Optimal power flow model incorporating wind,solar, and bundled solar-thermal power in the restructured Indian power system

A new optimal power flow model for wind, solar, and solar-thermal bundled power scheduling and dispatch is proposed, incorporating the deviation incentive/penalty charges for renewable energy introduced in India. The multiobjective function is solved using the flower pollination algorithm; the scheme is successfully tested on the IEEE 30-bus and Indian utility 30-bus systems. The forecasting error constraints introduced in renewable energy scheduling and dispatch are demonstrated to be beneficial in several aspects. Solar-thermal bundling is shown to create win-win situations for thermal and solar generators. The effectiveness of the flower pollination algorithm in solving optimal power flow models is proved.     

Multi-criteria PSO-based optimal design of grid-connected hybrid renewable energy systems

ABSTRACT

Human-induced climate change through the over liberation of greenhouse gases, resulting in devastating consequences to the environment, is a concern of considerable global significance which has fuelled the diversification to alternative renewable energy sources. The unpredictable nature of renewable resources is an impediment to developing renewable projects. More reliable, effective, and economically feasible renewable energy systems can be established by consolidating various renewable energy sources such as wind and solar into a hybrid system using batteries or back-up units like conventional energy generators or grids. The precise design of these systems is a critical step toward their effective deployment. An optimal sizing strategy was developed based on a heuristic particle swarm optimization (PSO) technique to determine the optimum number and configuration of PV panels, wind turbines, and battery units by minimizing the total system life-cycle cost while maximizing the reliability of the hybrid renewable energy system (HRES) in matching the electricity supply and demand. In addition, by constraining the amount of conventional electricity purchased from the grid, environmental concerns were also considered in the presented method. Various systems with different reliabilities and potential of reducing consumer’s CO₂ emissions were designed and the behavior of the proposed method was comprehensively investigated. An HRES may reduce the annualized cost of energy and carbon footprint significantly.     

Optimization of grid tied hybrid power system in smart premises

Tapping of renewable energy sources like solar and wind is given great priority by power producers all over the world. Technical problems of linking them to the grid are solved. The cost constraints of utilizing renewable energy at specific locations are to be determined. In this work, a model is developed for grid tied hybrid power system (HPS) consisting of photovoltaic (PV) module and wind mill at the roof top of smart premises. The grid is capable of delivering and receiving energy. Objective function is formed with constraints taking into account the cost of PV module, wind mill, and grid tied inverter with controller. The constraints are rating of HPS and energy that can be delivered to the grid. Using this model, case studies were conducted in three locations in India, each location having two different demands. The results are presented. With the optimal rating of HPS, results shows that, conventional energy cost is higher.     

Multi-objective-based optimal transmission switching and demand response for managing congestion in hybrid power systems

ABSTRACT

This paper proposes a novel congestion management (CM) approach by using the optimal transmission switching (OTS) and demand response (DR) for a system with conventional thermal generators and renewable energy sources (RESs). In this paper, wind and solar PV units are considered as the RESs. The stochastic behavior of wind and solar PV powers are modeled by using the appropriate probability density functions (PDFs). The proposed CM methodology simultaneously optimizes the generation dispatch, demand response, and also the network topology of the power system. The OTS identifies the branches that should be taken out of service by significantly reducing the operating cost of the system while respecting the system security. Here, the total operating cost minimization/social welfare maximization and system losses minimization are considered as the objectives to be optimized. The proposed CM problem is solved using the multi-objective Jaya algorithm and it is used to determine a set of Pareto-optimal solutions. The Jaya algorithm is simple and it does not have any algorithmic-specific parameters to be tuned. This aspect reduces the designer’s effort in tuning the parameters to arrive at the optimum objective function value. A fuzzy logic-based approach is used to identify the best compromise solution. The effectiveness of the proposed CM approach is examined on modified IEEE 30 and practical Indian 75 bus test systems. The obtained simulation results are analyzed and they show the effectiveness of the proposed approach.     

