Severe and long-lasting power shortages plague many developing countries and result in blackouts, the occurrence and duration of which are escalating; thus an efficient mitigation solution is much sought after. In the paper a distributed agentbased power aggregation and demand appeasement system for managing domestic demand during chronic cyclic blackouts is presented. Air conditioning appliances are dynamically grouped into adaptive clusters powered through the aggregation of superfluous power available from scattered standby generators while basic set appliances are powered from the rationed utility supply. The proposed approach was preceded by a field survey and implemented on the DDSM-IDEA platform, a development environment specially designed for this purpose. Simulation shows that the proposed solution provides an acceptable Qualityof-Service (QoS) level at minimum cost penalty. The solution is proven to be flexible and effective.
-Many countries around the world are challenged to meet the escalating demand for power often resulting in frequent blackouts. Domestic standby generation and associated running costs are prohibitive and novel strategies to provision measures that manage blackouts are becoming much sought after. Almost all installed standby generation is not fully utilized and certain amounts of surplus power can be identified. The paper presents a strategy that harnesses the aggregated standby superfluous power to fulfil essential demand in residential areas during cyclic blackouts covering wide areas. The solution has at its foundation, a multiagent distributed demand management system with a supplydemand matching capability. Environmental conditions are monitored periodically and power is distributed accordingly to each sub-district. Customers at sub-districts receive a share of power according to two different distribution criteria and although their immediate allocated power is not the same, their overall daily power ration is equal. Air conditioners are backed up with less power demanding counterparts and a group of options is adaptively clustered. Their usage rights are distributed among customers according to available superfluous power. The approach is evaluated through an extensive emulation framework and results show that the proposed system is capable of providing an acceptable Quality-of-Service (QoS) level during cyclic blackout periods.
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