Multi-objective dynamic generation and transmission expansion planning considering capacitor bank allocation and demand response program constrained to flexible-securable clean energy

Abstract This paper presents the dynamic generation and transmission expansion planning considering switched capacitor bank allocation and demand response program. This scheme is in the form of four-objective optimization to supply flexible-securable and highly reliable energy. The scheme minimizes the planning costs, expected pollution, expected energy not-supplied, and voltage security index in separate objective functions. It is constrained to network AC power flow equations, operation, reliability, flexibility, network voltage security constraints, capacitor planning model, and demand response operating formulation. Then, the e constraint-based Pareto optimization technique obtains a single-objective model for the proposed scheme. The unscented transformation method models the uncertainties of load, renewable power, and network equipment availability. To achieve an optimal solution including a low standard deviation in the final response, a hybrid meta-heuristic algorithm is used. This solver is based on merging the firefly algorithm and harmonic search algorithm. Eventually, the scheme is applied to IEEE 6-bus and 118-bus transmission networks. Then, the numerical results confirm the capability of the proposed strategy in improving the operation, reliability, security, and flexibility of the network, as well as enhancing the economic and environmental status.

[1]  Jasbir S. Arora,et al.  Survey of multi-objective optimization methods for engineering , 2004 .

[2]  Majid Moazzami,et al.  Advanced model for joint generation and transmission expansion planning including reactive power and security constraints of the network integrated with wind turbine , 2019 .

[3]  Sasan Pirouzi,et al.  Conjugate active and reactive power management in a smart distribution network through electric vehicles: A mixed integer-linear programming model , 2020 .

[4]  Ali Reza Abbasi,et al.  Investigation of simultaneous effect of demand response and load uncertainty on distribution feeder reconfiguration , 2020, IET Generation, Transmission & Distribution.

[5]  Taher Niknam,et al.  Flexible, reliable, and renewable power system resource expansion planning considering energy storage systems and demand response programs , 2019, IET Renewable Power Generation.

[6]  Wei Lee Woon,et al.  Optimal Protection Coordination for Microgrids With Grid-Connected and Islanded Capability , 2012 .

[7]  Pedro Gazmuri,et al.  An Adaptive Robust Optimization Model for Power Systems Planning with Operational Uncertainty , 2020, 2020 IEEE Power & Energy Society General Meeting (PESGM).

[8]  Hamid Parvin,et al.  Probabilistic planning of the active and reactive power sources constrained to securable-reliable operation in reconfigurable smart distribution networks , 2021 .

[9]  Mohammad Shahidehpour,et al.  Aggregated Model of Data Network for the Provision of Demand Response in Generation and Transmission Expansion Planning , 2021, IEEE Transactions on Smart Grid.

[10]  Ali Reza Seifi,et al.  A Novel Method Mixed Power Flow in Transmission and Distribution Systems by Using Master-Slave Splitting Method , 2008 .

[11]  Akbar Maleki,et al.  Optimal sizing of a PV/wind/diesel system with battery storage for electrification to an off-grid remote region: A case study of Rafsanjan, Iran , 2014 .

[12]  Amin Kargarian,et al.  Risk-based dynamic generation and transmission expansion planning with propagating effects of contingencies , 2020 .

[13]  Ali Reza Abbasi,et al.  Application of statistical control charts to discriminate transformer winding defects , 2021 .

[14]  Abdollah Kavousi-Fard,et al.  A novel adaptive modified harmony search algorithm to solve multi-objective environmental/economic dispatch , 2014, J. Intell. Fuzzy Syst..

[15]  Nnamdi I. Nwulu,et al.  A multi-period composite generation and transmission expansion planning model incorporating renewable energy sources and demand response , 2020 .

[16]  Enzo Sauma,et al.  Reliable Renewable Generation and Transmission Expansion Planning: Co-Optimizing System's Resources for Meeting Renewable Targets , 2017, IEEE Transactions on Power Systems.

[17]  Abdollah Kavousi-Fard,et al.  An smart stochastic approach to model plug-in hybrid electric vehicles charging effect in the optimal operation of micro-grids , 2015, J. Intell. Fuzzy Syst..

