Muhammad Humayun

Utilization Improvement of Transformers Using Demand Response

Due to load growth, aging infrastructure, and a competitive environment, innovative solutions are required by electrical utilities to enhance the utilization of transformers which are cost intensive. This paper proposes a demand response optimization model based on transformer hottest-spot temperature. The optimization model quantifies the improvement of transformer utilization through DR. The proposed model is applied to a typical Finnish residential primary and secondary distribution transformers for case studies of load with and without DR. The results show that the loading on the transformers can be significantly increased without sacrificing the life of transformers. The gain in utilization depends on the DR capability of the load. Significant monetary benefits can be achieved with the deployment of the proposed model in a real system.

Demand Response for Operational Life Extension and Efficient Capacity Utilization of Power Transformers During Contingencies

Severe overloads, caused by the outage of units in multi-transformer substations, may affect transformer life adversely. This paper presents a novel demand response (DR) based optimization model to limit load on healthy transformers during contingencies. The model selects combination of the best remedial actions among DR, load curtailment (LC) and transferring load to a neighboring substation. IEEE standard thermal and aging models are used for transformer loss-of-life (LOL) calculation. For a realistic study, the proposed model is applied to a Finnish residential two-transformer primary substation for case studies of load with and without DR. The load profile and flexibility of the demand are estimated by hourly metered consumption and survey data. Simulations are performed for two situations depending upon availability of connection with a neighboring substation. The results show that the LOL of transformers can be reduced by employing DR following contingency events and the capacity utilization can be increased correspondingly.

MAS-Based Modeling of Active Distribution Network: The Simulation of Emerging Behaviors

Agent-based modeling of active distribution network helps to understand the dynamics and to design the control strategies for overall system efficiency. There is, however, a lack of generic and multipurpose agent definitions in existing studies. In this paper, a multi-agent system-based modeling of an active distribution network is presented using cooperative agents. A method to solve a network-wise objective of state estimation is explained with the proposed model. The network component agents are defined to be cooperative to meet the overall objectives and greedy to fulfil individual objectives such as energy cost minimization. A token-ring protocol is deployed for the agent communication among themselves, as well as with market and network operator agents. Furthermore, a MATLAB/Simulink model of active distribution network is used to simulate the emerging stochastic loading scenario, while the autonomous prosumer agents optimize their total energy cost responding to market price variations.

Optimal use of demand response for lifesaving and efficient capacity utilization of power transformers during contingencies

Contingencies of transformers in a multi-unit substation may affect life of healthy units severely due to overloads. This paper proposes a novel demand response (DR) and dynamic thermal rating (DTR) based optimization model for efficient capacity utilization and life management of transformers during contingencies. The model opts for the optimal combination of corrective actions among load curtailment (LC), DR, and shifting load to an adjacent substation while maintaining the winding hot-spot-temperature (HST) under a predefined limit. Simulations are performed, on a typical Finnish two-transformer primary distribution substation as a test system, for case studies of demand with and without DR & two situations based on availability of neighboring substation connection. The obtained results indicate that the proposed model offers substantial benefits of life-saving and utilization improvement for transformers present in different ambient conditions.

Block-Layer Reliability Method for Distribution Systems Under Various Operating Scenarios

This paper formulates a block-layer method for the reliability assessment of distribution systems. The characteristics of the method include: 1) identifying the impact of distribution component reliability on the system and load points using a block-layer structured assessment; 2) incorporating time-dependent failure parameters; and 3) taking account of the topological, seasonal, and meteorological features of the distribution systems under analysis. The proposed method first identifies the three critical parts of the distribution system: main supply, feeder, and secondary substation. It can also include reserve connections and distributed generation. Second, the method frames these parts into the layered structure, each corresponding to the zone of total load curtailment. To verify this reliability technique, this paper simulates distribution feeders assembled in a number of topologies and compares them with the state sampling technique. Data provided by the local utility company are processed to model the equipment and load for the base year. The results show that the proposed method can provide a wide range of partial and system indices. These values assist in the identification of parts of the distribution system and scenarios with low reliability and to determine possible remedial actions.