besides, to facilitate the integration and storage of RES, this promising energy carrier is well capable to efficiently link various energy sectors. By introduction of green hydrogen as a new flexibility source to power systems, it is necessary to investigate its possible impacts on the generation scheduling and power system security. In this paper, a security-constrained multi-period optimal power flow (SC-MPOPF) model is developed aiming to determine the optimal hourly dispatch of generators as well as power to hydrogen (P2H) units in the presence of large-scale renewable energy sources (RES). The proposed model characterizes the P2H demand flexibility in the proposed SC-MPOPF model, taking into account the electrolyzer behavior, reactive power support of P2H demands and hydrogen storage capability. The developed SC-MPOPF model is applied to IEEE 39-bus system and the obtained numerical results demonstrate the role of P2H flexibility on cost as well as RES's power curtailment reduction.