Peer-to-peer energy trading for improving economic and resilient operation of microgrids

Towards Resilient Energy Communities: Evaluating the Impact of Economic and Technical Optimization

“…The dynamic aspect now enters the picture. The energy share 𝑆ℎ𝑎𝑟𝑒 𝑑,% ℎ,𝑛 is equal to the ratio of each member's net demand 𝑁𝑒𝑡𝐷 ℎ,𝑛 with respect to the demand of the EC 𝐷 𝑐 ℎ in (20). This can then be multiplied by the EC production 𝑃 𝑐 to obtain 𝑆ℎ𝑎𝑟𝑒 𝑀𝑊 ℎ,𝑛 in (21).…”

“…For example, [8][9][10][11][12][13][14] minimize the overall EC cost, whereas [15][16][17] minimize the cost of each individual member. The possible technological objective functions are more diverse, such as minimizing energy curtailment [18], imports to the EC [19], or battery energy storage system (BESS) degradation [20]. Other objective functions include maximizing self-consumption [21,22] and energy sharing [23].…”

“…Out of the above-mentioned literature on EC optimization, only Refs. [9,11,12,14,15,19,20] consider an electricity grid and its constraints, which is less than half of them. While the EC is often not the balancing responsible party, and thus one could argue that modeling the grid is unnecessary, they must still adhere to the technical constraints of the grid in which they are located.…”

“…Ref. [20] establishes a peer-to-peer trading system, and while resilience is not optimized, it is compared for different grid disturbance scenarios. The hybrid renewable energy system in [8] indirectly maximizes resilience by minimizing the hourly gap between demand and production in the EC.…”

“…Flexibility measures in the ECs are also an important part of optimizing ECs. These are most commonly found in the form of BESSs, as shown in [8,10,12,[14][15][16]20,22,23]. Another option is to incorporate EVs into the model, as shown in [9,12,16,17,22].…”