Research On Demand Side Based Transmission Congestion Management Model And Algorithm

With the growth of demand and the limitation of available transfer capability, the transmission congestion (TC) has been an inherent problem in the electricity markets. TC may lead to pike price, market power behavior and unexpected blankout, and has posed great risk to the distribution company (Disco) and the end customers. TC can be mitigated when a significant level of potential demand side response is available. Two power resources, interruptible load (IL) and distributed generation (DG), which can be used to improve the demand side responses, are modeled to alleviate TC in the dissertation. The nonlinear complementarity method, which is used to solve the model, is also presented in this paper. The main work and the key contributions of this dissertation are as follows:Firstly, owning to the ILs' character of improving market competition and demand side responses, an IL based TC management model is proposed. This model consists of a two-level optimal model. The outer optimal power flow (OPF) model is to dispatch power generation and determinate nodal prices. The inner optimal model is to determine appropriate ILs to relieve the TC. Since the curtailed load will be compensated, so both the bid of IL and its role to alleviate congestion are addressed to select IL. To avoid increasing the burden on the independent system operator (ISO) to pay IL compensation, compensation cost for IL are constrained. In addition, the compensation cost is from the merchadize surplus (MS), thus MS can not be owned by ISO and produce unproper incentive to ISO. A modified IEEE 30 bus system is used to illustrate the validity of the proposed model. It shows that the model can help ISO not only dispatch power in normal condition, but also curtail load in congestion condition. This work is one of contributions of this dissertation.Secondly, based on an interruptible load management mechanism with incentive compatibility, a novel model is proposed to solve the invalid use of IL resulted from the asymmetry of information between ISO and the customers in the electricity markets. The model includes two problems, one is the selection of IL and the other is the monetary compensation for IL. A two-level optimization model is developed to select IL. In regard to the monetary compensation problem, an incentive compatible compensation mechanism is employed. The interrupted customer's profit is maximized only when he bids his true type under this mechanism, which can encourage the customer to participate in congestion management. The nonlinear complementarity method and Monte Carlos simulation method are used to solve the model. A modified IEEE 30 bus system is employed to test the validity of the model and the methods. Obviously, mechanism with incentive compatibility has significant social and economic meaning in the market enviorments. This work is also one of the contributions of this dissertation.Thirdly, considering the price volatility poses risk to Disco, this paper presents a single-period energy acquisition model for a Disco with DG and IL in a day-ahead electricity market. Since each Disco's energy acquisition strategy is interactive, the Disco's energy acquisition strategy is modeled as a bi-level optimization problem with the upper sub-problem representing individual Discos and the lower sub-problem representing ISO. The upper sub-problem maximizes individual Discos' revenues. The lower sub-problem simulates the ISO's market cleating problem that minimizes generation costs and compensation costs for interrupting load. An 8-bus example demonstrates that the proposed model can help Discos make optimal energy purchasing plans in different constraint conditions. The roles of DG and IL are also studied in case of transmission congestion. Studies in this paper show that DG and IL can alleviate congestion, hedge the volatility of market price, and reduce Gencos' market power. Based on these results, Discos are encouraged to make full use of the two useful resources by investing on DGs and signing IL contracts with the end customers. This work is also one of the contributions of this dissertation.Fourthly, to model the actual operation condition, based on a single-period energy acquisition model mentfoned above, ramping constraints are considered in the ISO market clearing model, which makes the energy acquisition model a linked multi-period optimization problem. Since the inclusion of inter-temporal generation constraints such as ramping constraints may lead to different generation output, nodal price, and then different energy acquisition scheme from the single-period energy acquisition plan, the multi-period energy acquisition model offers insight to appropriate energy acquisition scheme. An 8-bus system demonstrates this. This work is also one of the contributions of this dissertation.Finally, this dissertation introduces the nonlinear complementarity method in the solution of two-level optimal problem. The proposed method involves gathering the Karush-Kuhn-Tucker conditions of the inner optimal model to form a mixed nonlinear complementarity problem (NCP). Using a special nonlinear complementarity function, the NCP is formulated as a set of nonlinear algebraic equations. Those equations are used as the constraints of the outer optimal model, Repeating the transform process to the outer optimal model and then solving all nonlinear algebraic equations to obtain the solution of the two-level optimal model. The examples demonstrate that this method provides an efficient way to the solution of the large-scale complicated optimal models.