Open AccessPlanning a decentralised and bi‐directional market‐based management system
Author(s) -
Hejeejo Rashid,
Qiu Jing,
Mirzaeva Galina
Publication year - 2017
Publication title -
iet renewable power generation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.005
H-Index - 76
eISSN - 1752-1424
pISSN - 1752-1416
DOI - 10.1049/iet-rpg.2017.0190
Subject(s) - electricity market , grid , renewable energy , electric power system , computer science , electricity , energy management , load management , smart grid , distributed generation , spot contract , mathematical optimization , reliability engineering , power (physics) , business , electrical engineering , engineering , finance , energy (signal processing) , statistics , physics , geometry , mathematics , quantum mechanics , futures contract
The increases in renewable current sources, prosumers and decentralised control generation in centralised grids have increased the fluctuations in electricity costs, increased the bi‐direction power flow problems and changed the operation and investment of the centralised grid. These new constraints have to be observed to manage the design of the market, the new management near the load and the new operators for the power system. This study proposes a stochastic framework for the centralised grid with a market‐based, decentralised management and bi‐directional power flow of mixed generators of electrical energy. A decentralised and bi‐directional market‐based management system (DBMBMS) model is developed which considers the operation costs, security and reliability of the centralised grid, the spot market price, weather changes and the fluctuations in the load. A differential evolution technique with a Monte Carlo program is used in aggregation with bi‐directional power flows to find the optimal solutions, depending on the uncertainties of the centralised grid. Using a DBMBMS model, optimal load and price management are then realised, based on the decision‐maker's choices. The impacts of this new management system on the reduction of the total electricity prices of the different power sources are analysed and illustrated with practical case studies.