11,060 research outputs found

    A goal programming methodology for multiobjective optimization of distributed energy hubs operation

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    This paper addresses the problem of optimal energy flow management in multicarrier energy networks in the presence of interconnected energy hubs. The overall problem is here formalized by a nonlinear constrained multiobjective optimization problem and solved by a goal attainment based methodology. The application of this solution approach allows the analyst to identify the optimal operation state of the distributed energy hubs which ensures an effective and reliable operation of the multicarrier energy network in spite of large variations of load demands and energy prices. Simulation results obtained on the 30 bus IEEE test network are presented and discussed in order to demonstrate the significance and the validity of the proposed method

    Short-term Self-Scheduling of Virtual Energy Hub Plant within Thermal Energy Market

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    Multicarrier energy systems create new challenges as well as opportunities in future energy systems. One of these challenges is the interaction among multiple energy systems and energy hubs in different energy markets. By the advent of the local thermal energy market in many countries, energy hubs' scheduling becomes more prominent. In this article, a new approach to energy hubs' scheduling is offered, called virtual energy hub (VEH). The proposed concept of the energy hub, which is named as the VEH in this article, is referred to as an architecture based on the energy hub concept beside the proposed self-scheduling approach. The VEH is operated based on the different energy carriers and facilities as well as maximizes its revenue by participating in the various local energy markets. The proposed VEH optimizes its revenue from participating in the electrical and thermal energy markets and by examining both local markets. Participation of a player in the energy markets by using the integrated point of view can be reached to a higher benefit and optimal operation of the facilities in comparison with independent energy systems. In a competitive energy market, a VEH optimizes its self-scheduling problem in order to maximize its benefit considering uncertainties related to renewable resources. To handle the problem under uncertainty, a nonprobabilistic information gap method is implemented in this study. The proposed model enables the VEH to pursue two different strategies concerning uncertainties, namely risk-averse strategy and risk-seeker strategy. For effective participation of the renewable-based VEH plant in the local energy market, a compressed air energy storage unit is used as a solution for the volatility of the wind power generation. Finally, the proposed model is applied to a test case, and the numerical results validate the proposed approach

    Attributes of Big Data Analytics for Data-Driven Decision Making in Cyber-Physical Power Systems

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    Big data analytics is a virtually new term in power system terminology. This concept delves into the way a massive volume of data is acquired, processed, analyzed to extract insight from available data. In particular, big data analytics alludes to applications of artificial intelligence, machine learning techniques, data mining techniques, time-series forecasting methods. Decision-makers in power systems have been long plagued by incapability and weakness of classical methods in dealing with large-scale real practical cases due to the existence of thousands or millions of variables, being time-consuming, the requirement of a high computation burden, divergence of results, unjustifiable errors, and poor accuracy of the model. Big data analytics is an ongoing topic, which pinpoints how to extract insights from these large data sets. The extant article has enumerated the applications of big data analytics in future power systems through several layers from grid-scale to local-scale. Big data analytics has many applications in the areas of smart grid implementation, electricity markets, execution of collaborative operation schemes, enhancement of microgrid operation autonomy, management of electric vehicle operations in smart grids, active distribution network control, district hub system management, multi-agent energy systems, electricity theft detection, stability and security assessment by PMUs, and better exploitation of renewable energy sources. The employment of big data analytics entails some prerequisites, such as the proliferation of IoT-enabled devices, easily-accessible cloud space, blockchain, etc. This paper has comprehensively conducted an extensive review of the applications of big data analytics along with the prevailing challenges and solutions

    Assessing the role of variable renewables in energy transition: methodologies and tools

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    Due to the environmental impacts brought by current energy schemes, the energy transition, a new paradigm-shift from fossil fuels to renewable energy, has been widely accepted and is being realized through collective international and local efforts. Electricity, as the most direct and effective use of renewable energy sources (RES), plays a key role in the energy transition. In this paper, we first discuss a viable pathway to energy transition through the electricity triangle, highlighting the role of RES in electricity generation. Further, we propose methodologies for the planning of wind and solar PV, as well as how to address their uncertainty in generation expansion problems. Finally, by using a web-based tool, “RES-PLAT” 1 , we demonstrate the scheme in a case study of the North Africa, which evaluates the impacts and benefits of a large-scale RES expansion