全国碳市场启动后北京热电行业低碳运行管理方式研究

随着四大热电中心的建成投产,北京市完成了由燃机替代煤机的转变,实现了更加智能化的清洁能源发电供热。2013年北京市碳市场启动运行,给刚起步的燃气供热机组运行赋予了更广阔和更深远的意义;2017年12月19日,以发电行业为突破口,全国碳排放交易体系正式启动,北京市热电行业低碳运行管理意义重大而深远。本文以燃气热电联产机组运行数据为基础,通过计算分析,提出燃气热电联产机组清洁、高效、低碳运行方式,为全国碳市场启动后,北京乃至全国热电行业低碳运行管理提供经验借鉴。     

Global energy and emissions scenarios for effective climate change mitigation—Deterministic and stochastic scenarios with the TIAM model

The achievement possibilities of the EU 2 °C climate target have been assessed with the ETSAP TIAM global energy systems model. Cost-effective global and regional mitigation scenarios of carbon dioxide, methane, nitrous oxide and F-gases were calculated with alternative assumptions on emissions trading. In the mitigation scenarios, an 85% reduction in CO₂ emissions is needed from the baseline, and very significant changes in the energy system towards emission-free sources take place during this century. The largest new technology groups are carbon-capture and storage (CCS), nuclear power, wind power, advanced bioenergy technologies and energy efficiency measures. CCS technologies contributed a 5.5-Pg CO₂ annual emission reduction by 2050 and 12 Pg CO₂ reduction by 2100. Also large-scale forestation measures were found cost-efficient. Forestation measures reached their maximum impact of 7.7 Pg CO₂ annual emission reduction in 2080. The effects of uncertainties in the climate sensitivity have been analysed with stochastic scenarios.     

Triple-objective optimal sizing based on dynamic strategy for an islanded hybrid energy microgrid

A triple-objective optimal sizing method based on a dynamic strategy is presented for an islanded hybrid energy microgrid, consisting of wind turbine, solar photovoltaic, battery energy storage system and diesel generator. The dynamic strategy is given based on a dynamic complementary coordination between two different master-slave control modes for maximum renewable energy utilization. Combined with the proposed strategy, NSGA-II-based optimization program is applied to the sizing optimization problem with triple different objectives including the minimization of annualized system cost, the minimization of loss of power supply probability and the maximization of utilization ratio of renewable energy generation. The sizing results and the proposed strategy are both compared and analyzed to validate the proposed method in a real case of an islanded hybrid energy microgrid on Dong’ao Island, China.     

Electricity systems with near-zero emissions of CO2 based on wind energy and coal gasification with CCS and hydrogen storage

Emissions from electricity generation will have to be reduced to near-zero to meet targets for reducing overall greenhouse gas emissions. Variable renewable energy sources such as wind will help to achieve this goal but they will have to be used in conjunction with other flexible power plants with low-CO₂ emissions. A process which would be well suited to this role would be coal gasification hydrogen production with CCS, underground buffer storage of hydrogen and independent gas turbine power generation. The gasification hydrogen production and CO₂ capture and storage equipment could operate at full load and only the power plants would need to operate flexibly and at low load, which would result in substantial practical and economic advantages. This paper analyses the performances and costs of such plants in scenarios with various amounts of wind generation, based on data for power demand and wind energy variability in the UK. In a scenario with 35% wind generation, overall emissions of CO₂ could be reduced by 98–99%. The cost of abating CO₂ emissions from the non-wind residual generation using the technique proposed in this paper would be less than 40% of the cost of using coal-fired power plants with integrated CCS.     

碳达峰碳中和目标下可再生能源产业财税金融支持政策研究

能源作为经济社会发展的重要物质基础,也是碳排放的主要来源,推动能源结构调整、大力发展可再生能源产业是实现碳达峰碳中和目标的必然要求。为了促进可再生能源产业发展,国家实施了一系列财税宏观调控政策。本文在梳理政策现状的基础上,对存在的问题进行了识别,包括弃风弃光现象影响财政资金使用效益、可再生能源电价补贴不到位、财税优惠政策形式相对单一、优惠政策执行的配套机制不足等。从建立、完善可再生能源电力消纳保障机制,多种渠道解决可再生能源补贴缺口问题,进一步完善税收优惠政策,适时优化调整财政支持政策,与其他政策协同发挥作用等方面提出了政策优化建议。     

