Power Flow and ATC Estimation in modern power systems | |
| Author | M Nimal, Madhu |
| Call Number | AIT Diss. no.ET-16-05 |
| Subject(s) | Electric power systems--Control Electric lines Electric power transmission Electric power systems--Planning |
| Note | A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Engineering in Energy |
| Publisher | Asian Institute of Technology |
| Series Statement | Dissertation ; no. ET-16-05 |
| Abstract | Analysis tools for power system planning and operation, presently available, are designed based on high voltage, high inertial and dispatchable centralized generation characteristics. Many of the se assumptions used by conventional analysis methods need to be reformulated to suit the power systems with small and distributed generations (DG) that facilitate autonomous operation modes. This research focuses on formulation of analysis methods suitable for modern systems, giving due diligence to realistic modelling. In addition to the two basic analysis tools, Power flow and optimal power flow, identifying the impact of DG on the power flow and dispatch profiles, ATC estimation is also selected as the static analysis methods for discussion. A droop control incorporated distribution power flow method, applicable to low (LV) and medium voltage (MV), autonomous or non - autonomous AC microgrid systems is formulated. The solver is designed to be independent assumptions like PV, PQ and slack buses, R/X ratio, P - δ and Q - V coupling etc. treating the power flow problem as a normal optimization problem, that endeavors to minimize errors in nodal power balance. Results obtained from this solver provided better operating points in terms of voltage profile, load sharing, reduced power loss etc. in comparison to existing solvers. A power flow model solving the problem in the DC - domain, creating a DC structural equivalent of the actual system , is proposed. The algorithm also solves the power flow problem as a normal optimization problem. Apart from low and medium voltage systems, the method is found applicable to high voltage as well as hybrid AC - DC systems. From the obtained results, in addit ion to better voltage profile, load sharing , and reduced power loss, the method showed better convergence capability under increased loading and for wider R/X ratio. A risk - adjusted stochastic optimal power dispatch problem to estimate ATC from network/transmission system owner/operator perspective is discussed. Dependence of ATC on the uncertainties in renewable generation and load is assessed in an interconnected transmission - distribution system (TDS). A two - stage process is proposed to estimate ATC, min imizing the risk using stochastic weight trade - off particle swarm optimization (SWT - PSO). The proposed algorithm provided better ATC values (expected) and reduced variance of ATC deviation than the base case scenario ensuring better security and more oppor tunities for financial participation. A multi - objective (MO) formulation for estimating ATC, hedging the associated risk is formulated. Different scenarios envisaging different perspectives, like operational efficiency, self - sustenance, benefits etc. are assessed in a system with transmission interconnections and active microgrid interconnections. From the results, it could be deduced that trade - off based assessments are advisable in either single or multiple owner cases and scenario combining operational efficiency and benefit as objectives are the better option considering technical and financial aspects of the system. The new formulations proposed in this research are found suitable for modern systems, independent of their structural /network configuration, size/capacity, voltage level, R/X ratio, or autonomous/non - autonomous modes of operation, enhancing the predictability and feasibility of operation. The attributed features like processing time make them apt for planning as well as short term operation applications that also takes into account stochastic components |
| Year | 2016 |
| Corresponding Series Added Entry | Asian Institute of Technology. Dissertation ; no. ET-16-05 |
| Type | Dissertation |
| School | School of Environment, Resources, and Development (SERD) |
| Department | Department of Energy and Climate Change (Former title: Department of Energy, Environment, and Climate Change (DEECC)) |
| Academic Program/FoS | Energy Technology (ET) |
| Chairperson(s) | Singh, Jai Govind |
| Examination Committee(s) | Weerakorn Ongsakul ;Dhakal, Shobhakar ;Shrestha, Sangam |
| Scholarship Donor(s) | Asian Institute of Technology Fellowship |
| Degree | Thesis (Ph.D.) - Asian Institute of Technology, 2016 |