Scheduling Model for Renewable Energy Sources Integration in an Insular Power System

Osório, Gerardo J.; Shafie‐khah, Miadreza; Lujano-Rojas, Juan M.; Catalão, João P.S.

doi:10.3390/en11010144

Cited by 16 publications

(14 citation statements)

References 37 publications

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“…Existing studies on the flexibility problem can be categorized into two types: those that discuss the application of flexible resources, such as energy storage systems, and demand-side resources (DSRs) to mitigate the variability and uncertainty [3,[17][18][19][20]; and those that investigate operational methods such as the unit commitment (UC) and power flow to effectively respond to increased variability and uncertainty [21][22][23][24][25][26][27][28]. In the latter category, the effects of variability and uncertainty are restricted using ramp-up/down constraints (collectively known as ramp constraints) in stochastic and deterministic UC formulations [21][22][23][24][25][26]. However, ramp constraints merely guarantee a feasible solution; adequate or optimal flexibility and the trade-off between the available amount of flexible resources and the operating cost are not taken into account.…”

Section: Introductionmentioning

confidence: 99%

Analyzing the Impact of Variability and Uncertainty on Power System Flexibility

Min

2019

Applied Sciences

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Featured Application: This study presents a method for separating the variability and uncertainty in a power system, and determining which is more influential in terms of flexibility, based on the flexibility index, named the ramping capability shortage probability (RSP). A process of scenario generation and sensitivity analysis is also proposed, and applied to a modified IEEE-RTS-96. The proposed method can evaluate the individual effect of variability and uncertainty and effectively provide the system operator with information that will enable more efficient operation and planning of a power system. Abstract:This study investigates the impact of variability and uncertainty on the flexibility of a power system. The variability and uncertainty make it harder to maintain the balance between load and generation. However, most existing studies on flexibility evaluation have not distinguished between the effects of variability and uncertainty. The countermeasures to address variability and uncertainty differ; thus, applying strategies individually tailored to variability and uncertainty is helpful for more efficient operation and planning of a power system. The first contribution of this study is in separating the variability and uncertainty, and determining which is more influential in terms of flexibility in specific system situations. A flexibility index, named the ramping capability shortage probability (RSP), is used to quantify the extent to which the variability and uncertainty affect the flexibility. The second contribution is to generate various scenarios for variability and uncertainty based on a modified IEEE-RTS-96, to evaluate the flexibility. The penetration level of renewable energy resources is kept the same in each scenario. The results of a sensitivity analysis show that variability is more effective than uncertainty for high and medium net loads.

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Section: Introductionmentioning

confidence: 99%

Analyzing the Impact of Variability and Uncertainty on Power System Flexibility

Min

2019

Applied Sciences

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“…The solutions to this problem have been explored for years in various areas. Among them, the development and integration of generators based on renewable resources (RRs) [3] is one of the most promising strategies. These types of generators have some drawbacks, mainly related to their cost and the uncertainty of the generation, but they present a sustainable alternative for the development of electricity grids or the reinforcement of existing networks [4].…”

Section: Introductionmentioning

confidence: 99%

Optimal Generation Scheduling with Dynamic Profiles for the Sustainable Development of Electricity Grids

et al. 2019

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The integration of renewable generation in electricity networks is one of the most widespread strategies to improve sustainability and to deal with the energy supply problem. Typically, the reinforcement of the generation fleet of an existing network requires the assessment and minimization of the installation and operating costs of all the energy resources in the network. Such analyses are usually conducted using peak demand and generation data. This paper proposes a method to optimize the location and size of different types of generation resources in a network, taking into account the typical evolution of demand and generation. The importance of considering this evolution is analyzed and the methodology is applied to two standard networks, namely the Institute of Electrical and Electronics Engineers (IEEE) 30-bus and the IEEE 118-bus. The proposed algorithm is based on the use of particle swarm optimization (PSO). In addition, the use of an initialization process based on the cross entropy (CE) method to accelerate convergence in problems of high computational cost is explored. The results of the case studies highlight the importance of considering dynamic demand and generation profiles to reach an effective integration of renewable resources (RRs) towards a sustainable development of electric systems.Sustainability 2019, 11, 7111 2 of 26 design stage, then the investment plans obtained could be inadequate. The sustainable development of electrical power systems by installing and integrating renewable generators also improves the diversity of energy supply and enables the objectives for addressing climate change approved by most countries to be met [5]. However, despite the aforementioned variable and unpredictable availability of these resources, the methods used to optimize the design of the generation of a network are generally not prepared to be effective and accurate under these conditions [6].The optimal design of a power grid is a problem of great complexity that involves combining the appropriate selection of topology with the optimal location, size, and operating strategy of generators. Each of these objectives constitutes a complex problem. The optimal design of the generation system in a power grid (location and size of generators) is a non-linear optimization problem that has received considerable attention in recent years. It can be considered a problem with an economic objective (to minimize the cost of generation), like in [7], or as a multi-objective problem, if other criteria are added, such as optimizing voltages in buses or reducing CO 2 emissions, for example [8]. The combinatorial nature of the problem and the mathematical difficulty involved in its solution has often led to evolutionary optimization algorithms, such as particle swarm optimization (PSO), like in [9], or heuristics (genetic algorithms, for example), like in [10][11][12].The literature contains many methods for the optimal sizing and placement of generation units in electrical networks, taking into account peak demand and ge...

