scholarly journals A Risk-Averse Approach for Distribution Grid Expansion Planning

Energies ◽  
2021 ◽  
Vol 14 (24) ◽  
pp. 8482
Author(s):  
Alexandre Moreira ◽  
Miguel Heleno ◽  
Alan Valenzuela
Keyword(s):  
Convex Combination ◽  
Distribution Networks ◽  
Expected Value ◽  
Power Grids ◽  
Test Case ◽  
Distribution Grid ◽  
Storage Devices ◽  
Expansion Planning ◽  
Utility System ◽  
Key Factor

Recent episodes of natural disasters have challenged the resilience of power grids. Adequate distribution grid planning that properly captures the risk aversion of the utility system planner is a key factor to increase the flexibility of distribution networks to circumvent these events. In this paper, we propose a methodology to determine the optimal portfolio of investments in lines and storage devices in order to minimize a convex combination between expected value and CVaR of operational costs, including energy not served, while taking into account the multistage nature of the energy storage management within this context. While the expected value of energy not served has been traditionally employed to tackle routine failures, we also minimize the CVaR of energy not served to address high-impact, low-probability (HILP) events. We illustrate the performance of the proposed methodology with a 54-Bus system test case.

scholarly journals Review of Voltage and Reactive Power Control Algorithms in Electrical Distribution Networks

Energies ◽  
2019 ◽  
Vol 13 (1) ◽  
pp. 58 ◽  
Author(s):  
Daiva Stanelyte ◽  
Virginijus Radziukynas
Keyword(s):  
Smart Grids ◽  
Reactive Power ◽  
Low Voltage ◽  
Distribution Networks ◽  
Power Grids ◽  
Renewable Energy Resources ◽  
Distribution Grid ◽  
Harmonic Compensation ◽  
Distributed Power Generation ◽  
Control Devices

The traditional unidirectional, passive distribution power grids are rapidly developing into bidirectional, interactive, multi-coordinated smart grids that cover distributed power generation along with advanced information communications and electronic power technologies. To better integrate the use of renewable energy resources into the grid, to improve the voltage stability of distribution grids, to improve the grid protection and to reduce harmonics, one needs to select and control devices with adjustable reactive power (capacitor batteries, transformers, and reactors) and provide certain solutions so that the photovoltaic (PV) converters maintain due to voltage. Conventional compensation methods are no longer appropriate, thus developing measures are necessary that would ensure local reactive and harmonic compensation in case an energy quality problem happens in the low voltage distribution grid. Compared to the centralized methods, artificial intelligence (heuristic) methods are able to distribute computing and communication tasks among control devices.

scholarly journals Gaussian Copula Methodology to Model Photovoltaic Generation Uncertainty Correlation in Power Distribution Networks

Energies ◽  
2021 ◽  
Vol 14 (9) ◽  
pp. 2349
Author(s):  
Harshavardhan Palahalli ◽  
Paolo Maffezzoni ◽  
Giambattista Gruosso
Keyword(s):  
Power Distribution ◽  
Distribution System ◽  
Low Voltage ◽  
Distribution Networks ◽  
Load Flow ◽  
Power Grids ◽  
Gaussian Copula ◽  
Expansion Planning ◽  
Probabilistic Load Flow ◽  
Photovoltaic Generators

Deterministic load flow analyses of power grids do not include the uncertain factors that affect the network elements; hence, their predictions can be very unreliable for distribution system operators and for the decision makers who deal with the expansion planning of the power network. Adding uncertain probability parameters in the deterministic load flow is vital to capture the wide variability of the currents and voltages. This is achieved by probabilistic load flow studies. Photovoltaic systems represent a remarkable source of uncertainty in the distribution network. In this study, we used a Gaussian copula to model the uncertainty in correlated photovoltaic generators. Correlations among photovoltaic generators were also included by exploiting the Gaussian copula technique. The large sets of samples generated with a statistical method (Gaussian copula) were used as the inputs for Monte Carlo simulations. The proposed methodologies were tested on two different networks, i.e., the 13 node IEEE test feeder and the non-synthetic European low voltage test network. Node voltage uncertainty and network health, measured by the percentage voltage unbalance factor, were investigated. The importance of including correlations among photovoltaic generators is discussed.

