9 Conclusions 110 the effects of load curtailment and wheeling power on nodal prices were studied. The study shows that wheeling transactions affect the locational marginal prices of the control area which transmit through them. It also shows that making wheeling transaction in proper directions can reduce the transmission congestion and postpone transmission expansion. In the second part, requirements of competitive markets were discussed. In competitive markets there is no price discrimination among producers and consumers. In this market customers do not have any restriction to buy from any producer. To have a competitive electric market, the above conditions must be satisfied. On the other word, locational marginal prices must be made equal at all buses and transmission congestion must be alleviated. Based on theses conditions, two market based criteria were presented to measure how much an expansion plan facilitates competition. The criteria are “average congestion cost” and “weighted standard deviation of mean of locational marginal prices”. Different weights were used in order to provide a competitive environment for more power system participants. Justification of costs is very important in competitive environments. Therefore the presented criteria were extended in order to consider transmission expansion costs. In the third part of the work, a transmission expansion planning approach was presented for deregulated environments. This approach consists of scenario technique and probabilistic optimal power flow which was presented in the first part. Scenario technique was used to take into account the non-random uncertainties. Probabilistic optimal power flow was used to consider the random uncertainties. The approach uses the market based criteria to measure the goodness of expansion plans. Market based criteria provide a non-discriminatory competitive environment for stakeholders. Minimax regret criterion was used in scenario technique for risk assessment and selecting the final plan. To determine which criterion leads to zero congestion cost and flat price profile at minimum cost or at minimum number of expansion plans, the presented approach was applied on IEEE 30 bus test system. Two different cases were considered. In case A, it was assumed that there is not any non-random uncertainty. The result of simulation shows that “average congestion cost” is a more efficient criterion than others if there is not any non-random uncertainty. In case B, it was assumed that there is nonrandom uncertainty. Eight different scenarios were defined to cover all non-random uncertainties. The result of simulation shows that “weighted standard deviation of mean of locational marginal prices” with the weight “sum of mean of generation and load” is as efficient as “average congestion cost” in multi scenario cases. The sensitivity analysis shows that “average congestion cost” is less insensitive than other criteria to the occurrence degrees
9 Conclusions 111 of future scenarios. Conventional risk assessment has some drawbacks. In the fourth part, drawbacks of scenario technique criteria were pointed out. New criteria were presented for the scenario technique including degree of robustness of order 1-5. Fuzzy multi criteria decision making was used for the risk assessment of solutions. In this method a fuzzy appropriateness index is defined for selecting the final plan. The fuzzy appropriateness index is computed by aggregation of importance degrees of decision criteria and appropriateness degrees of expansion plans versus decision criteria. The presented approach is applied to IEEE 30 bus test system and the result was compared with conventional risk assessment in different cases. The comparison shows that fuzzy risk assessment overcomes the shortcomings of conventional risk assessment method. In the fifth part of the work, a transmission expansion planning approach with consideration given to stakeholders’ desires was presented. The approach considers the desires of demand customers, power producers, network owner(s), system operator, and regulator in transmission expansion planning. Stakeholders’ desires can be sought in competition, reliability, flexibility, network charge and environmental impacts. Fuzzy decision making was used for taking into account the desires of all stakeholders. A fuzzy appropriateness index is defined for measuring the goodness of expansion plans. The fuzzy appropriateness index is defined by aggregating importance weights of stakeholders in decision making, importance degrees of stakeholders’ desires from the viewpoint of different stakeholders, and appropriateness degrees of expansion plans versus stakeholders’ desires. The approach was applied to IEEE 30 bus test systems to find the plan which compromise between stakeholders’ desires. The presented approach in the fifth part can not consider non-random uncertainties. In the sixth part, the presented approach was extended to consider stakeholders’ desires under nonrandom uncertainties. The fuzzy appropriateness index, which is defined in part five for measuring the goodness of expansion plans, is computed for each expansion plan in each scenario. Fuzzy regret was defined with considering the occurrence degrees of future scenarios. Fuzzy risk assessment was used to find the final plan. The steps of planning were described in details by applying the approach to an eight bus system.