MPC-Based Local Voltage Control Strategy of DGs in Active Distribution Networks

Li, Peng; Ji, Jie; Ji, Haoran; Jian, Jie; Ding, Fei; Wu, Jianzhong; Wang, Chengshan

doi:10.1109/tste.2020.2981486

Cited by 57 publications

(25 citation statements)

References 42 publications

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“…Figs. 2 and 3 show the robust info gap regions attained from uncertainty horizon κ m based on (27), and the RA offering scheme in the DA and RT markets. For the DA strategic offering in the first-stage, the uncertainty horizon κ I is optimized as 0.201.…”

Section: A Robust Sigm For Ra Offeringmentioning

confidence: 99%

“…Once the DA market is cleared, the CSP plant also has the opportunity to offer in the RT market, which is decided in the second-stage. In order to mitigate the prediction errors and consider the latest predictions and future possible conditions, the CSP plant in the RT market determines the offering strategy in a rolling horizon manner, also known as model predictive control [27], [28], i.e., in each operating hour h the second-stage model is optimized with a looking ahead horizon |T |-h + 1 based on the updated latest information by hour h-1, but only the offering strategy in operating hour h is actually implemented; then in h + 1 the second-stage model is solved again with a looking ahead horizon |T |-h and only the offering strategy in h + 1 is implemented [29].…”

Section: ) Second-stage: Rt Offering Strategy Optimizationmentioning

confidence: 99%

“…The two models are connected by an user-set robust revenue threshold, as in (29). By using the robust IGDT, the revenue of the RA CSP plant under NSUs from the thermal production would not be less than the robust revenue threshold if the actual thermal production falls into the info gap region defined by (27).…”

Section: A Igdt For Management Of Nsusmentioning

confidence: 99%

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A Mixed CVaR-Based Stochastic Information Gap Approach for Building Optimal Offering Strategies of a CSP Plant in Electricity Markets

et al. 2020

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The development of the concentrating solar power (CSP) plant as a new dispatchable resource that can participate in the electricity markets as an independent power producer and coordinate intermittent renewables has attracted much attention recently. In this work, optimal offering strategies of a price-taker CSP plant in the day-ahead (DA) and real-time (RT) electricity markets are addressed considering non-stochastic uncertainties (NSUs) from the thermal production of the CSP plant and stochastic uncertainties (SUs) from the market prices as well as the risk attitude of the CSP plant concerned. A hybrid stochastic information gap approach (SIGA) integrating the well-established information gap decision theory with the mixed conditional value at risk (CVaR) is proposed to hedge the revenue risk against NSUs and SUs in the offering problem based on the risk preference of the decision maker. A two-stage architecture is utilized for framing the DA and RT offering problems, where the first-stage co-optimizes offering strategies in the DA and RT markets, while the second-stage determines the actual RT hourly offering strategy in a rolling horizon manner. Case studies show that the SIGA can make optimal offering strategies against the non-stochastic thermal production and stochastic market prices given the risk attitude of the CSP plant. Comparisons also demonstrate that the SIGA could be an effective tool to manage coexistent NSUs and SUs.

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Section: A Robust Sigm For Ra Offeringmentioning

confidence: 99%

Section: ) Second-stage: Rt Offering Strategy Optimizationmentioning

confidence: 99%

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A Mixed CVaR-Based Stochastic Information Gap Approach for Building Optimal Offering Strategies of a CSP Plant in Electricity Markets

et al. 2020

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“…In [12], optimal power flow is used to coordinate the droop control of DG in dealing with overvoltage challenges on distribution grids. However, the implementation of schemes such as in [7][8][9][10][11][12] requires communication facilities that are absent in most medium-voltage distribution grids in developing countries because of limited financial resources.…”

Section: Introductionmentioning

confidence: 99%

Autonomous adaptive Q(U) control for distributed generation in weak medium‐voltage distribution grids

Ampofo

Myrzik

2021

IET Energy Syst Integration

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This study seeks to exploit the reactive power capability of inverter-based distributed generation (DG) to solve the voltageregulation challenges associated with weak mediumvoltage distribution networks in developing countries. Voltage-dependent reactive power control, also known as the Q(U) control method, is widely used for voltage regulation. The challenge with this control mode, however, is determining its control parameters, which must be unique for each bus for optimal performance compared with implementing standardised or general parameters. This paper proposes an innovative approach to incorporate an adaptive functionality into the typical Q(U) control to enhance its performance in medium-voltage grids. This concept, when implemented, achieved better performance than that of the Q(U) control with fixed parameters, which was unsatisfactory under certain conditions, and performance comparable to that of the centralised voltage scheme, which relies on communication facilities. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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“…Bidgoli and Cutsem [16] proposed an MPC‐based approach to refine the reactive power set‐point corrections of DG units centrally, obtained from the local control. In [17], MPC is used as a local voltage control strategy to frequently tune the local curve of DG units to adjust the DG uncertainties. A distributed MPC is proposed as a secondary control scheme for autonomous microgrids (MGs) in [18].…”

Section: Introductionmentioning

confidence: 99%

Model predictive control‐based optimal voltage regulation of active distribution networks with OLTC and reactive power capability of PV inverters

Dutta¹,

Ganguly²,

Kumar³

2020

IET gener. transm. distrib.

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MPC-Based Local Voltage Control Strategy of DGs in Active Distribution Networks

Cited by 57 publications

References 42 publications

A Mixed CVaR-Based Stochastic Information Gap Approach for Building Optimal Offering Strategies of a CSP Plant in Electricity Markets

A Mixed CVaR-Based Stochastic Information Gap Approach for Building Optimal Offering Strategies of a CSP Plant in Electricity Markets

Autonomous adaptive Q(U) control for distributed generation in weak medium‐voltage distribution grids

Model predictive control‐based optimal voltage regulation of active distribution networks with OLTC and reactive power capability of PV inverters

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