Active and Reactive Power Management in the Smart Distribution Network Enriched with Wind Turbines and Photovoltaic Systems

Mehbodniya, Abolfazl; Paeizi, Ali; Rezaie, Mehrdad; Azimian, Mahdi; Masrur, Hasan; Senjyu, Tomonobu

doi:10.3390/su14074273

Cited by 13 publications

(5 citation statements)

References 38 publications

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“…Of course, the basic requirement of this method is the convexity of the lower-level problem; however, this problem is non-convex due to the use of power flow equations [20,21]. Thus, to compensate for this challenge, a linear approximation model is first developed for the lower-level problem constraints [29][30][31]. Then a mixed-integer quadratically constrained program (MIQCP) model with quadratic objective function and linear constraints is obtained for the single-level problem.…”

Section: Contributionsmentioning

confidence: 99%

Resilience‐oriented expansion planning of multi‐carrier microgrid utilizing bi‐level technique

Dehshiri Badi,

Amir,

Shariatmadar

2023

IET Renewable Power Gen

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This paper presents the generation and transmission expansion planning (GTEP) in electricity and gas networks by considering their resilience against floods and earthquakes. These networks supply electricity, heat, and gas consumption energies as a multi‐carrier microgrid. The scheme is expressed in the form of bi‐level optimization, the upper level of which is the minimization of generation and transmission planning cost (total investment cost and expected operating cost) in the mentioned networks constrained to the investment budget and the planning model of the mentioned elements. Lower‐level formulation minimizes the total expected annual operating cost of these networks and the expected outage cost of electricity, heat, and gas consumers in the event of floods and earthquakes. This formulation is bound by the power flow equations of electricity and gas networks, the operation and resilience constraints of the networks, and the limitation on generation capability. In this problem, the expected energy not‐supplied and the outage cost during natural disasters are considered resilience indicators. Next, a single‐level model for the proposed design is extracted from the Karush–Kuhn–Tucker (KKT) method. The basic requirement of this method is the convexity of the lower‐level constraints. For this purpose, first, a linear approximation model is obtained for the lower‐level constraints of the problem. Furthermore, stochastic optimization is adopted to model the uncertainty of load, renewable power, and network equipment availability during floods and earthquakes. Finally, the extracted numerical results confirm the capability of the proposed scheme in improving the operation and resilience of the mentioned networks using optimal generation and transmission planning.

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Section: Contributionsmentioning

confidence: 99%

Resilience‐oriented expansion planning of multi‐carrier microgrid utilizing bi‐level technique

Dehshiri Badi,

Amir,

Shariatmadar

2023

IET Renewable Power Gen

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“…The authors concluded that injecting reactive power into the grid through the inverters is a viable energy-saving solution. In [19], the authors discuss the energy management of smart DNs that include WG and PVG. The model aims at minimizing DN operating costs stated as an objective function in relation to the constraints of an optimal AC power flow.…”

Section: Related Workmentioning

confidence: 99%

Multi-Period Optimal Power Flow with Photovoltaic Generation Considering Optimized Power Factor Control

de Souza,

da Silva,

Rossoni

et al. 2023

Sustainability

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This paper presents a Multi-Period Optimal Power Flow (MOPF) modeling applied to the minimization of energy losses in Distribution Networks (DNs) considering the reactive power control of Photovoltaic Generation (PVG) that can be applied to both short-term and long-term operation planning. Depending on the PV Power Factor (PVpf) limitations, PVG may provide both active and reactive power. The optimal power factor control on the buses with PVG contributes to an economical and safe operation, minimizing losses and improving the voltage profile of the DN. The proposed MOPF was modeled in order to minimize active energy losses subject to grid constraints and PVpf limitations. The variations of loads and PVG were discretized hour by hour, composing a time horizon of 24 h for day-ahead planning; nonetheless, the methodology can be applied to any other time period, such as a month, year, etc., by simply having generation and load forecasts. To demonstrate the effectiveness and applicability of the proposed approach, various tests were carried out on 33-bus and 69-bus distribution test systems. The analyses considered the DN operating with PVG in four different cases: (a) PVpf fixed at 1.0; (b) PVpf fixed at 0.9 capacitive; (c) hourly PVpf optimization; and (d) optimization of PVpf for a single value. The results show that a single optimal adjustment of PVpf minimizes losses, improves voltage profile, and promotes safe operation, avoiding multiple PVpf adjustments during the operating time horizon. The algorithm is extremely fast, taking around 2 s to reach a solution.

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“…The distribution network operation optimization (DNOO) problem is essentially a multivariate and uncertain problem [1]. With the construction of new energy power system, the transformation of energy is unstoppable, and the status of new energy power generation (especially photovoltaic and wind power) in the power system is gradually rising [2][3][4][5], which increases the difficulty of distribution network operation optimization [6,7]. Because large-scale wind and solar time series data will bring high time complexity to the optimization program, it is necessary to determine the typical scene of wind and scenery.…”

Section: Introductionmentioning

confidence: 99%

Operation Optimization Method of Distribution Network with Wind Turbine and Photovoltaic Considering Clustering and Energy Storage

et al. 2023

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The problem of distribution network operation optimization is diversified and uncertain. In order to solve this problem, this paper proposes a method of distribution network operation optimization considering wind-solar clustering, which includes source load and storage. Taking the total operating cost as the objective function, it includes network loss cost, unit operating cost, and considers a variety of constraints such as energy storage device constraints and demand response constraints. This paper aims to optimize the operation according to different wind-solar clustering scenes to improve the economy of distribution network. Taking the 365-day wind-solar output curves as the research object, K-means clustering is carried out, and the best k value is obtained by elbow rule. The second-order cone programming method and solver are used to solve the optimization model of each typical scenario, and the operation optimization analysis of each typical scenario obtained by clustering is carried out. Taking IEEE33 system and local 365-day wind-solar units output scenes as examples, the period is 24 h, which verifies the effectiveness of the proposed method. The proposed method has guiding significance for the operation optimization of distribution network.

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Active and Reactive Power Management in the Smart Distribution Network Enriched with Wind Turbines and Photovoltaic Systems

Cited by 13 publications

References 38 publications

Resilience‐oriented expansion planning of multi‐carrier microgrid utilizing bi‐level technique

Resilience‐oriented expansion planning of multi‐carrier microgrid utilizing bi‐level technique

Multi-Period Optimal Power Flow with Photovoltaic Generation Considering Optimized Power Factor Control

Operation Optimization Method of Distribution Network with Wind Turbine and Photovoltaic Considering Clustering and Energy Storage

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