Power shortage is a serious issue especially in developing nations. Such power deficits are traditionally handled through rolling blackouts - a service area is divided into subareas, each of which is denied power during a designated time in the day. Today, smart grids provide the opportunity of avoiding complete blackouts, converting them to brownouts which allow selective provisioning of power supply to support essential loads while curtailing supply to less critical loads. We formulate the brownout based power distribution problem as an integer linear programming (ILP) and show that solution strategies such as conventional dynamic programming (DP) impose substantial overheads. So, we propose the streamlined DP-based priority level allocator (SDPA) which utilizes the discrete nature of power demands of each subarea and generates the overall optimal solution far quicker by focusing on a lower number of non-dominating partial DP-solutions. SDPA is found to be about 9 to 33 times faster than DP and applicable to real-time brown-out based power distribution in moderate sized grids. However, even SDPA may fail to meet the real-time requirements of dynamic power imbalance mitigation in very large grids. So, a fast yet effective power adjustment approach namely, Proportionally Balanced Priority level Allocator (PBPA) , has been designed and implemented. Experimental results show that although solutions provided by PBPA could be less effective by upto 12 percent compared to optimal dynamic programming based schemes, being about 4 orders of magnitude faster, it can be deployed for real time allocations of power.