[18]  Ali Reza Abbasi,et al.  Tight convex relaxation for TEP problem: a multiparametric disaggregation approach , 2020, IET Generation, Transmission & Distribution.

[19]  Joao P. S. Catalao,et al.  Hybrid stochastic/robust optimization model for resilient architecture of distribution networks against extreme weather conditions , 2021 .

[20]  Ali Reza Abbasi,et al.  Efficient linear network model for TEP based on piecewise McCormick relaxation , 2019, IET Generation, Transmission & Distribution.

[21]  Carlos Henggeler Antunes,et al.  Interactive MOLP explorer—A graphical‐based computational tool for teaching and decision support in multi‐objective linear programming models , 2015, Comput. Appl. Eng. Educ..

[22]  Mahdi Pourakbari-Kasmaei,et al.  A Demand-Side Management-Based Model for G&TEP Problem Considering FSC Allocation , 2019, IEEE Systems Journal.

[23]  Alireza Abbasi,et al.  Consideration effect of wind farms on the network reconfiguration in the distribution systems in an uncertain environment , 2017, J. Exp. Theor. Artif. Intell..

[24]  Matti Lehtonen,et al.  Hybrid stochastic/robust scheduling of the grid-connected microgrid based on the linear coordinated power management strategy , 2020 .

[25]  Mojtaba Shivaie,et al.  A vulnerability-constrained quad-level model for coordination of generation and transmission expansion planning under seismic- and terrorist-induced events , 2020 .

[26]  Taher Niknam,et al.  Integrated resource expansion planning of wind integrated power systems considering demand response programmes , 2019, IET Renewable Power Generation.

[27]  Baljit Singh Khehra,et al.  Teaching-learning-based optimization algorithm to minimize cross entropy for Selecting multilevel threshold values , 2019, Egyptian Informatics Journal.

[28]  Kun Zhang,et al.  Reliability-Constrained AC Power Flow-Based Co-Optimization Planning of Generation and Transmission Systems With Uncertainties , 2020, IEEE Access.

[29]  Matti Lehtonen,et al.  Security-Constrained generation and transmission expansion planning based on optimal bidding in the energy and reserve markets , 2021 .

[30]  Soumya Das,et al.  Security constrained AC transmission network expansion planning , 2018, Electric Power Systems Research.

[31]  Tao Ma,et al.  Performance comparison of heuristic algorithms for optimization of hybrid off-grid renewable energy systems , 2020 .

[32]  Rahmat-Allah Hooshmand,et al.  Combination of AC Transmission Expansion Planning and Reactive Power Planning in the restructured power system , 2012 .

[33]  Matti Lehtonen,et al.  Multi-objective resilient-constrained generation and transmission expansion planning against natural disasters , 2021 .

[34]  Mohamed Benbouzid,et al.  Renewable Generation and Transmission Expansion Planning Coordination with Energy Storage System: A Flexibility Point of View , 2021, Applied Sciences.

[35]  Sasan Pirouzi,et al.  Flexibility Planning of Distributed Battery Energy Storage Systems in Smart Distribution Networks , 2020, Iranian Journal of Science and Technology, Transactions of Electrical Engineering.

[36]  João Tomé Saraiva,et al.  Impact of decision-making models in Transmission Expansion Planning considering large shares of renewable energy sources , 2019, Electric Power Systems Research.

[37]  Mohammad Mehdi Arefi,et al.  Transformer Winding Faults Detection Based on Time Series Analysis , 2021, IEEE Transactions on Instrumentation and Measurement.

[38]  Nima Amjady,et al.  Generation and Transmission Expansion Planning: MILP–Based Probabilistic Model , 2014, IEEE Transactions on Power Systems.

[39]  Alireza Abbasi,et al.  Optimal placement of distributed generation in radial networks considering reliability and cost indices , 2016, J. Intell. Fuzzy Syst..

[40]  A. Abbasi.  Probabilistic Load Flow Based on Holomorphic Embedding, Kernel Density Estimator and Saddle Point Approximation Including Correlated Uncertainty Variables , 2020 .

[41]  Abbas Rabiee,et al.  Voltage stability constrained multi-objective optimal reactive power dispatch under load and wind power uncertainties: A stochastic approach , 2016 .