This paper presents the development of an energy management system (EMS) for a water pumping system with the objective of minimizing energy costs, demand charges, and life cycle maintenance costs. A novel power consumption model is developed for the pumps using data generated from PSCAD simulations, wherein pump power consumption data is obtained as the rotational speed is reduced using variable speed drive control. Considering a linear relationship between the centrifugal pump's rotational speed and flow rate, a neural network is trained to estimate the power consumption as a function of the output flow rate. This model is included in the EMS to determine the optimal load schedule and optimal pump operations. Simulation results indicate potential savings on energy cost and demand charges as the pumps' operational schedules and flow rates are optimized, and also the life cycle costs and reliability can be improved by minimizing number of startups.
[1]
G. Dalmaz.
Variable Speed Pumping: A Guide to Successful Applications
,
2002
.
[2]
Christian von Lücken,et al.
Multi-objective pump scheduling optimisation using evolutionary strategies
,
2005,
Adv. Eng. Softw..
[3]
Kankar Bhattacharya,et al.
Optimal Operation of Industrial Energy Hubs in Smart Grids
,
2015,
IEEE Transactions on Smart Grid.
[4]
Melvin Neufeld,et al.
A comparative study of fixed speed vs. variable speed control of a series configured pipeline pumping application
,
2014,
2014 IEEE Petroleum and Chemical Industry Technical Conference (PCIC).
[5]
Hamed Mohsenian Rad,et al.
Optimal Industrial Load Control in Smart Grid
,
2016,
IEEE Transactions on Smart Grid.