Transmission Expansion Planning in Deregulated Power Systems

• Main Author: Oloomi Buygi, Majid
• Format: Others
• Language: English; en
• Published: 2004
• Online Access: https://tuprints.ulb.tu-darmstadt.de/486/1/PhD_Thesis_Oloomi.pdf; Oloomi Buygi, Majid <http://tuprints.ulb.tu-darmstadt.de/view/person/Oloomi_Buygi=3AMajid=3A=3A.html> (2004): Transmission Expansion Planning in Deregulated Power Systems.Darmstadt, Technische Universität, [Online-Edition: http://elib.tu-darmstadt.de/diss/000486 <http://elib.tu-darmstadt.de/diss/000486> <official_url>],[Ph.D. Thesis]

The main goal of this thesis is to present a centralized static approach for transmission expansion planning in deregulated power systems. Restructuring and deregulation have unbundled the roles of network stakeholders. They exposed transmission planner to the new objectives and uncertainties. Unbundling the roles has brought new challenges for stakeholders. In these environments, stakeholders have different desires and expectations from the performance and expansion of the system. Therefore, new incentives and disincentives have emerged regarding transmission expansion decisions. This research work is involving with considering new objectives and uncertainties in transmission expansion planning. This research work is handled in six main parts. In the first part a probabilistic tool is presented for analyzing the performance of electric markets. In this part probability density function of locational marginal prices are computed for analysis electric market. The approach was applied to an 8-bus network. The effects of load curtailment and wheeling power on nodal prices were studied. The study shows 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, two market based criteria are presented to measure how much an expansion plan facilitates and promotes competition. The criteria are “average congestion cost” and “weighted standard deviation of mean of locational marginal prices”. Different weights are 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 are extended in order to consider transmission expansion costs. In the third part of the work, a transmission expansion planning approach is presented for deregulated environments. This approach consists of scenario technique and probabilistic optimal power flow which was presented in the first part. Scenario technique is used to take into account the non-random uncertainties. Probabilistic optimal power flow is 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 is 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. The conventional risk assessment has some drawbacks. In the fourth part, drawbacks of scenario technique criteria are pointed out. New criteria are defined for the scenario technique. Fuzzy multi criteria decision making is 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. 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 is 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 is used for taking into account the desires of all stakeholders. A fuzzy appropriateness index is defined for measuring the goodness of expansion plans. The 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 is extended to consider stakeholders’ desires under non-random uncertainties. Fuzzy appropriateness index is defined to measure the goodness of each expansion plan in each scenario with considering the stakeholders’ desires. Fuzzy regret is defined with considering the occurrence degrees of future scenarios. Fuzzy regret of plan k in scenario l is equal to difference between the fuzzy appropriateness index of plan k in scenario l and fuzzy appropriateness index of optimal plan of scenario l. Fuzzy risk assessment is used to find the final plan. The steps of planning were described in details by applying the approach to an eight bus system. The following results were obtained from the simulation. The criteria “average congestion cost” and “weighted standard deviation of mean of locational marginal prices” with the weight “sum of mean of generation and load” are the best criteria for providing a competitive electric market. “Average congestion cost” is more insensitive that other criteria to the occurrence degrees of future scenarios. Fuzzy risk assessment overcomes the shortcomings of conventional risk assessment method. The presented approach selects the final plan by compromising between stakeholders’ desires.