Optimizing rooftop photovoltaic distributed generation with battery storage for peer-to-peer energy trading

By Su Nguyen, Wei Peng, P. Sokolowski, Damminda Alahakoon, Xinghuo Yu. Applied Energy, 2018

259 citations recorded by the source corpus.

Distributed generation (DG) based on rooftop photovoltaic (PV) systems with battery storages is a promising alternative energy generation technology to reduce global greenhouse gas emissions. As regulatory tariff-based incentives are diminishing, innovative solutions are required to sustain this renewable energy generation. An optimization model is proposed to maximize the economic benefits for rooftop PV-battery DG in a peer-to-peer (P2P) energy trading environment. The goal of the proposed model is to investigate the feasibility of such renewable source participated P2P energy trading by examining the economic benefits. The model is illustrated in a simulation framework for a local community with 500 households under real-world constraints encompassing PV systems, battery storage, customer demand profiles and market signals including the retail price, feed-in tariff and P2P energy trading mechanism. Interactions among peer-to-peer trading stakeholders are examined, quantifying household savings for different scenarios of this P2P-based DG. Household energy savings are identified to be sensitive to many factors including the scale of PV systems, the PV penetration, the P2P trading margins, the presence of battery storage and energy trading time. The model shows that maximal savings up to 28% can be achieved by households equipped with larger PV systems and battery storages during weekdays from an exemplified case. The sensitivity analysis demonstrates that households with PV systems have lower savings when PV penetration is high owing to excessive energy traded on the P2P market, pushing down the clearing price and the savings gain. Households with a battery-only configuration are shown to achieve fewer savings in contrast to households without any renewable resources in a P2P trading community. The model’s energy insights are the beginning of understanding the actual impact of policy, market and technical signals on economic benefits for household distributed renewable generation in a P2P energy trading market.

Subfields: Electrical and Electronic Engineering, Pollution

View Paper: https://www.semanticscholar.org/paper/3d9a3f76885a9bb1ea81d75f1293034df68b7069

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Citations in the corpus

Peer-to-Peer Trading in Electricity Networks: An Overview (2020, methodology): “An MILP technique is used by [44] to optimize the use of energy gener-”
A Motivational Game-Theoretic Approach for Peer-to-Peer Energy Trading in the Smart Grid (2019, background): “References [24], [25], [26], [27] [16], [17], [18], [19], [20], [28], [29], [31], [32] [33]”
Peer-to-Peer Energy Systems for Connected Communities: A Review of Recent Advances and Emerging Challenges (2020, background): “For example, in [120], it is shown that a household can increase its savings by up to 28% when it involves both its PV and storage in energy sharing.”
State-of-the-Art Analysis and Perspectives for Peer-to-Peer Energy Trading (2020, background): “[39] proposed an optimization model to maximize the economic benefits of a group of households with photovoltaic (PV) cells and batteries.”