Abstract
This article introduces a robust optimal week-ahead generation scheduling approach that takes into account plug in hybrid electric vehicles (PHEVs) considering uncertainty in loads, renewable energy resources, and PHEV charging behavior. Due to the complexity of the scheduling process there is crucial need for a reliable optimal algorithm. The proposed approach can be applied in energy management platforms of decarbonized eco-friendly power systems. Generation scheduling is modeled as a multi-objective optimization problem: (a) minimize generation production cost and (b) minimize emission costs. The focal concern is to (a) handle the scheduling of renewable energy resources against their volatilities, (b) integrating PHEVs with uncertainties related to their state of charge, and (c) stochastic load behavior over a whole week. Two heuristic-based algorithms are used to solve the optimization problem, namely Water Cycle Algorithm and Gravitational Search Algorithm The proposed scheduling approach is implemented in MATLAB Ⓡ Platform, and is tested using two different microgrids sizes, 3 generator, and 10 generator unit systems integrating the effect of week days profile, renewable energy intermittency and different PHEV state of charges using the IEEE Reliability Test System (RTS) data. The results show promising performance of GSA over the WCA in the energy management studies integrating three different types of sources; thermal units, Renewable Energy Resources (RERs), and the PHEVs.
Highlights
De-carbonization is a vital enticement behind most of the power system operation and planning studies
Dmax is the operational cost coefficient of the batteries of plug in hybrid electric vehicles (PHEVs) is the maintenance cost coefficient of the batteries of PHEVs The vehicle battery efficiency number of connected vehicles hour ‘‘i’’ the total available number of vehicles number of units that are on in the unit commitment problem at each hour is the total number of thermal generators is the number of periods in hours that each unit ‘‘i is still off until certain time ‘‘hour’’. is the time of cold startup is a linear cost function’s coefficient of wind and solar plants at each hour
This article introduced a comprehensive model for weekly generation scheduling of small scale systems taking into account (a) PHEV, (b) wind/solar resources intermittency, and (c) load variability
Summary
Dmax is the operational cost coefficient of the batteries of PHEVs is the maintenance cost coefficient of the batteries of PHEVs The vehicle battery efficiency number of connected vehicles hour ‘‘i’’ the total available number of vehicles number of units that are on in the unit commitment problem at each hour is the total number of thermal generators is the number of periods in hours that each unit ‘‘i is still off until certain time ‘‘hour’’. Are the hours that the unit is on or off respectively until time period ‘‘t’’. The present state of charge (PSOC) a single solution in an array of 1 × Nvar in the WCA the number of streams that travel towards certain rivers or the sea in the WCA. Are the hours that the unit is on or off respectively until time period ‘‘t’’. the present state of charge (PSOC) a single solution in an array of 1 × Nvar in the WCA the number of streams that travel towards certain rivers or the sea in the WCA. the number of population in the WCA. the summation of the number of rivers in the WCA a small number and its value is near to zero in the WCA
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