scholarly journals On the Value of Community Association for Microgrid Development: Learnings from Multiple Deterministic and Stochastic Planning Designs

2021 ◽  
Vol 11 (14) ◽  
pp. 6257
Author(s):  
Juan David Mina-Casaran ◽  
Diego Fernando Echeverry ◽  
Carlos Arturo Lozano ◽  
Alejandro Navarro-Espinosa
Keyword(s):  
Power Systems ◽  
Economies Of Scale ◽  
Power Grid ◽  
Renewable Energy Sources ◽  
Minimum Cost ◽  
Planning Problem ◽  
Planning Models ◽  
Stochastic Planning ◽  
Deterministic Solution ◽  
Potential Benefits

The reliability of the power grid is a constant problem faced by those who operate, plan and study power systems. An alternative approach to this problem, and others related to the integration of renewable energy sources, is the microgrid. This research seeks to quantify the potential benefits of urban community microgrids, based on the development of planning models with deterministic and stochastic optimization approaches. The models ensure that supply meets demand whilst assuring the minimum cost of investment and operation. To verify their effectiveness, the planning of hundreds of microgrids was set in the city of Santiago de Chile. The most important results highlight the value of community association, such as: a reduction in investment cost of up to 35%, when community microgrids are planned with a desired level of reliability, compared to single residential household microgrids. This reduction is due to the diversity of energy consumption, which can represent around 20%, on average, of cost reduction, and to the Economies of Scale (EoS) present in the aggregation microgrid asset capacity, which can represent close to 15% of the additional reduction in investment costs. The stochastic planning approach also ensures that a community can prepare for different fault scenarios in the power grid. Furthermore, it was found that for approximately 90% of the planned microgrids with reliability requirements, the deterministic solution for the worst three fault scenarios is equivalent to the solution of the stochastic planning problem.

scholarly journals Voltage Stability of Power Systems with Renewable-Energy Inverter-Based Generators: A Review

Electronics ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 115
Author(s):  
Nasser Hosseinzadeh ◽  
Asma Aziz ◽  
Apel Mahmud ◽  
Ameen Gargoom ◽  
Mahbub Rabbani
Keyword(s):  
Renewable Energy ◽  
Power Systems ◽  
Voltage Stability ◽  
Reactive Power ◽  
Power Grid ◽  
Renewable Energy Sources ◽  
Electrical Power ◽  
System Stability ◽  
Special Issue ◽  
Synchronous Generators

The main purpose of developing microgrids (MGs) is to facilitate the integration of renewable energy sources (RESs) into the power grid. RESs are normally connected to the grid via power electronic inverters. As various types of RESs are increasingly being connected to the electrical power grid, power systems of the near future will have more inverter-based generators (IBGs) instead of synchronous machines. Since IBGs have significant differences in their characteristics compared to synchronous generators (SGs), particularly concerning their inertia and capability to provide reactive power, their impacts on the system dynamics are different compared to SGs. In particular, system stability analysis will require new approaches. As such, research is currently being conducted on the stability of power systems with the inclusion of IBGs. This review article is intended to be a preface to the Special Issue on Voltage Stability of Microgrids in Power Systems. It presents a comprehensive review of the literature on voltage stability of power systems with a relatively high percentage of IBGs in the generation mix of the system. As the research is developing rapidly in this field, it is understood that by the time that this article is published, and further in the future, there will be many more new developments in this area. Certainly, other articles in this special issue will highlight some other important aspects of the voltage stability of microgrids.

scholarly journals On-Site Engineering Test of Active Support Control for the PV Station and Wind Farm in the AC-DC Hybrid Power Grid under Extreme Fault Conditions

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Xiao-ling Su ◽  
Lai-jun Chen ◽  
Jun Yang ◽  
Zhengxi Li ◽  
Peng Zhou ◽  
...  
Keyword(s):  
Power Systems ◽  
Power System ◽  
Control Strategy ◽  
Wind Farm ◽  
Power Grid ◽  
Renewable Energy Sources ◽  
Wind Farms ◽  
System Stability ◽  
Test Results ◽  
Hybrid Power

Power systems have developed significantly because of the increasing share of renewable energy sources (RESs). Despite the advantages, they also bring inevitable challenges to power system stability, especially under extreme fault conditions. This paper presents a practical active support control strategy for RESs to support the power grid under extreme fault conditions. The proof process is taken in an AC-DC hybrid power grid integrated with large capacity of PV stations and wind farms. The on-site engineering test results reflect that RESs bring potential risks in the AC-DC hybrid power grid operation and validate the excellent engineering practical features of the proposed control strategy. In addition, test results also reveal predisposing factors of power system instability which are missing in the simulation and fault simulation device-based testing results. They prove the outstanding advantages of on-site engineering tests.

