This paper proposes a new distribution system planning method that considers distributed generators （DG） and uncertainty risk. The authors have studied so far a similar new planning method to take into account DG installation. For practical planning，however，demand forecast and DG installation forecast should be very important factors and the uncertainty of them is becoming large due to deregulation of power industry. In our previous. study，the future demand and the DG installation were assumed to be a certain value and the effects of their uncertainty was not considered. This means that if the assumption is not appropriate，the plan will be no use and huge amount of pecuniary damage will appear. The new distribution system planning method proposed in this paper includes DG installation and risk estimation，which is induced by the uncertainty of DG installation and demand growth. Scenario-tree method is adopted to express the their uncertainties and utility function is used to express a decision-maker's feeling against the risk. This method can avoid pecuniary damage effectively at the planning stage. The proposed method is demonstrated through several numerical simulations to validate the effectiveness of the proposed method with successful results.

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Electric power demand has an increasing tendency year by year. The load power fluctuation becomes larger with the incleasing demand，thus electric power quality is getting worse. To improve the electric power quality，electric power leveling systems (EPLS's) using energy storage technology are desired to be developed. This paper proposes a new optimization method of the EPLS with superconducting magnetic energy storages (SMES's) using distributed genetic algorithms. The evaluation function in the optimization is composed of the initial costs of EPLS and the reduction cost of the electricity rate. The efficiency of the power converter in the ELPS and the effect of the reactive power compensation on the electricity rate are also taken into account. From the optimization results，installing the ELPS can achieve the cost reduction by sixteen billion yen in the SMES life. The effective optimization can be realized compared with the simple genetic algorithms. Thus，the proposed method is clarified to be valid for the optimization of the EPLS.

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