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Different from the original cobweb design, adaptive price expectations do not suffice to eliminate fluctuations.
It moves beyond the existing work by explicitly simulating the emergence of property prices and their spatial distribution under adaptive price expectations of heterogeneous agents, advancing toward empirical modeling of agent-based land markets.
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Since vegetable prices are not stable throughout the year, designing a rotation schedule that maximizes expected profits, distributes farmers' profits more equitably, maintains the diversity of produce in the market, and reduces the risk of pests and diseases, requires adaptive, price-contingent rotation schedules (here, called "self-adaptive adjustment").
Closed-loop adaptive pricing mitigates load synchronization.
Besides, adaptive pricing brings higher benefits to traffic efficiency compared to fixed pricing.
Finally, in settings with very flexible loads adaptive pricing schemes may become a necessity.
At the same time closed-loop adaptive pricing emerges as the most effective coordination means.
Hence, closed-loop adaptive pricing remains a somewhat distant vision for retail markets.
With increasing renewable generation and flexible load penetration the performance gap between closed-loop adaptive pricing and group pricing increases.
In the special case of closed-loop adaptive prices the rate design and load response steps are performed simultaneously.
Our results show that simple open-loop pricing can almost match the efficiency of closed-loop adaptive pricing in settings with limited system flexibility.
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