居民生活用电碳排放交易机制研究

个人排放交易被认为可以促进居民参与碳减排,但是因其减排收益难以覆盖高昂的建立和运行成本,降低了公众接受度。本文提出除了考虑碳减排的收益外,更需要关注个人排放交易机制的教育价值、形成正确的激励以及鼓励创新的价值,并提出可以基于当前国内多地实行的阶梯电价制度,利用电力系统现有的用户网络和账户系统,建立居民生活用电碳排放交易机制,以降低成本并实现上述价值。在此基础上,就居民生活用电碳排放交易机制的配额设定与分配、配额交易以及清缴问题做了细致的分析,并提出绿色电力作为补充电力可以免费获得碳配额以促进绿色消费。同时,比较分析了在居民生活用电交易机制和阶梯电价制度下,不同居民家庭以及电力公司的用电成本(收益),指出了其在形成正确的激励方面的作用。最后指出在条件成熟的情况下,居民生活用电碳排放交易机制可以扩展到居民的其他能源消费领域,以实现更为全面的个人排放交易。     

碳排放权配额管理体系的比较和借鉴

在地方性试点的基础上,我国已在电力行业启动全国性碳排放权交易市场建设。配额管理不仅直接影响参与者的经济利益,还决定着碳排放权交易机制能否成功建立和持续运行。从配额总量设定、地区和企业层面的配额分配、配额的调控和灵活管理机制等角度总结比较了各国碳排放权配额管理制度设计的经验教训,并从五个方面提出了对我国全国性碳交易市场建设的启示。     

Climate targets and comprehensive greenhouse gas emissions trading

In June 1992 a Framework on Climate Change Convention was signed in Rio de Janeiro, calling for the control of greenhouse gases, notably in the industrialized countries. Its formulation allows for joint implementation of measures to reach emission targets for greenhouse gases. Such joint implementation covering all greenhouse gases could form the first step towards a system of comprehensive emissions trading. This paper addresses both advantages and disadvantages of comprehensive emissions trading across different gases, sinks and sources. It concludes that in addition to carbon dioxide from fossil fuels, the inclusion of biotic carbon emissions and selected sources of methane is attractive from both the economic and environmental viewpoint. The uncertainties associated with emissions can be overcome by requiring a thorough review of trade proposals by a broad-based international supervisory body, utilizing a consistent methodology such as that being developed by the Intergovernmental Panel on Climate Change (IPCC). Finally, the paper addresses the central objective of the Climate Convention, which implicity sets a limit to greenhouse gases emissions and thus provides a guideline for the total amount of permits that may be made available in a tradeable permit system.     

A novel process integration,optimization and design approach for large-scale implementation of oxy-fired coal power plants with CO2 capture

The widespread use of fossil fuels within the current energy infrastructure is considered as the largest source of anthropogenic emissions of carbon dioxide, which is largely blamed for global warming and climate change. At the current state of development, the risks and costs of non-fossil energy alternatives, such as nuclear, biomass, solar, and wind energy, are so high that they cannot replace the entire share of fossil fuels in the near future timeframe. Additionally, any rapid change towards non-fossil energy sources, even if possible, would result in large disruptions to the existing energy supply infrastructure. As an alternative, the existing and new fossil fuel-based plants can be modified or designed to be either “capture” or “capture-ready” plants in order to reduce their emission intensity through the capture and permanent storage of carbon dioxide in geological formations. This would give the coal-fired power generation units the option to sustain their operations for longer time, while meeting the stringent environmental regulations on air pollutants and carbon emissions in years to come.Currently, there are three main approaches to capturing CO₂ from the combustion of fossil fuels, namely, pre-combustion capture, post-combustion capture, and oxy-fuel combustion. Among these technology options, oxy-fuel combustion provides an elegant approach to CO₂ capture. In this approach, by replacing air with oxygen in the combustion process, a CO₂-rich flue gas stream is produced that can be readily compressed for pipeline transport and storage. In this paper, we propose a new approach that allows air to be partially used in the oxy-fired coal power plants. In this novel approach, the air can be used to carry the coal from the mills to the boiler (similar to the conventional air-fired coal power plants), while O₂ is added to the secondary recycle flow as well as directly to the combustion zone (if needed). From a practical point of view, this approach eliminates problems with the primary recycle and also lessens concerns about the air leakage into the system. At the same time, it allows the boiler and its back-end piping to operate under slight suction; this avoids the potential danger to the plant operators and equipment due to possible exposure to hot combustion gases, CO₂ and particulates. As well, by integrating oxy-fuel system components and optimizing the overall process over a wide range of operating conditions, an optimum or near-optimum design can be achieved that is both cost-effective and practical for large-scale implementation of oxy-fired coal power plants.     

