Risk Constrained Energy Efficient Optimal Operation of a Converter Governed AC/DC Hybrid Distribution Network With Distributed Energy Resources and Volt-VAR Controlling Devices
Increasing penetration of direct current (dc) based distributed energy resources and dc loads in the conventional alternating current (ac) network necessitate the deployment of ac/dc hybrid distribution networks (HDNs). In view with the development of advanced energy management policy for ac/dc HDNs...
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| Published in: | IEEE transactions on industry applications Vol. 57; no. 4; pp. 4263 - 4277 |
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| Main Authors: | , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
New York
IEEE
01.07.2021
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subjects: | |
| ISSN: | 0093-9994, 1939-9367 |
| Online Access: | Get full text |
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| Abstract | Increasing penetration of direct current (dc) based distributed energy resources and dc loads in the conventional alternating current (ac) network necessitate the deployment of ac/dc hybrid distribution networks (HDNs). In view with the development of advanced energy management policy for ac/dc HDNs, unlike previous literatures, this article proposes a risk constrained energy efficient management algorithm by merging load shifting (LS) and conservation voltage reduction (CVR) techniques. The optimization framework aims to simultaneously minimize both true and conditional risk or conditional value at risk values of the expected energy cost under uncertain solar power generation, load demand, and upper grid energy price. In contrast with the available stochastic optimization process, in this article, two-point estimation strategy is employed in place of Monte Carlo simulation for scenario generation from the probability density functions of the uncertain parameters to reduce computational exertion. The proposed centralized optimization framework is initially developed as mixed integer nonconvex programming but to avoid computation complexity, the nonlinear components are replaced by their linear counterparts. Later, a new solution process named successive mixed integer linear programming (s-MILP) is proposed to obtain the optimal decisions for deployment of LS and CVR through smart inverters and volt-VAR controlling devices. Efficacy of the proposed technique is demonstrated on modified IEEE 33 bus ac/dc HDN and the most energy efficient operation is found by merging LS and CVR. Simulation outcomes prove fast and near optimal convergence of the s-MILP compared to conventional second-order conic programming relaxed mixed integer convex programming and piecewise linearization based MILP. Further, to assess the impact of network size on the solution time and optimality, the proposed advanced distribution network management systems strategy is employed on 132 bus ac/dc HDN. |
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| AbstractList | Increasing penetration of direct current (dc) based distributed energy resources and dc loads in the conventional alternating current (ac) network necessitate the deployment of ac/dc hybrid distribution networks (HDNs). In view with the development of advanced energy management policy for ac/dc HDNs, unlike previous literatures, this article proposes a risk constrained energy efficient management algorithm by merging load shifting (LS) and conservation voltage reduction (CVR) techniques. The optimization framework aims to simultaneously minimize both true and conditional risk or conditional value at risk values of the expected energy cost under uncertain solar power generation, load demand, and upper grid energy price. In contrast with the available stochastic optimization process, in this article, two-point estimation strategy is employed in place of Monte Carlo simulation for scenario generation from the probability density functions of the uncertain parameters to reduce computational exertion. The proposed centralized optimization framework is initially developed as mixed integer nonconvex programming but to avoid computation complexity, the nonlinear components are replaced by their linear counterparts. Later, a new solution process named successive mixed integer linear programming (s-MILP) is proposed to obtain the optimal decisions for deployment of LS and CVR through smart inverters and volt-VAR controlling devices. Efficacy of the proposed technique is demonstrated on modified IEEE 33 bus ac/dc HDN and the most energy efficient operation is found by merging LS and CVR. Simulation outcomes prove fast and near optimal convergence of the s-MILP compared to conventional second-order conic programming relaxed mixed integer convex programming and piecewise linearization based MILP. Further, to assess the impact of network size on the solution time and optimality, the proposed advanced distribution network management systems strategy is employed on 132 bus ac/dc HDN. |
| Author | Paul, Subho Sharma, Abhimanyu Padhy, Narayana |
| Author_xml | – sequence: 1 givenname: Subho orcidid: 0000-0002-7242-5652 surname: Paul fullname: Paul, Subho email: spaul@ee.iitr.ac.in organization: Department of Electrical Engineering, Indian Institute of Technology Roorkee, Roorkee, India – sequence: 2 givenname: Abhimanyu surname: Sharma fullname: Sharma, Abhimanyu email: abhimanyu1@ee.iitr.ac.in organization: Department of Electrical Engineering, Indian Institute of Technology Roorkee, Roorkee, India – sequence: 3 givenname: Narayana surname: Padhy fullname: Padhy, Narayana email: nppadhy@ee.iitr.ac.in organization: Department of Electrical Engineering, Indian Institute of Technology Roorkee, Roorkee, India |
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| SubjectTerms | Algorithms Alternating current Alternating current (ac)/direct current (dc) hybrid distribution network (HDN) Batteries Computational geometry Computer simulation conditional value at risk (CVaR) conservation voltage reduction (CVR) Convexity Direct current Distributed generation Distribution networks Electric converters Electrical loads Energy costs Energy distribution Energy management Energy resources Energy sources Integer programming Inverters Linear programming Load flow Load shifting load shifting (LS) Management systems Mathematical programming Mixed integer Monte Carlo simulation Optimization Parameter uncertainty Probability density functions Programming Reactive power Risk Strategy Stress concentration successive mixed integer linear programming (s-MILP) two-point estimation (2PE) |
| Title | Risk Constrained Energy Efficient Optimal Operation of a Converter Governed AC/DC Hybrid Distribution Network With Distributed Energy Resources and Volt-VAR Controlling Devices |
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