A data-driven approach to support voltage profiles & loss reduction in wind generator integrated active distribution network considering solid-state transformers with twofold reactive power compensation

ABSTRACT

The paper proposes an optimal planning strategy for an active distribution network (ADN) with wind energy-based distributed generation (WDG) by considering the twofold reactive power compensation (TRPC) feature of a three-stage type solid-state transformer (SST). A model for wind speed and load demand estimation for each hour of the day is formulated by using the partition around medoids (PAM) technique over an annual database of load demand and wind speed. A multi-objective mixed-integer non-linear programming (MINLP) approach for optimally locating and sizing the SST installations in the radial distribution network (RDN) is presented to address the dual objectives of voltage profile improvement (VPI) and energy loss reduction (ELR). Along with the SST parameters, the locations and number of wind turbine (WT) units to be integrated into the system are treated as optimization variables. Furthermore, the distribution power flow accounts for the distribution transformer’s (DT) operating losses as well as the approximate losses of the SST. The presented approach is tested on a 33-bus RDN and the results are reported for multiple case studies. The programming was developed in the MATLAB R2020a environment and the paretosearch algorithm (PSA) is used to address the MINLP problem. Other standard multi-objective optimization algorithms, including multi-objective multi-verse optimization (MOMVO), non-dominated sorting genetic algorithm (NSGA-II), and multi-objective salp swarm algorithm (MSSA) are used to compare the performance of the proposed method. The outcomes of the peak hour evaluation, with a 20% over-rating, show the active and reactive power demand on the MV side of the substation to have decreased by 56.3% and 30.1% respectively. The active line loss has been lowered by 76.95% and the reactive line loss has decreased by 76.14%. The absolute minimum voltage has increased by 7.314%. Furthermore, according to the annual technical evaluation, there was a 29.42% reduction in active energy served by the DTs and SSTs.

Graphical abstract

KEYWORDS:

• Solid-state transformer
• active distribution network
• distributed generation
• voltage profile improvement
• loss reduction

Abbreviations

ADN; Active distribution network, DG; Distributed generation, DN; Distribution network, DNP; Distribution network planning, DSTATCOM; Distribution static compensator, DT; Distribution transformer, ELR; Energy loss reduction, LVDC; Low-voltage DC, MINLP; Mixed integer non-linear programming problem, MOMVO; Multi-objective multi-verse optimization, MVDC; Medium-voltage DC, NCES; Non-conventional energy sources, NSGA; Non-dominated sorting genetic algorithm, MSSA; Multi-objective salp swarm algorithm, PAM; Partition around medoids, PSA; paretosearch algorithm, PV; Photovoltaic, RDN; Radial distribution network, RPA; Reactive power assistance, SST; Solid-state transformer, TRPC; Twofold reactive power compensation, UPQC; Unified power quality condenser, VPI; Voltage profile improvement, WDG; Wind energy-based distributed generation, WT; Wind turbine, $v^f(t)$; Hourly variation factor, $\lambda$; Percentage of over-rating, ${\rho }_1,{\rho }_2$; Objective functions, ${\phi }_{DT}$; Bus location for DT positioning, ${\phi }_{SST}$; Bus location for SST positioning, ${\phi }_W$; Bus location for WDG positioning, $ALF$; Annual load factor, $I_{b,h}$; Branch current at hour $h$, $n_{br}$; Total number of branches, $n_{bus}$; Total number of buses, $n_h$; Number of daily hours, $n_W,n_{SST},n_{DT}$; No. of WDG, SST and DT, $P_{D,k},Q_{D,k},S_{D,k}$; Projected real, reactive and apparent load at bus $k$ for hour $t$, $P_k,Q_k$; Peak real and reactive load at bus $k$, $P_{L,SST}^k$; Losses of $k^{th}$ SST unit, $P_{L_{DT}}^m$; Actual losses of the $m^{th}$ DT, $P_{NL{L}_{DT}}^m$; No-load loss of $m^{th}$ DT unit, $P_{RW}$; Rated WT power output, $P_{SC{L}_{DT}}^m$; Short-circuit loss of $m^{th}$ DT unit, $P_{SST}$; Real power supplied by the stage-III inverters, $P_{WT}$; WT power output, $Q_{SSTD,k}(t)$; Local, stage-III RPA at bus $k$ for hour $t$, $Q_{SSTD}$; Local reactive power demand on the SST, $Q_{SSTG,k}(t)$; Grid RPA at bus $k$ for hour $t$, $S^m$; Rated capacity of $m^{th}$ DT unit, $S_{SI,k}(t)$; Stage-I converter rating for hour $t$, $S_{SS{T}_{bnd}}$; Total installed SST capacity, $S_{SST}$; SST’s apparent power capacity, $S_{SST}^{lim}$; Each SST’s capacity rating, $S_L$; Load rating of a load bus, $v_{cin}$; Cut-in wind speed, $v_{cout}$; cutoff wind speed, $V_{Min,k}$; Minimum voltage magnitude at bus $k$, $v_r$; Rated wind speed, $V_{ref}$; Reference voltage.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Notes on contributors

Amaresh Gantayet

Amaresh Gantayet was born in Bhubaneswar, Odisha, India. He received the B. Tech. degree in electrical engineering from Biju Patnaik University of Technology, Rourkela, India in 2009 and the M. Tech. in electrical engineering from the Indian Institute of Technology Kharagpur, India in 2013. He joined the department of electrical and electronics engineering, Siksha ‘O’ Anusandhan, Deemed to be University, Bhubaneswar, India, as an Assistant Professor in 2013. He is currently working toward a Ph.D. degree with the department of electrical engineering at the National Institute of Technology Patna, India. His current research interests include electric power distribution systems, distributed generation, and demand-side management.

Dharmendra Kumar Dheer

Dr. Dharmendra Kumar Dheer was born in Bhagalpur, Bihar, India. He received his B.Sc. Engineering degree in electrical engineering from Muzaffarpur Institute of Technology, Muzaffarpur, India, in 2007, his M.Tech. degree in electrical engineering with a specialization in power system engineering from the Indian Institute of Technology Kharagpur, India, in 2010, and his Ph.D. degree in power and energy systems engineering from the department of energy science and engineering, Indian Institute of Technology Bombay, Mumbai, India, in 2017. Currently, he is serving as an assistant professor in the department of electrical engineering at the National Institute of Technology Patna, India. He has one and a half years of teaching experience after receiving his M.Tech. degree, six months of research experience as a research associate at IIT Bombay and five and a half months of research experience as a postdoctoral researcher at Arizona State University (ASU), USA. His current research interests include stability and control of microgrids, stability aspects of conventional power systems, electric power distribution systems, and solar photovoltaic.