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Planning of power distribution networks in local energy communities

Maleki Delarestaghi, Javid (2021) Planning of power distribution networks in local energy communities. PhD thesis, Murdoch University.

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Recent technological advances, the global understanding of climate change and the role that renewable energy resources can play, along with the rise in electricity prices and little incentive for feeding the excess PV generation back to the grid have led to the growing interest among end-users in residential solar photovoltaic (PV) systems with battery storage systems. The recently released Western Australian Climate Policy sets the goal of achieving net-zero greenhouse gas emissions (GGE) by 2050. The rapid growth in distributed energy resources (DER) has changed the load pattern in distribution networks (DNs). As more DER facilities are introduced to the electric power systems, the power utilities undertake more investments in infrastructure to tackle the uncertainties pertaining to DER and manage the voltage issues due to increasing DER penetration. In these cases, the conventional planning models will result in over- or under-investment choices due to limited knowledge about end-users, which ultimately leads to financial losses for both the utility and customers.

In order to effectively plan DNs for the future utilities need to understand the possible changes at the end-users’ side, which is missing in the existing literature. To achieve the optimal plan for the modern power distribution networks, all parties should be considered including the utility and end-users. There is also a critical need for better network charge tariffs designs to reflect the true contribution of customer DER in the cost of poles and wires. This thesis studies planning models for power utilities incorporating a model of end-users’ decisions. This enables utilities to see the most likely possible scenarios of end-users’ investment in DER.

The main contributions of this thesis are:
1. Development of a DN planning model that incorporates the expected end-users’ investments in DER. This model enables the utility to investigate the opportunities and challenges offered by end-users’ DER and presents more cost-effective investment plans for the utility.
2. Further development of a DN planning model through formulating a separate optimisation problem for the end-users. This model allows both the utility and end-uses to maximise their own benefits.
3. Inclusion of a local energy market where end-users can trade energy with other end-users in their neighbourhood providing more convenient prices for buyers and higher benefits for sellers.
4. Design of a network charge allocation scheme for the utility to rationalise the network use. This will help the utility to avoid unnecessary investment in the network.
5. Development of solution techniques using distributed optimisation algorithms and decomposition techniques to enhance the computation speed.
6. Formulation of a novel optimal power flow problem based on the concept of the Stackelberg game and Benders decomposition. This model provides more cost-effect solutions and is faster than existing models.

The simulations reveal that the proposed planning model enables power utilities to avoid overinvestments while motivating the increased installation of DER by end-users. In essence, the numerical studies show that the proposed planning model led to 75% reduction in the cost of network investment and 70% reduction in the total cost of planning and operation for the utility compared to existing planning models. As well as this the penetration of customer DER increased by 20% using our proposed model. The proposed model also reduced the total cost of electrification by 4%.

The numerical studies also show that the proposed dynamic network charge tariff design can effectively reflect the true contribution of customers to the cost of network upgrade. Essentially, the loading of lines and distribution transformers decreased by up to 30% which resulted in lower grid losses and avoided unnecessary costly infrastructure investments. The deviation of the node voltages from 1 per unit was also improved by a factor of 11%.

Item Type: Thesis (PhD)
Murdoch Affiliation(s): Engineering and Energy
United Nations SDGs: Goal 7: Affordable and Clean Energy
Supervisor(s): Arefi, Ali, Ledwich, Gerard and Lund, Christopher
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