scholarly journals A Two-layer Multistage Expansion Planning Method for Adaptability Enhancement of Distribution Networks

2021 ◽  
Vol 645 ◽  
pp. 012080
Author(s):  
Liang Feng ◽  
Yichao Dong ◽  
Shouxiang Wang ◽  
Qingzhi Jian ◽  
Long Zhao ◽  
...  
Keyword(s):  
Distribution Networks ◽  
Planning Method ◽  
Expansion Planning

scholarly journals To study the voltage stability limits of distributed generation using induction machine in distribution networks

2013 ◽  
Vol 16 (2) ◽  
pp. 43-53
Author(s):  
Chuong Trong Trinh ◽  
Anh Viet Truong ◽  
Tu Phan Vu
Keyword(s):  
Distributed Generation ◽  
Power Distribution ◽  
Power Flow ◽  
Voltage Stability ◽  
Reactive Power ◽  
Induction Machine ◽  
Distribution Networks ◽  
Distribution Grid ◽  
Asynchronous Machine ◽  
Asynchronous Machines

There are now a lot of distributed generation (DG) using asynchronous machines are connected to power distribution grid. These machines do not usually generate reactive power, even consume reactive power, so they generally affect the voltage stability of whole power grid, and can cause instability in itself it is no longer balanced by the torque to work. In this paper, we investigate the voltage stability problem of the asynchronous machine of wind turbines used in power distribution networks. From the static model of the asynchronous machine, this paper will apply the pragmatic criteria to analysis the voltage stability of the asynchronous machine based on the results of the power flow in power distribution network.

scholarly journals Coordinated Market Clearing for Combined Thermal and Electric Distribution Grid Operation

2020 ◽  
Author(s):  
Sebastian Troitzsch ◽  
Kai Zhang ◽  
Tobias Massier ◽  
Thomas Hamacher
Keyword(s):  
District Heating ◽  
Test Case ◽  
Distribution Grid ◽  
Electric Grid ◽  
Market Clearing ◽  
Alternating Direction ◽  
Locational Marginal Price ◽  
Flexible Loads ◽  
Electric Distribution ◽  
Grid Operation

To economically dispatch distributed energy resources (DERs) while addressing operational concerns of the electric grid, distribution locational marginal price (DLMP)-based market frameworks have been formulated for the electric distribution grid. This paper proposes to extend this methodology to thermal grids, i.e. district heating or cooling systems, and presents a market-clearing mechanism based on the alternating direction method of multipliers (ADMM) for coordinating between thermal grid, electric grid and DER operation. The ability of the proposed mechanism to achieve the market equilibrium for a combined thermal and electric grid is demonstrated for a test case with 22 flexible loads (FLs).

Flexibility and Real Options Analysis in Design for Long-Term Generation Expansion Planning of Power Grids

2017 ◽  
Author(s):  
Muhammad Rahmat ◽  
Aakil Mohammad Caunhye ◽  
Michel-Alexandre Cardin
Keyword(s):  
Real Options ◽  
Decision Rule ◽  
Power Grids ◽  
Programming Approach ◽  
Generation Expansion Planning ◽  
Expansion Planning ◽  
Generation Expansion ◽  
Time Period ◽  
Capacity Uncertainty ◽  
Supply Capacity

In recent years, the electricity industry has seen a drive towards the integration of renewable and environmentally friendly generation resources to power grids. These resources have highly variable availabilities. This work proposes a stochastic programming approach to optimize generation expansion planning (GEP) under generator supply capacity uncertainty. To better capture upside opportunities and reduce exposure to downside risks, flexibility is added to the GEP problem through real options on generator addition, which are to be exercised after uncertainty realizations. In addition, with the end goal of providing decision makers with easy-to-use guidelines, a conditional-go decision rule, akin to an if-then-else statement in programming, is proposed whereby the decision maker is provided with a threshold of excess total generator capacity from the previous time period, below which a predetermined generator addition plan (the option) is exercised. The proposed methodology and its decision rule are implemented in a real-world study of Midwest U.S. Comparisons are made to quantify the value of flexibility and to showcase the usefulness of the proposed approach.

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