Optimal dynamic expansion planning of distribution systems considering non-renewable distributed generation using a new heuristic double-stage optimization solution approach

Ahmadigorji, Masoud; Amjady, Nima

doi:10.1016/j.apenergy.2015.07.042

Cited by 36 publications

(5 citation statements)

References 34 publications

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“…Consulting the models proposed in [8][9][10], a modified model which possesses following characteristics is built in this section: (i) planning horizon consists of multiple stages, (ii) the sequential varying loads are discretised into different load levels, (iii) installation of DGs, SVGs, and expansion of distribution network are jointly determined, and (iv) constraints are formulated to impose network radiation and connectivity. In addition, SOC relaxation method is used to substitute quadratic constraints and transform the MINLP problem into a convex problem.…”

Section: Problem Formulation: Misocp Modelmentioning

confidence: 99%

“…Latterly, multistage coordinated planning considering multiple alternatives has become a research focus. The cooptimisation model has better performance in finding planning optimisation [8]. According to relevant works on the multistage co-optimisation model, decisions on network expansion as well as siting and sizing of DGs are usually formulated as variables.…”

Section: Introductionmentioning

confidence: 99%

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Decomposition method for coordinated planning of distributed generation and distribution network

Liu

et al. 2018

IET Generation, Transmission & Distribution

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Section: Problem Formulation: Misocp Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Decomposition method for coordinated planning of distributed generation and distribution network

Liu

et al. 2018

IET Generation, Transmission & Distribution

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“…5 minute resolution) "real-time" electricity market, as well as reserve and regulation markets. Typically, proprietary software tools are used to solve the UCP for these markets; however, extensive research into methodologies and solutions has been conducted in academia, as well [24], and other optimization approaches are being developed [25][26][27]. The increased interest in integrating large capacities of variable renewable energy into the power system has led to efforts to account for uncertainty in the UCP by incorporating stochastic optimization using Lagrangian relaxation [28] and adaptive modeling techniques [29].…”

Section: Approach Overviewmentioning

confidence: 99%

“…Following initial analyses using the model described in Eqs. (25)(26)(27)(28)(29), some exceptions to the NYISO transmission limits were made: Flows on the G-H, H-I and I-J were constrained to positive flow-only. Otherwise, the linear program occasionally selected a reverse flow condition on these lines.…”

Section: Transmission Constraints -Linear Program Formulationmentioning

confidence: 99%

Modeling wind power curtailment with increased capacity in a regional electricity grid supplying a dense urban demand

Waite

Modi

2016

Applied Energy

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Many US states have targets for vastly expanding electricity generation from renewable resources. As installed wind capacity increases, several factors can lead to the curtailment of potential wind-generated electricity. Reliably estimating wind power outputs remains a challenge given the dearth of available hub height-altitude wind speed data and measured outputs from newer turbines. A methodology to make such estimates with large increases in wind capacity is described. A regional wind power model, including subroutines for evaluating Statewide grid constraints, and a linear program to solve the model were developed to assess capacity factors and curtailments with deep penetration of wind power into an existing grid under several constrained scenarios implied by demand, baseload generation and transmission. Actual zonal demand and interzonal transmission limits were used for the New York State electricity grid, which has significant potential for wind power mostly distant from the concentrated electricity demand in and around New York City. 0.015% of the total number of 5-minute demand values over the 6-year analysis period. As such, any assumptions required to complete the zonal time series are not expected to have a significant impact on the results of the analysis.

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“…In this paper, the O&M costs are equivalent to the cost for per unit of electricity generated (i.e., $/kWh) as [22] and [23] did.…”

Section: Total Dg Costmentioning

confidence: 99%

Crisscross Optimization Algorithm and Monte Carlo Simulation for Solving Optimal Distributed Generation Allocation Problem

Peng

Zheng

et al. 2015

Energies

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Distributed generation (DG) systems are integral parts in future distribution networks. In this paper, a novel approach integrating crisscross optimization algorithm and Monte Carlo simulation (CSO-MCS) is implemented to solve the optimal DG allocation (ODGA) problem. The feature of applying CSO to address the ODGA problem lies in three interacting operators, namely horizontal crossover, vertical crossover and competitive operator. The horizontal crossover can search new solutions in a hypercube space with a larger probability while in the periphery of each hypercube with a decreasing probability. The vertical crossover can effectively facilitate those stagnant dimensions of a population to escape from premature convergence. The competitive operator allows the crisscross search to always maintain in a historical best position to quicken the converge rate. It is the combination of the double search strategies and competitive mechanism that enables CSO significant advantage in convergence speed and accuracy. Moreover, to deal with system uncertainties such as the output power of wind turbine and photovoltaic generators, an MCS-based method is adopted to solve the probabilistic power flow. The effectiveness of the CSO-MCS method is validated on the typical 33-bus and 69-bus test system, and results substantiate the suitability of CSO-MCS for multi-objective ODGA problem.

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Optimal dynamic expansion planning of distribution systems considering non-renewable distributed generation using a new heuristic double-stage optimization solution approach

Cited by 36 publications

References 34 publications

Decomposition method for coordinated planning of distributed generation and distribution network

Decomposition method for coordinated planning of distributed generation and distribution network

Modeling wind power curtailment with increased capacity in a regional electricity grid supplying a dense urban demand

Crisscross Optimization Algorithm and Monte Carlo Simulation for Solving Optimal Distributed Generation Allocation Problem

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