Optimal Planning models and algorithms for Distribution Network containing Renewable DGs, ESS and DNR considering the Reliability and Costs -- 2

Job ID: 30690453

Budget: $30 – $250 USD

Scenarios:
1. Optimal allocation of solar and wind based DGs (maybe add other type) for 33-118-node Distribution Networks considering the Reliability and Costs. (without time considering and with 24 h planning horizon)
2. Optimal allocation of Energy storage system for 33-118-node Distribution Networks considering the Reliability and Costs. (without time considering and with 24 h planning horizon)
3. Optimal Distribution Network Reconfiguration for 33-118-node Distribution Networks considering the Reliability and Costs. (without time considering and with 24 h planning horizon)
4. Simulation in the same time above three simulation for 33-118-node Distribution Networks considering the Reliability and Costs. (without time considering and with 24 h planning horizon).
a) First, allocation DGs than DNR for 33-118-node Distribution Networks considering the Reliability and Costs. (without time considering and with 24 h planning horizon).
b) Second, DNR than DGS and ESS allocation or new idea from you for 33-118-node Distribution Networks considering the Reliability and Costs. (without time considering and with 24 h planning horizon).
c) Third, planning in the same time all above conditions for 33-118-node Distribution Networks considering the Reliability and Costs. (without time considering and with 24 h planning horizon).
Requirements:.
1) Need to all power flow simulations by using backward and forward method (not using Matpower or like that)
2) Need to use newer multi-objective metaheuristic optimization (at least two for fair compression) techniques (not use CPLEX or other like that tools). To find better solution need to use fuzzy or pareto analysis (maybe like this analysis)
3) You must provide all Matlab mfile codes (if customer meet problem while running code you need help to him/her to solve that problem and understand the codes).