TY - CHAP
T1 - Combined Heat and Power Stochastic Dynamic Economic Dispatch Using Particle Swarm Optimization Considering Load and Wind Power Uncertainties
AU - Pourghasem, Pouya
AU - Sohrabi, Farnaz
AU - Jabari, Farkhondeh
AU - Mohammadi-Ivatloo, Behnam
AU - Asadi, Somayeh
N1 - Publisher Copyright:
© 2020, Springer Nature Switzerland AG.
PY - 2020
Y1 - 2020
N2 - Due to the increased cost of energy sources and related environmental problems, systems with higher efficiency such as combined heat and power (CHP) units are getting more popular. Renewable energy sources can be another alternative solution for the above mentioned problems. Scheduling of renewable-based systems are getting more complicated due to the intermittent behavior of these sources. In this chapter, a stochastic programming framework is utilized to model uncertainties in dynamic economic dispatch (DED) problem of CHP based systems integrating wind energy. Forecast errors of electrical load and wind power are assumed as the two sources of uncertainty. A heuristic method called particle swarm optimization (PSO) is used to attain optimal solution of the problem due to non-linearity, non-convexity, and complexity of the problem. The stochastic programming provides more comprehensive and realistic viewpoint about dispatch problem by considering a variety of most probable scenarios compared to a single scenario.
AB - Due to the increased cost of energy sources and related environmental problems, systems with higher efficiency such as combined heat and power (CHP) units are getting more popular. Renewable energy sources can be another alternative solution for the above mentioned problems. Scheduling of renewable-based systems are getting more complicated due to the intermittent behavior of these sources. In this chapter, a stochastic programming framework is utilized to model uncertainties in dynamic economic dispatch (DED) problem of CHP based systems integrating wind energy. Forecast errors of electrical load and wind power are assumed as the two sources of uncertainty. A heuristic method called particle swarm optimization (PSO) is used to attain optimal solution of the problem due to non-linearity, non-convexity, and complexity of the problem. The stochastic programming provides more comprehensive and realistic viewpoint about dispatch problem by considering a variety of most probable scenarios compared to a single scenario.
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U2 - 10.1007/978-3-030-34050-6_7
DO - 10.1007/978-3-030-34050-6_7
M3 - Chapter
AN - SCOPUS:85078145518
T3 - Studies in Systems, Decision and Control
SP - 143
EP - 169
BT - Studies in Systems, Decision and Control
PB - Springer
ER -