Stochastic multi-objective operational planning of smart distribution systems considering demand response programs

Zakariazadeh, Alireza; Jadid, Shahram; Siano, Pierluigi

doi:10.1016/j.epsr.2014.02.021

Cited by 151 publications

(73 citation statements)

References 49 publications

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“…Moreover modified augmented ε-constrained method along with FDM has utilized for best compromise solution among the set of Pareto optimal solutions. [40] 2014 2 1 ✓ ---MO augmented ε constrained method proposed for DGP planning on short term basis for future DNWs with ANM functionalities. The MOO planning framework based on non-dominated sorting genetic algorithm II (NSGA-II) along with MCS (for uncertain operation ---An MO optimization problem for multiple micro-turbines (DG) placement and sizes is solved by hybrid PSO and SFL algorithms based framework, followed by fuzzy decision-making tool to select the most preferred Pareto optimal solution satisfying competing objectives.…”

Section: Planning Techniques Based On Evaluation Methods In Multi-objmentioning

confidence: 99%

“…CONOPT solver of GAMS solves the nonlinear optimization problem (NLP) as in [39]. The DICOPT solver of GAMS solves MINLP problem as in [40].…”

Section: Load Flow Solution Methods (S)mentioning

confidence: 99%

Section: ---mentioning

confidence: 99%

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Multi-Objective Planning Techniques in Distribution Networks: A Composite Review

2017

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Distribution networks (DNWs) are facing numerous challenges, notably growing load demands, environmental concerns, operational constraints and expansion limitations with the current infrastructure. These challenges serve as a motivation factor for various distribution network planning (DP) strategies, such as timely addressing load growth aiming at prominent objectives such as reliability, power quality, economic viability, system stability and deferring costly reinforcements. The continuous transformation of passive to active distribution networks (ADN) needs to consider choices, primarily distributed generation (DG), network topology change, installation of new protection devices and key enablers as planning options in addition to traditional grid reinforcements. Since modern DP (MDP) in deregulated market environments includes multiple stakeholders, primarily owners, regulators, operators and consumers, one solution fit for all planning scenarios may not satisfy all these stakeholders. Hence, this paper presents a review of several planning techniques (PTs) based on mult-objective optimizations (MOOs) in DNWs, aiming at better trade-off solutions among conflicting objectives and satisfying multiple stakeholders. The PTs in the paper spread across four distinct planning classifications including DG units as an alternative to costly reinforcements, capacitors and power electronic devices for ensuring power quality aspects, grid reinforcements, expansions, and upgrades as a separate category and network topology alteration and reconfiguration as a viable planning option. Several research works associated with multi-objective planning techniques (MOPT) have been reviewed with relevant models, methods and achieved objectives, abiding with system constraints. The paper also provides a composite review of current research accounts and interdependence of associated components in the respective classifications. The potential future planning areas, aiming at the multi-objective-based frameworks, are also presented in this paper.Keywords: active distribution network (ADN); distributed generation (DG); distributed energy resources (DERs); distribution network planning (DP); multi-objective optimization (MOO); multi-criteria decision analysis (MCDA); distributed generation placement (DGP); volt-ampere reactive power (VAR) compensation and power quality (VPQ); component reinforcement and up gradation (CRU); network (distribution) topology change and reconfiguration (NTR); planning techniques (PT); multiple objective planning (MOP); multi-objective planning techniques (MOPTs); future distribution networks (FDNs)

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Section: Planning Techniques Based On Evaluation Methods In Multi-objmentioning

confidence: 99%

“…CONOPT solver of GAMS solves the nonlinear optimization problem (NLP) as in [39]. The DICOPT solver of GAMS solves MINLP problem as in [40].…”

Section: Load Flow Solution Methods (S)mentioning

confidence: 99%

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Multi-Objective Planning Techniques in Distribution Networks: A Composite Review

2017

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“…The corresponding solutions for the models are based on linear [19,20] or nonlinear programing [16,21], mixed integer programming [22,23], dynamic programming [24], and decision theory [25][26][27]. Multiobjective problems and the methods for solving them have also been studied [28,29]. Most of the scheduling optimization research deals with day-ahead (24 h) scheduling problems to verify the effectiveness of the proposed models and the promotion effect on energy efficiency [30].…”

Section: Introductionmentioning

confidence: 99%

“…In the power generation section, some models have been proposed to reduce wind and solar [29,34,35] power generation forecasting error. Stochastic formulation [28,29] has also been used to simulate power generation. Other literature deals with load forecasting [36,37] and market price forecasting [38,39].…”

Section: Introductionmentioning

confidence: 99%

Joint Scheduling Optimization of Virtual Power Plants and Equitable Profit Distribution Using Shapely Value Theory

Tan

et al. 2018

Mathematical Problems in Engineering

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The installation capacity of wind and solar photovoltaic power is continually increasing, which makes renewable energy grid connection and power generation an important link of China's power structure optimization. A virtual power plant (VPP) is an important way to help distributed energy resource grid connection and promote renewable energy industry development. To study the economic scheduling problem of various distributed energy resources and the profit distribution problem of VPP alliance, this study builds a separate operation scheduling model for individual VPP and a joint operation scheduling model for VPP alliance, as well as the profit distribution model. The case study verifies the feasibility and effectiveness of the proposed model. The sensitivity analysis provides information about VPP decision-making in accordance with the policy environment development trend.

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A joint energy and reserve scheduling framework based on network reliability using smart grids applications

Ansari

Malekshah

2019

Int Trans Electr Energ Syst

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Summary This paper presents a new method based on a probabilistic scheduling reserve for smart grids, which include renewable energy sources (RESs), thermal units, and energy storage systems (ESSs). The method is divided into two main parts. The first part is based on spinning reserve to overcome the load‐generation imbalance in the network, while the second part is related to the spinning reserve for the outage of generation units. The total expected energy not supplied (TEENS) is the reliability criterion that determines the required spinning reserve. In the proposed formulation, generation units, the demand response (DR) program, and ESSs are capable of providing both types of reserves. The proposed method is evaluated using The Institute of Electrical and Electronics Engineers (IEEE) standard 30‐bus and IEEE reliability test networks. The suggested structure has been implemented by General Algebraic Modeling System (GAMS), and the results indicate the appropriate performance of the proposed method.

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Stochastic multi-objective operational planning of smart distribution systems considering demand response programs

Cited by 151 publications

References 49 publications

Multi-Objective Planning Techniques in Distribution Networks: A Composite Review

Multi-Objective Planning Techniques in Distribution Networks: A Composite Review

Joint Scheduling Optimization of Virtual Power Plants and Equitable Profit Distribution Using Shapely Value Theory

A joint energy and reserve scheduling framework based on network reliability using smart grids applications

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