This paper presents an optimal expansion planning model for an energy hub with multiple energy systems. Energy hub represents a coupling among various energy infrastructures for supplying electricity, natural gas, and heating loads. Combined heat and power (CHP) and natural gas furnaces are considered within the energy hub to convert energy into other forms. The multiple energy system planning problem would optimally determine appropriate investment candidates for generating units, transmission lines, natural gas furnaces, and CHPs that satisfy electricity and heating load forecasts and hub system constraints. The system performances associated with reliability, energy efficiency, and emission matrices is evaluated for the identified planning schedules. Numerical simulations demonstrate the effectiveness of the proposed multiple energy system expansion planning approach based on energy hub.Index Terms-Combined heat and power (CHP), energy hubs, expansion planning, multiple energy systems (electricity, natural gas, heat).

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The optimal planning of the interconnected network of multimicrogrids is discussed in this paper. The interconnection planning will enhance the reliability and the economic operation of a community of microgrids. The proposed approach will apply a probabilistic minimal cut-set-based iterative methodology for the optimal planning of interconnection among microgrids with variable renewable energy sources. The optimal planning takes into account various factors including the economics, reliability, and variability of renewables, networkand resource-based uncertainties, and adaptability to accommodate the prevailing operating concerns. A clustering-based method is considered for analyzing the variable data concerning the potential deployment of renewable energy in microgrids. The proposed interconnection planning methodology is applied to a six-microgrid system and the planning results are discussed. The numerical results demonstrate that the proposed interconnection planning methodology will determine an optimal topology accurately and efficiently for a cluster of microgrids, and show that the proposed adaptive planning methodology can easily be applied to practical microgrid applications.Index Terms-Community microgrid, distribution network planning, microgrid planning, minimum cut-set, reliability. NOMENCLATURE VariablesC AnnPay , C Interrupt Annualized project capital payment and annual customer energy interruption cost. R i Reliability indices matrix from iteration-i. Indices and Seti Index of iteration in the proposed method. sIndex of wind state (s = 1, . . . , N s ). tIndex of time period (t = 1, . . . , N t ).

In this paper, the coordination of constrained electricity and natural gas infrastructures is considered for firming the variability of wind energy in electric power systems. The stochastic security-constrained unit commitment is applied for minimizing the expected operation cost in the day-ahead scheduling of power grid. The low cost and sustainable wind energy could substitute natural gas-fired units, which are constrained by fuel availability and emission. Also, the flexibility and quick ramping capability of natural gas units could firm the variability of wind energy. The electricity and natural gas network constraints are considered in the proposed model (referred to as EGTran) and Benders decomposition is adopted to check the natural gas network feasibility. The autoregressive moving average (ARMA) time-series model is used to simulate wind speed forecast errors in multiple Monte Carlo scenarios. Illustrative examples demonstrate the effectiveness of EGTran for firming the variable wind energy by coordinating the constrained electricity and natural gas delivery systems.Index Terms-Day-ahead scheduling, natural gas, renewable energy, stochastic security-constrained unit commitment.

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