Robust Restoration Decision-Making Model for Distribution Networks Based on Information Gap Decision Theory

Chen, Kening; Wu, Wenchuan; Zhang, Boming; Sun, Hongbin

doi:10.1109/tsg.2014.2363100

Cited by 128 publications

(83 citation statements)

References 32 publications

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“…The Information Gap Decision Theory (IGDT) [19] tries to find the optimal set of DV to maximize the robustness of the objective function against the uncertainty input parameters [29]. It has been used in various applications such as electricity retailer energy selling strategy [30], generation asset allocation [31], transmission expansion planning [32] and GenCo's Trading Portfolio [33] and Distribution network restoration [34]. An optimization problem could generally be defined as follows:…”

Section: Proposed Igdt Formulationmentioning

confidence: 99%

Robust computational framework for mid‐term techno‐economical assessment of energy storage

Maghouli¹,

Soroudi

Keane

2016

IET Generation, Transmission & Distribution

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Abstract-Rapid expansion and integration of wind energy is restrained due to transmission capacity constraints and conventional generation technologies limited operational flexibility in todays power systems. Energy storage is an attractive option to integrate and utilize more renewable energy without major and timely upgrade of existing transmission infrastructure. Also it can be considered as a mean for differing the reinforcement plans. The evaluation of energy storage deployment projects is a challenging task due to severe uncertainty of wind power generation. In this paper a robust techno-economic framework is proposed for energy storage evaluation based on Information Gap Decision Theory for handling wind generation uncertainty. The total social cost of the system including conventional generators' fuel and pollution cost and wind power curtailment cost is optimized considering generators operational constraints and transmission system capacity limitations based on the DC model of the power grid. The effect of storage devices on system performance is evaluated taking into account wind power uncertainty. The proposed method is conducted on the modified IEEE Reliability Test System (IEEE-RTS) and the modified IEEE 118 bus test system to assess its applicability and performance in midterm robust evaluation of energy storage implementation plans.Index Terms-DC optimal power flow, Storage devices, Transmission capacity constraints, Wind power generation, Information Gap Decision Theory. NOMENCLATURE Sets & Indices Capacity of Wind turbine installed in busCharging/discharging efficiency of the energy storage unitCritical/opportunistic increase/decrease of base cost in RA/RS approach ($) ∆t Duration of time period t ag/bg/cg Fuel cost coefficient of thermal unit g P I. INTRODUCTION A. Background and motivationsMany countries have long term plans to increase the share of renewable energy resources in their generation mix. Among these renewable resources there has been increasing interest to invest and integrate more wind power in to existing power systems. However, increasing the wind penetration introduces profound challenges to traditional operating and planning practices. These new challenges arise mainly because of the variable nature of wind energy which results in none optimal operation of electric power systems. Traditionally it is accepted that electricity supply and consumption must remain in instantaneous balance the opportunity to store electrical energy in storage devices may now change this paradigm. Wind power intermittency and variability requires other fast ramping power sources to balance the supply-demand equilibrium in power systems [1]. Because of limiting capacity of fast ramping generation technologies such as hydro and pumped storage power plants, significant integration of wind power to existing power infrastructure requires major system upgrades or implementing energy storage facilities [2]. Besides, using energy storage facilities will result in more utilization of existing assets and ...

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Section: Proposed Igdt Formulationmentioning

confidence: 99%

Robust computational framework for mid‐term techno‐economical assessment of energy storage

Maghouli¹,

Soroudi

Keane

2016

IET Generation, Transmission & Distribution

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“…IGDT has been used in many fields of research, in [18] to assess the management of timber production and in [19] for the planning of water resources. This approach is also applicable to power system analysis [20][21][22][23] especially under severe uncertainty.…”

Section: Information Gap Decision Theory Based Congestion and Voltagementioning

confidence: 99%

“…Equating the active power and reactive power flow on the lines of the network to the net power flow found from (17) and (18) for a connected node, gives (19) and (20).…”

Section: ) Objective Functionmentioning

confidence: 99%

Information Gap Decision Theory based congestion and voltage management in the presence of uncertain wind power

Murphy

Soroudi

Keane

2016

2016 IEEE Power and Energy Society General Meeting (PESGM)

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“…Based on the works [11], [12], [18] and [19] proposed an improved restoration algorithm, which is adopted in this paper, accompanied with the idea of using conic relaxation technique from [20]. Regarding the previous works, the main contributions of this paper are:…”

Section: Introductionmentioning

confidence: 99%

“…1) A second-order cone programming with mixed-integer (MISOCP), considering network losses based on [19] and [20], is established for the analysis of distribution network reconfiguration functionalities. 2) Based on (1), two improved TSC evaluation models are presented.…”

Section: Introductionmentioning

confidence: 99%

A Method to Evaluate Total Supply Capability of Distribution Systems Considering Network Reconfiguration and Daily Load Curves

Chen

Zhang

et al. 2016

IEEE Trans. Power Syst.

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The total supply capability (TSC) is an important index for assessing the reliability of a distribution power system. In this paper, two models to evaluate the TSC are established. In the first, the TSC is acquired with the conditions that all load outages can be restored via network reconfiguration with transformers' N-1 contingencies, i.e., that all constraints related to branch thermal ratings and bus-voltage limits can be satisfied following restoration for each N-1 contingency. The second model, which is revision of the first, considers the daily load curves for different classes of customers, e.g., residential, commercial and industrial. Both models can be formulated as mixed integer problems with second-order cone programming (MISOCP), which can be solved using commercially available optimization software. Two test systems are used to demonstrate the applicability of the presented models. Numerical results show that the presented model is more accurate than the previously published models. This proposed analytical approach can be applied in a range of network planning studies, e.g., for selecting appropriate ratings of transformers, or for optimal locating of circuit breakers and distributed energy resources.Index Terms-Daily load curves, distribution power system, N-1 contingency, total supply capability. NOMENCLATURESet of all buses, excluding root buses.Set of root buses.

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Robust Restoration Decision-Making Model for Distribution Networks Based on Information Gap Decision Theory

Abstract: His current research interests include active distribution network security analysis and restoration. Wenchuan Wu (SM'14) received the B.S., M.S., and Ph.D. degrees from the Electrical Engineering

Cited by 128 publications

References 32 publications

Robust computational framework for mid‐term techno‐economical assessment of energy storage

Robust computational framework for mid‐term techno‐economical assessment of energy storage

Information Gap Decision Theory based congestion and voltage management in the presence of uncertain wind power

A Method to Evaluate Total Supply Capability of Distribution Systems Considering Network Reconfiguration and Daily Load Curves

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