scholarly journals Evolutionary Priority-Based Dynamic Programming for the Adaptive Integration of Intermittent Distributed Energy Resources in Low-Inertia Power Systems

Eng ◽  
2021 ◽  
Vol 2 (4) ◽  
pp. 643-660
Author(s):  
Pavlos Nikolaidis ◽  
Andreas Poullikkas
Keyword(s):  
Dynamic Programming ◽  
Power Systems ◽  
Optimal Power Flow ◽  
Unit Commitment ◽  
Renewable Energy Sources ◽  
Minimum Cost ◽  
Energy Resources ◽  
Distributed Energy Resources ◽  
Distributed Energy ◽  
Priority List

The variability and uncertainty caused by the increased penetrations of renewable energy sources must be properly considered in day-ahead unit commitment, optimal power flow, and even real-time economic dispatch problems. Besides achieving minimum cost, modern generation schedules must satisfy a larger set of different complex constraints. These account for the generation constraints in the presence of renewable generation, network constraints affected by the distributed energy resources, bilateral contracts enclosing independent capacity provision, ancillary power auctions, net-metering and feed-in-tariff prosumers, and corrective security actions in sudden load variations or outage circumstances. In this work, a new method is presented to appropriately enhance the integration of distributed energy resources in low-inertia power grids. Based on optimal unit commitment schedules derived from priority-based dynamic programming, the potential of increasing the renewable capacity was examined, performing simulations for different scenarios. To ameliorate the expensive requirement of computational complexity, this approach aimed at eliminating the increased exploration-exploitation efforts. On the contrary, its promising solution relies on the evolutionary commitment of the next optimum configuration based on priority-list schemes to accommodate the intermittent generation progressively. This is achieved via the collection of mappings that transform many-valued clausal forms into satisfiability equivalent Boolean expressions.

scholarly journals The Application of Molten Salt Energy Storage to Advance the Transition from Coal to Green Energy Power Systems

Energies ◽  
2020 ◽  
Vol 13 (9) ◽  
pp. 2222 ◽  
Author(s):  
Wojciech Kosman ◽  
Andrzej Rusin
Keyword(s):  
Energy Storage ◽  
Power Systems ◽  
Molten Salt ◽  
Power Grid ◽  
Renewable Energy Sources ◽  
Green Energy ◽  
Operating Conditions ◽  
Energy Sources ◽  
Steam Turbines ◽  
Technical Solutions

The paper presents technical solutions for a power grid that undergoes the elimination of a significant number of coal-based power generating units. The purpose of the solutions is to adapt the existing machines with sufficient lifespans to the new operating conditions. In particular these include steam turbines. The steam turbines’ cycles may be extended with energy storage systems based on a molten salt. This allows to increase the flexibility of the power generating units while maintaining the largest possible efficiency of the power generation. The solutions presented here allow to connect the steam turbines cycles to renewable energy sources and reduce the overall number of the units that create the fundamental layer of the power grid. The analysis of the solutions involves numerical modeling. The paper describes the assumptions and the results of the modeling for chosen cases of the modernization. The researched considered a number of options that differed in the investment costs and the resulting performance.

scholarly journals A New Virtual Synchronous Generator Design Based on the SMES System for Frequency Stability of Low-Inertia Power Grids

Energies ◽  
2020 ◽  
Vol 13 (21) ◽  
pp. 5641
Author(s):  
Gaber Magdy ◽  
Abualkasim Bakeer ◽  
Morsy Nour ◽  
Eduard Petlenkov
Keyword(s):  
Energy Storage ◽  
Power Systems ◽  
Power Grid ◽  
Renewable Energy Sources ◽  
Synchronous Generator ◽  
Frequency Stability ◽  
Power Grids ◽  
Renewable Power ◽  
Utility Grid ◽  
Virtual Synchronous Generator

In light of the challenges of integrating more renewable energy sources (RESs) into the utility grid, the virtual synchronous generator (VSG) will become an indispensable configuration of modern power systems. RESs are gradually replacing the conventional synchronous generators that are responsible for supplying the utility grid with the inertia damping properties, thus renewable power grids are more vulnerable to disruption than traditional power grids. Therefore, the VSG is presented to mimic the behavior of a real synchronous generator in the power grid through the virtual rotor concept (i.e., which emulates the properties of inertia and damping) and virtual primary and secondary controls (i.e., which emulate the conventional frequency control loops). However, inadequate imitation of the inertia power owing to the low and short-term power of the energy storage systems (ESSs) may cause system instability and fail dramatically. To overcome this issue, this paper proposes a VSG based on superconducting magnetic energy storage (SMES) technology to emulate the needed inertia power in a short time and thus stabilizing the system frequency at different disturbances. The proposed VSG based on SMES is applied to improve the frequency stability of a real hybrid power grid, Egyptian Power System (EPS), with high renewables penetration levels, nonlinearities, and uncertainties. The performance superiority of the proposed VSG-based SMES is validated by comparing it with the traditional VSG approach based on battery ESSs. The simulation results demonstrated that the proposed VSG based on the SMES system could significantly promote ultra-low-inertia renewable power systems for several contingencies.

