Demand-side management framework for deregulated electricity markets
| dc.creator | Ngondya, Daniel John | |
| dc.date | 2019-06-07T05:43:25Z | |
| dc.date | 2019-06-07T05:43:25Z | |
| dc.date | 2018-07 | |
| dc.date.accessioned | 2022-10-25T09:15:30Z | |
| dc.date.available | 2022-10-25T09:15:30Z | |
| dc.description | A Dissertation Submitted in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy in Information and Communication Science and Engineering of the Nelson Mandela African Institution of Science and Technology | |
| dc.description | Stability and reliability of electricity grids are at stake because of demand growth rate outstripping supply, aging of transmission and distribution infrastructure, and the energy sector globally is fast moving towards incorporating green sources of energy into national grids in order to stabilize and make the grid more reliable. These challenges have compelled researchers from various sectors to envisage a modern grid capable of autonomously managing demand, particularly where there is potential for reduction or shifting demand. Earlier efforts on demand side management of electricity focused on industrial and commercial consumers. However, residential demand side management programs are gaining popularity because of decreasing cost of smart meters, coupled with the fact that residences represent the fastest growing demand and have strongest potential for load reduction or shifting during peak hours. Works on residential demand side management have largely assumed a single utility supplying electricity to a number of consumers. Deregulation of the electricity sector such that multiple utilities offer services, has a potential to improve efficiency and provide value-added services to consumers. This study has developed a framework of interactions among utilities and between utilities and residential consumers aiming at improving grid reliability and stability. Using soft-systems methodology, models for interaction among utilities and between utilities and residential consumers were developed and evaluated using simulations. Interactions among utilities have been modelled as a Potluck Problem with non-rational learning so as to establish equilibrium demand and supply, taking into account past consumption patterns. Interactions between utility and consumers have been modeled and simulated using token-based scheduling so as to ensure equity and guaranteed access to shared power capacity established from interactions among utilities. Simulation of interactions and validation using actual consumption information indicates reduced variability between demand and supply with Mean Absolute Percentage Error of 5-33% and Peak Average Ratio of up to 27.7% . Consumers can discretionarily shift their demand at peak hours and save up to 16.6% of electricity cost. Coordinated use of green energy sources on the consumer side can reduce by up to 23.4% of potential reverse peaks, thereby decreasing loads dropped because of power capacity constraints. Developing countries characterized by insufficient generation, demand growth outstripping available supply and limited access to electricity have an opportunity to sustainably improve stability and reliability of their grids through the use of demand management programs and therefore may not need to solely rely on investment in new a generation. | |
| dc.format | application/pdf | |
| dc.identifier | http://dspace.nm-aist.ac.tz/handle/123456789/301 | |
| dc.identifier.uri | http://hdl.handle.net/123456789/94537 | |
| dc.language | en_US | |
| dc.publisher | NM-AIST | |
| dc.subject | Demand Side Management | |
| dc.subject | Green-Aware Scheduling | |
| dc.subject | Demand-Supply Variability | |
| dc.subject | Deregulated Electricity Market | |
| dc.subject | Potluck Problem | |
| dc.title | Demand-side management framework for deregulated electricity markets | |
| dc.type | Thesis |