    Renewable electricity generation and transmission network developments in light of public opposition: Insights from Ireland. ESRI Working Paper No. 653 March 2020

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    This paper analyses how people’s attitudes towards onshore wind power and overhead transmission lines affect the costoptimal development of electricity generation mixes, under a high renewable energy policy. For that purpose, we use a power systems generation and transmission expansion planning model, combined with information on public attitudes towards energy infrastructure on the island of Ireland. Overall, households have a positive attitude towards onshore wind power but their willingness to accept wind farms near their homes tends to be low. Opposition to overhead transmission lines is even greater. This can lead to a substantial increase in the costs of expanding the power system. In the Irish case, costs escalate by more than 4.3% when public opposition is factored into the constrained optimisation of power generation and grid expansion planning across the island. This is mainly driven by the compounded effects of higher capacity investments in more expensive technologies such as offshore wind and solar photovoltaic to compensate for lower levels of onshore wind generation and grid reinforcements. The results also reveal the effect of public opposition on the value of onshore wind, via shadow prices. The higher the level of public opposition, the higher the shadow value of onshore wind. And, this starkly differs across regions: regions with more wind resource or closest to major demand centres have the highest shadow prices. The shadow costs can guide policy makers when designing incentive mechanisms to garner public support for onshore wind installations

    Combined Operational Planning of Natural Gas and Electric Power Systems: State of the Art

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    The growing installation and utilization of natural gas fired power plants (NGFPPs) over the last two decades has lead to increasing interactions between electricity and natural gas (NG) sectors. From 1990 to 2005, the worldwide share of NGFPPs in the power generation mix has almost doubled, from around 10% to nearly 19%; reaching in 2007, for instance, the 54% in Argentina, the 42% in Italy, the 40% in USA, and the 32% in UK (IEA, 2007; IEA, 2009a). The installation of NGFPPs has been driven by technical, economic and environmental reasons. The high thermal efficiency of combined-cycle gas turbine (CCGT) power plants and combined heat and power (CHP) units, their relatively low investment costs, short construction lead time and the prevailing low natural gas prices until 2004 have made NGFPPs more attractive than traditional coal, oil and nuclear power plants, particularly in liberalized electricity markets. Additionally, burning NG has a smaller environmental footprint and a lower carbon emission than any other fossil fuel. Under the light of all conditions previously described, there is a strong and rising interdependency between NG and electricity sectors. In this context, it is essential to include NG system models in electric power systems operation and planning. On the other hand, NG system operation and planning require, as input data, the NG demands of each NGFPPs, which accurately values can only be obtained from the electric power systems dispatch. Therefore, several approaches that address the integrated modeling of electric power and NG systems have been presented. These new approaches contrast with the current models in which both systems are considered in a decoupled manner.Fil: Rubio Barros, Ricardo German. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan; Argentina. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Energía Eléctrica; ArgentinaFil: Ojeda Esteybar, Diego Mauricio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan; Argentina. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Energía Eléctrica; ArgentinaFil: Año, Osvaldo. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Energía Eléctrica; ArgentinaFil: Vargas, Alberto. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Energía Eléctrica; Argentin

    Risk-Based Optimal Operation of Coordinated Natural Gas and Reconfigurable Electrical Networks with Integrated Energy Hubs

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    Abstract This paper elaborates on optimal scheduling of coordinated power and natural gas (NG) networks in the presence of interconnected energy hubs considering reconfiguration as a flexibility source. With regard to the energy hub system consisting of several generation units, storage and conversion technologies, as well as natural gas‐fired units, the high interdependency between gas and electricity carriers should be captured. The hourly reconfiguration capability is developed for the first time in a multi‐energy system to enhance the optimal power dispatch and gas consumption pattern. The realistic interdependency of electrical and NG grids is investigated by employing the steady‐state Weymouth equation and AC‐power flow model for power and gas networks, respectively. Furthermore, to handle the risk associated with strong uncertainty of wind power, load, and real‐time power price, the conditional value at risk approach is employed. The proposed model is implemented on the integrated test system and simulation results are presented for different cases. The impact of the risk aversion level on operating cost and optimal scheduling of controllable units is examined. Numerical results demonstrate that reconfigurable capability reduces the operational cost up to 7.82%
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