scholarly journals Special Issue: “Wind Power Integration into Power Systems: Stability and Control Aspects”

Energies ◽  
2021 ◽  
Vol 14 (12) ◽  
pp. 3680
Author(s):  
Lasantha Meegahapola ◽  
Siqi Bu
Keyword(s):  
Power Systems ◽  
Wind Power ◽  
Renewable Energy Sources ◽  
Power Grids ◽  
Energy Sources ◽  
Low Carbon ◽  
Carbon Neutrality ◽  
Stability And Control ◽  
Wind Power Integration ◽  
And Control

Power network operators are rapidly incorporating wind power generation into their power grids to meet the widely accepted carbon neutrality targets and facilitate the transition from conventional fossil-fuel energy sources to the clean and low-carbon renewable energy sources [...]

scholarly journals Optimum Distribution System Expansion Planning Incorporating DG Based on N-1 Criterion for Sustainable System

2021 ◽  
Vol 13 (12) ◽  
pp. 6708
Author(s):  
Hamza Mubarak ◽  
Nurulafiqah Nadzirah Mansor ◽  
Hazlie Mokhlis ◽  
Mahazani Mohamad ◽  
Hasmaini Mohamad ◽  
...  
Keyword(s):  
Power Systems ◽  
Distribution System ◽  
Industrial Revolution ◽  
Optimal Solution ◽  
Search Space ◽  
Planning Problem ◽  
System Expansion ◽  
Optimum Distribution ◽  
Optimal Sizing ◽  
Expansion Planning

Demand for continuous and reliable power supply has significantly increased, especially in this Industrial Revolution 4.0 era. In this regard, adequate planning of electrical power systems considering persistent load growth, increased integration of distributed generators (DGs), optimal system operation during N-1 contingencies, and compliance to the existing system constraints are paramount. However, these issues need to be parallelly addressed for optimum distribution system planning. Consequently, the planning optimization problem would become more complex due to the various technical and operational constraints as well as the enormous search space. To address these considerations, this paper proposes a strategy to obtain one optimal solution for the distribution system expansion planning by considering N-1 system contingencies for all branches and DG optimal sizing and placement as well as fluctuations in the load profiles. In this work, a hybrid firefly algorithm and particle swarm optimization (FA-PSO) was proposed to determine the optimal solution for the expansion planning problem. The validity of the proposed method was tested on IEEE 33- and 69-bus systems. The results show that incorporating DGs with optimal sizing and location minimizes the investment and power loss cost for the 33-bus system by 42.18% and 14.63%, respectively, and for the 69-system by 31.53% and 12%, respectively. In addition, comparative studies were done with a different model from the literature to verify the robustness of the proposed method.

scholarly journals Predicting AC Optimal Power Flows: Combining Deep Learning and Lagrangian Dual Methods

2020 ◽  
Vol 34 (01) ◽  
pp. 630-637 ◽  
Author(s):  
Ferdinando Fioretto ◽  
Terrence W.K. Mak ◽  
Pascal Van Hentenryck
Keyword(s):  
Deep Learning ◽  
Power Systems ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Large Scale ◽  
Renewable Energy Sources ◽  
Electrical Power ◽  
Practical Applications ◽  
Fundamental Building Block ◽  
Optimal Power

The Optimal Power Flow (OPF) problem is a fundamental building block for the optimization of electrical power systems. It is nonlinear and nonconvex and computes the generator setpoints for power and voltage, given a set of load demands. It is often solved repeatedly under various conditions, either in real-time or in large-scale studies. This need is further exacerbated by the increasing stochasticity of power systems due to renewable energy sources in front and behind the meter. To address these challenges, this paper presents a deep learning approach to the OPF. The learning model exploits the information available in the similar states of the system (which is commonly available in practical applications), as well as a dual Lagrangian method to satisfy the physical and engineering constraints present in the OPF. The proposed model is evaluated on a large collection of realistic medium-sized power systems. The experimental results show that its predictions are highly accurate with average errors as low as 0.2%. Additionally, the proposed approach is shown to improve the accuracy of the widely adopted linear DC approximation by at least two orders of magnitude.

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