Improving the dynamic response of frequency and power in a wind integrated power system by optimal design of compensated superconducting magnetic energy storage

The frequency deviation and power fluctuation need to be controlled in a wind-integrated power system (WIPS) for keeping the balance between system power generation and demand, which support the quality and stability of overall power system. The present paper addresses this problem while concerning the integration of intermittent wind power and load disturbance into the WIPS. With this intent, it proposes the compensated superconducting magnetic energy storage (CSMES) system with proportional integral derivative (PID) controller for improving the frequency and power deviation profile. A novel swarm intelligence-based artificial bee colony (ABC) algorithm is used for optimal design of PID-CSMES system. Robustness of the proposed ABC-based PID-CSMES control strategy is tested in WIPS under various disturbance patterns of load and wind power. To demonstrate the improved dynamic response, their simulation results are compared with particle swarm optimization-based PID-CSMES, PID with SMES, and only PID controller technique. The performance indices and transient response characteristics of frequency and power deviation are used to evaluate and compare the accuracy and efficiency of each controller. Stability of various system configurations is analyzed using eigenvalue location. Comparing the results of different controller in WIPS indicates a substantial improvement in the dynamic response of system frequency and power deviations by utilizing the proposed control strategy.     

Health and safety implications of alternative energy technologies. II. Solar

No energy technology is risk free when all aspects of its utilization are taken into account. Every energy technology has some attendant direct and indirect health and safety concerns. Solar technologies examined in this paper are wind, ocean thermal energy gradients, passive, photovoltaic, satellite power systems, low- and high-temperature collectors, and central power stations, as well as tidal power. For many of these technologies, insufficient historical data are available from which to assess the health risks and environmental impacts. However, their similarities to other projects make certain predictions possible. For example, anticipated problems in worker safety in constructing ocean thermal energy conversion systems will be similar to those associated with other large-scale construction projects, like deep-sea oil drilling platforms. Occupational hazards associated with photovoltaic plant operation would be those associated with normal electricity generation, although for workers involved in the actual production of photovoltaic materials, there is some concern for the toxic effects of the materials used, including silicon, cadmium, and gallium arsenide.Satellite power systems have several unique risks. These include the effects of long-term space travel for construction workers, effects on the ozone layer and the attendant risk of skin cancer in the general public, and the as-yet-undetermined effects of long-term, low-level microwave exposure. Hazards may arise from three sources in solar heating and cooling systems: water contamination from corrosion inhibitors, heat transfer fluids, and bactericides; collector over-heating, fires, and out-gassing and handling and disposal of system fluids and wastes. Similar concerns exist for solar thermal power systems. Even passive solar systems may increase indoor exposure levels to various air pollutants and toxic substances, eitherdirectly from the solar system itself or indirectly by trapping released pollutants from furnishings, building materials, and indoor combustion.Operated by Union Carbide Corporation under contract W-7405-eng-26 for the U.S. Department of Energy.     

Risk-based optimal operation of hybrid power system using multiobjective optimization

ABSTRACT

This paper solves an optimal generation scheduling problem of hybrid power system considering the risk factor due to uncertain/intermittent nature of renewable energy resources (RERs) and electric vehicles (EVs). The hybrid power system considered in this work includes thermal generating units, RERs such as wind and solar photovoltaic (PV) units, battery energy storage systems (BESSs) and electric vehicles (EVs). Here, the two objective functions are formulated, i.e., minimization of operating cost and system risk, to develop an optimum scheduling strategy of hybrid power system. The objective of proposed approach is to minimize operating cost and system risk levels simultaneously. The operating cost minimization objective consists of costs due to thermal generators, wind farms, solar PV units, EVs, BESSs, and adjustment cost due to uncertainties in RERs and EVs. In this work, Conditional Value at Risk (CVaR) is considered as the risk index, and it is used to quantify the risk due to intermittent nature of RERs and EVs. The main contribution of this paper lies in its ability to determine the optimal generation schedules by optimizing operating cost and risk. These two objectives are solved by using a multiobjective-based nondominated sorting genetic algorithm-II (NSGA-II) algorithm, and it is used to develop a Pareto optimal front. A best-compromised solution is obtained by using fuzzy min-max approach. The proposed approach has been implemented on modified IEEE 30 bus and practical Indian 75 bus test systems. The obtained results show the best-compromised solution between operating cost and system risk level, and the suitability of CVaR for the management of risk associated with the uncertainties due to RERs and EVs.     