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“…The role of integration between individual energy sources is emphasized in Reference [27] on the example of São Miquel in the Azores. The considerations concern the heat and power plant, two geothermal power plants, a hydroelectric plant, a wind farm, and a conventional source.…”

Section: Introductionmentioning

confidence: 99%

“…4. At present, fast development of electro-mobility is observed [27,59,64,65]. The "vehicle to grid" trends (the system which enables the bi-directional electricity flow between an electric vehicle and the grid) can also be implemented on El Hierro, where local authorities prepare the replacement of 6400 cars with electric vehicles, as well as 35 charging stations [60].…”

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El Hierro Renewable Energy Hybrid System: A Tough Compromise

Frydrychowicz-Jastrzębska

2018

Energies

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The Gorona del Viento project was characterized in this article, concerning its implementation, as well as several years of exploitation in an isolated location, namely on the El Hierro island. The hybrid system includes a wind farm and a pumped storage power plant, which acts as an energy storage, and all are equipped with a control system. The planned strategy assumed a configuration based on 100% wind energy supply. However, the system does not guarantee the anticipated effectiveness. The problems with the lack of energy self-sufficiency are partly the result of changes in the project made already during construction, in particular because of the mismatch of the water reservoir's capacity and the wind turbines' energy production efficiency. This results in the necessity to limit the wind farm capacity to ensure grid stability and hence requires supplementation of energy from the diesel generator. The author compared the object to analogical ones which employ different technological solutions and presented potential suggestions as to improve the existing state and achieve the reliability of the system's operation.Reference [7] assessed the isolated electricity network and goals proposed in the Canary Islands energy plan (PECAN), taking into account the average cost and risk associated with different alternatives to electricity generation. In order to increase efficiency (even by 30%), authors additionally suggest the use of natural gas. Current and future (until 2050) action plan in this area was presented in Reference [8]. Reference [9], on the other hand, presented the program of introducing RES in the Azores from 2007 to 2018. The smallest of the archipelago islands, Corvo, is planned to be powered exclusively from RES [4,9]. Reference [10] concerned the Greek islands of Crete, Kythnos, Ikaria, and Agios Efstrations. An interesting solution was applied on Ikaria (thermal, PV (photovoltaic), wind, and hydro with storage in two locations). The island of Agios Efstrations is planned to achieve 100% energy self-sufficiency only from RES. In Reference [11], the importance of assessing the technical and economic feasibility of isolated wind energy systems is emphasized.Because of the instability of the RES (the availability of their potential depends on many factors), a reserve conventional source and a storage are often introduced into the system [4].Reference [12] proposed a novel method of optimizing the efficiency of battery energy storage systems. Four optimal objective functions have been taken into account, such as minimum energy storage capacity, minimum load dump, the maximum lowest deflection frequency, and minimum disruption duration indicator.An overview of possible solutions for electricity storage is presented in References [13-18] including pumped hydro storage, flywheel, superconducting magnetic energy storage (SMES), supercapacitors, battery energy storage system (BESS), pumped heat electrical storage (PHES), and compressed air energy storage (CAES), whereas in References [13,14,[16][17][18], the ...

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Scheduling Model for Renewable Energy Sources Integration in an Insular Power System

Cited by 16 publications

References 37 publications

Analyzing the Impact of Variability and Uncertainty on Power System Flexibility

Analyzing the Impact of Variability and Uncertainty on Power System Flexibility

Optimal Generation Scheduling with Dynamic Profiles for the Sustainable Development of Electricity Grids

El Hierro Renewable Energy Hybrid System: A Tough Compromise

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