DiSC: A simulation framework for distribution system voltage control

Pedersen, Rasmus; Sloth, Christoffer; Andresen, Gorm Bruun; Wisniewski, Rafael

doi:10.1109/ecc.2015.7330680

Cited by 49 publications

(33 citation statements)

References 13 publications

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“…In order to evaluate the monitoring framework we implemented a prototype of the publisher layer inside of DiSC simulation framework [6]. DiSC is MATLAB based open source simulation framework that contains implementation of PV panels, as well as the data of real solar irradiation and household consumption collected in Denmark.…”

Section: Simulation Framework and Evaluation Resultsmentioning

confidence: 99%

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Information-Quality Based LV-Grid-Monitoring Framework and Its Application to Power-Quality Control

Findrik

Kristensen

Hinterhofer

et al. 2015

Ad-Hoc, Mobile, and Wireless Networks

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Abstract. The integration of unpredictable renewable energy sources into the low voltage (LV) power grid results in new challenges when it comes to ensuring power quality in the power grid. Addressing this problem requires control of not only the secondary substation but also control of flexible assets inside the LV grid. In this paper we investigate how the flexibility information of such assets can be accessed by the controller using heterogeneous off-the-shelf communication networks. To achieve this we develop an adaptive monitoring framework, through which the controller can subscribe to the assets' flexibility information through an API. We define an information quality metric making the monitoring framework able to adapt information access strategies to ensure the information is made available to the controller with the highest possible information quality. To evaluate the monitoring framework, an event-driven voltage controller is simulated in an LV grid. This controller utilizes the flexibility of photovoltaic (PV) panels to get the voltages into acceptable ranges when the limit is exceeded. This is done by controlling the grid periodically during the time interval that starts when a voltage limit is exceeded and ends when an acceptable voltage level is reestablished. We show how the volatile behaviour of the PV panels causes overvoltages in a baseline scenario. We then show the controller's ability to keep the voltages within their limits. Lastly we show how control performance can be increased by optimizing information access strategies.

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Section: Simulation Framework and Evaluation Resultsmentioning

confidence: 99%

“…Algorithm 1: PI control algorithm for stabilizing the voltage at the bus i utilizing PVs at the bus i and the upstream buses b ∈ X The PV model used for evaluation purposes is adopted from the simulation framework in reference [6] (details are described in Section 4), where active power output in normal operation is given by:…”

Section: Voltage Control Approachmentioning

confidence: 99%

Information-Quality Based LV-Grid-Monitoring Framework and Its Application to Power-Quality Control

Findrik

Kristensen

Hinterhofer

et al. 2015

Ad-Hoc, Mobile, and Wireless Networks

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“…measurement at the branch connecting the feeder to the main grid, as in [12]. Load samples are constructed by aggregating load data of several households [19], and generation availability is constructed using real solar irradiation and wind speed data [10]. We choose the standard voltage limits V min = 0.95, V max = 1.05 [10].…”

Section: Case Optimum Expectationmentioning

confidence: 99%

Sieving out Unnecessary Constraints in Scenario Optimization with an Application to Power Systems

Picallo

Dörfler

2019

2019 IEEE 58th Conference on Decision and Control (CDC)

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Many optimization problems incorporate uncertainty affecting their parameters and thus their objective functions and constraints. As an example, in chance-constrained optimization the constraints need to be satisfied with a certain probability. To solve these problems, scenario optimization is a well established methodology that ensures feasibility of the solution by enforcing it to satisfy a given number of samples of the constraints. The main theoretical results in scenario optimization provide the methods to determine the necessary number of samples, or to compute the risk based on the number of so-called support constraints. In this paper, we propose a methodology to remove constraints after observing the number of support constraints and the consequent risk. Additionally, we show the effectiveness of the approach with an illustrative example and an application to power distribution grid management when solving the optimal power flow problem. In this problem, uncertainty in the loads converts the admissible voltage limits into chance-constraints.

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“…The blockchain is based on peer-to-peer networking, where each agent connects to a set of randomly selected neighbors. 2 The communication protocol adopts TCP connections to exchange two types of information, as shown in Fig. 3.…”

Section: Peer-to-peer Network and Protocol Messagesmentioning

confidence: 99%

“…Inspired by the MG LV scenario in [2], we adopt the power system composed by LV and MV MGs depicted in Fig. 1 as 6 We note that the scenario with a single neighbor should be avoided, as in this case a malicious neighbor may corrupt or hide the information [11].…”

Section: Case Studymentioning

confidence: 99%

Distributed proportional-fairness control in microgrids via blockchain smart contracts

Danzi

Angjelichinoski

Stefanović

et al. 2017

2017 IEEE International Conference on Smart Grid Communications (SmartGridComm)

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Residential microgrids (MGs) may host a large number of Distributed Energy Resources (DERs). The strategy that maximizes the revenue for each individual DER is the one in which the DER operates at capacity, injecting all available power into the grid. However, when the DER penetration is high and the consumption low, this strategy may lead to power surplus that causes voltage increase over recommended limits. In order to create incentives for the DER to operate below capacity, we propose a proportional-fairness control strategy in which (i) a subset of DERs decrease their own power output, sacrificing the individual revenue, and (ii) the DERs in the subset are dynamically selected based on the record of their control history. The trustworthy implementation of the scheme is carried out through a custom-designed blockchain mechanism that maintains a distributed database trusted by all DERs. In particular, the blockchain is used to stipulate and store a smart contract that enforces proportional fairness. The simulation results verify the potential of the proposed framework.

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DiSC: A simulation framework for distribution system voltage control

Cited by 49 publications

References 13 publications

Information-Quality Based LV-Grid-Monitoring Framework and Its Application to Power-Quality Control

Information-Quality Based LV-Grid-Monitoring Framework and Its Application to Power-Quality Control

Sieving out Unnecessary Constraints in Scenario Optimization with an Application to Power Systems

Distributed proportional-fairness control in microgrids via blockchain smart contracts

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