Abstract
With the large-scale development of distributed generations (DGs) and the connection into the main grid of active distribution networks (ADNs), traditional centralized dispatch of power system has encountered enormous challenge. In a bilateral electricity market, introducing ADN resources in the day-ahead generation schedule will not only enrich the dispatch patterns to the power system, but also reflect the initiative of ADNs. This paper proposes a coordinated scheduling model of power system with a plurality of ADNs based on multi-agent system where ADN agents are brought in the day-ahead market clearing. The process of market clearing and the dispatch of DGs in ADNs are independent with each other but linked together through the market clearing price (MCP) and bid volume. The optimal operating point of the whole system is achieved through multiple information exchange. In comparison with the dispatch without interaction between ADNs and the market operator (MO), the coordinated scheduling model is applied in a system with four ADNs to verify that the proposed method can improve the overall interests of ADNs. Finally, the effects of storage device and tie-line power limit are analyzed.
Highlights
With the gradual deterioration of global environmental problems and exploration of fossil fuels, large numbers of distributed generations (DGs) are connected to the distribution network
According to market clearing price (MCP) provided by market operator (MO) agent, each active distribution networks (ADNs) agent optimizes the dispatch of DGs and re-declares the bid volume of electricity to the MO agent
T1⁄41 k1⁄41 where ktADN is the MCP at period t; PtADN is the power bought from the MO at period t; FDk;Gt is the cost function of DG k in the ADN at period t; PkD;Gt is the active power of DG k in the ADN at period t; nDG is the number of DGs in the AND; T is the scheduling period
Summary
With the gradual deterioration of global environmental problems and exploration of fossil fuels, large numbers of distributed generations (DGs) are connected to the distribution network. Compared to Lagrange relaxation, Benders decomposition doesn’t need to modify the multipliers to get a good convergence rate Intelligent algorithms such as particle swarm optimization [20], artificial bee colony optimization [21], teaching learning based optimization [22] are often used for multi-area optimization involving nonlinear conditions such as valve point loading effects. Inspired by the concept of OCD, this paper intends to use multi agent system to solve the coordinated scheduling problem between TN and ADNs. Multi-agent system (MAS) has been applied in the field of electricity market incorporating DGs. Reference [32] researches on EV aggregation scheduling strategy to participate in the power market. 2) A coordinated scheduling model based on MAS for power system with ADNs is proposed.
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