Optimal Design Methods for Hybrid Renewable Energy Systems

Renewable and hybrid energy systems (HESs) are expanding due to environmental concerns of climate change, air pollution, and depleting fossil fuels. Moreover, HESs can be cost effective in comparison with conventional power plants. This article reviews current methods for designing optimal HESs. The survey shows these systems are often developed on a medium scale in remote areas and stand-alone, but there is a global growing interest for larger scale deployments that are grid connected. Examples of HESs are PV–wind–battery and PV–diesel–battery. PV and wind energy sources are the most widely adopted. Diesel and batteries are often used but hydrogen is increasing as a clean energy carrier. The design of an efficient HES is challenging because HES models are nonlinear, non-convex, and composed of mixed-type variables that cannot be solved by traditional optimization methods. Alternatively, two types of approaches are typically used for designing optimal HESs: simulation-based optimization and metaheuristic optimization methods. Simulation-based optimization methods are limited in view of human intervention that makes them tedious, time consuming, and error prone. Metaheuristics are more efficient because they can handle automatically a range of complexities. In particular, multi-objective optimization (MOO) metaheuristics are the most appropriate for optimal HES because HES models involve multiple objectives at the same time such as cost, performance, supply/demand management, grid limitations, and so forth. This article shows that the energy research community has not fully utilized state-of-the-art MOO metaheuristics. More recent MOO metaheuristics could be used such as robust optimization and interactive optimization.     

Optimal sizing and siting of renewable energy resources in distribution systems considering time varying electrical/heating/cooling loads using PSO algorithm

Distributed Generation (DG) sources based on Renewable Energy (RE) can be the fastest growing power resources in distribution systems due to their environmental friendliness and also the limited sources of fossil fuels. In general, the optimal location and size of DG units have profoundly impacted on the system losses in a distribution network. In the present article, the Particle Swarm Optimization (PSO) algorithm is employed to find the optimal location and size of DG units in a distribution system. The optimal location and size of DG units are determined on the basis of a multi-objective strategy as follows: (i) the minimization of network power losses, (ii) the minimization of the total costs of Distributed Energy Resources (DERs), (iii) the improvement of voltage stability, and (iv) the minimization of greenhouse gas emissions. The related distribution system was assumed to be composed of the fuel cells, wind turbines, photovoltaic arrays, and battery storages. The electrical, cooling, and heating loads were also considered in this article. The heating and cooling requirements of the system consist of time varying water heating load, space heating load, and space cooling load. In this study, the waste and fuel cell were used to produce the required heating and cooling loads in the distribution system. In addition, the absorption chiller was used to supply the required space cooling loads. A detailed performance analysis was carried out on 13 bus radial distribution system to demonstrate the effectiveness of the proposed methodology.     

A convective wind resource model for Solar Vortex power generation

ABSTRACT

Climate change has increased the need for clean, nonpolluting energy sources to decrease dependence on fossil fuels. Alternative energy sources, mainly solar and horizontal wind, have been the primary focus for producing clean energy. New technologies are being developed, such as the Solar Vortex (SoV), which was developed at the Georgia Institute of Technology, and relies on a vertical wind resource to generate power. The National Renewable Energy Lab (NREL) has resource models representing solar and horizontal wind resources across the 48 United States. This research developed a vertical wind resource model that is comparable in resolution to NREL’s solar and horizontal wind resource models and uses the model for estimating power output for the SoV. This model complements NREL’s existing resource models and supports the deployment of an additional clean energy generation technology. The model was applied to Mesa, Arizona to find feasible sites for a small-scale vertical wind farm.