Optimal economic dispatch of FC-CHP based heat and power micro-grids

• Published in: Applied thermal engineering 2017-03, Vol.114, p.756-769
• Main Authors: Nazari-Heris, Morteza, Abapour, Saeed, Mohammadi-Ivatloo, Behnam
• Format: Article
• Language: English
• Subjects: Batteries; Boilers; Cogeneration; Combined heat and power (CHP); Cost engineering; Demand; Demand response (DR) program; Distributed generation; Economic dispatch; Electric power demand; Electric power grids; Electrical loads; Electricity consumption; Electricity generation; Emissions control; Energy management; Energy storage; Fuel cell; Heat and power micro-grid (MG); Multiple objective analysis; Optimization; Power dispatch; Scheduling; Storage devices; Storage systems; Studies; Time of use electricity pricing; ε-Constraint method
• ISSN: 1359-4311; 1873-5606
• DOI: 10.1016/j.applthermaleng.2016.12.016

•The multi objective economic/environmental heat and power MG dispatch is solved.•The heat and power MG include FC, CHP, boiler, storage system, and heat buffer tank.•Multi objective scheduling of heat and power MG is solved using ε-constraint method.•DR program is employed in the stochastic programming of heat and power MG dispatch.•The uncertainties for load demand and price signals are taken into account. Micro-grids (MGs) are introduced as a solution for distributed energy resource (DER) units and energy storage systems (ESSs) to participate in providing the required electricity demand of controllable and non-controllable loads. In this paper, the authors study the short-term scheduling of grid-connected industrial heat and power MG which contains a fuel cell (FC) unit, combined heat and power (CHP) generation units, power-only unit, boiler, battery storage system, and heat buffer tank. The paper is aimed to solve the multi-objective MG dispatch problem containing cost and emission minimization with the considerations of demand response program and uncertainties. A probabilistic framework based on a scenario method, which is considered for load demand and price signals, is employed to overcome the uncertainties in the optimal energy management of the MG. In order to reduce operational cost, time-of-use rates of demand response programs have been modeled, and the effects of such programs on the load profile have been discussed. To solve the multi-objective optimization problem, the ε-constraint method is used and a fuzzy satisfying approach has been employed to select the best compromise solution. Three cases are studied in this research to confirm the performance of the proposed method: islanded mode, grid-connected mode, and the impact of time of the use-demand response program on MG scheduling.