# Coordinated Scheduling of Power and Natural Gas Systems Considering Demand Uncertainty

## Nik Payam, Hossein | 2016

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1. Type of Document: M.Sc. Thesis
2. Language: Farsi
3. Document No: 49421 (01)
4. University: Sharif University of Technology
5. Department: Industrial Engineering
7. Abstract:
8. The everyday increasing electricity consumption of household and industrial sectors across the world, and also the limited generation capacity and fuel supplies has led electricity companies, whether in private or government sectors, to focus deliberately on power generation planning, its costs, risks and constraints Because of many reasons including high efficiency, low cost of capital investment, expeditious permitting, and operation flexibility of gas-fired generating units, electricity companies prefer them to old ones like coal-fired or oil-fired generating units. Thus natural gas has gained a significant share in the portfolio of electricity generation fuel resources, and it is increasing every day. Subsequently, with the growing interaction among electricity and natural gas systems, limitations on the fuel delivery are becoming increasingly relevant to the operation of power systems. In this paper we propose two models for coordinated planning of power and natural gas systems, as a part of electricity supply chain. The first one assumes that demand for both electricity and natural gas is known and deterministic; This model takes into account costs and constraints of both systems, and with hiring simplifications and linearization methods transforms initially nonlinear formulation to a mixed integer linear programming (MILP) problem. Natural gas would be assumed steady state, and the nonlinear Weymouth equation is linearized using a piecewise linear function. The assumed electricity network model, as a linearization of AC power flow, would be DC power flow. As it will be shown, these assumptions will combine computational simplicity with an acceptable level of accuracy; this quality makes this model applicable to, and suitable for large real size problems of this kind. The second model discusses the problem of coordinated scheduling of power and natural gas systems in the presence of demand uncertainty for both systems. The general Robust Optimization notion will be used to deal with natural gas demand uncertainty in its corresponding constraint, and with a two-stage Adaptive Robust Optimization approach, that is based on the nature of decision making in the real world problems of this kind, will solve the whole model. The solutions of the proposed model are robust against all possible realizations of the modeled uncertainty. Comparing with conventional Stochastic Programming approachs, this model is more practical in that it only requires a deterministic uncertainty set, rather than a hard-to-obtain probability distribution on the uncertain data
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