Transmission Network Planning Based On Biogeography-based Optimization

Transmission network planning, which plans transmission system according to power system load forecast and power planning, plays a critical role in power system planning. It is relatively difficult to solve Transmission network planning because of its high decision variable dimension and complex constraint condition.At present, there are many artificial intelligence algorithms which are being used to solve transmission network planning. However, we have not got a established ideal one. Biogeography-based optimization (BBO), which simulates the natural migration phenomenon, and ecology evolutionary algorithm of food chain (EEAFC), which simulates energy transmission phenomenon, are applied to solve transmission network planning problem. Tests are performed on18-bus system and19-bus system so as to comprehensively analyze abilities of algorithms under various mechanisms.1) Find that cosine migration model works best for transmission network planning through comparing the optimization abilities of different migration models.2) Tests optimization abilities of BBO based on different initial parameters show that it depends on initial parameters little because of its different biological incentive mechanism.3) Taking example by simulated annealing(SA) and other intelligence algorithms fusion, SA is proposed to improve BBO's convergence speed.4) A real number encoding method, which adopts the lines as the decision variables and the serial number of the planning stage as the search domain, is proposed and multisage optimal planning of the transmission network is transformed into static optimization problem. By using the proposed method, it solves the problem that decision variables'dimension increases as the stage increases and it is suitable to BBO algorithm implement.