Learning Large Electrical Loads via Flexible Contracts With Commitment

Large electricity customers (e.g., large data centers) can exhibit huge and variable demands, which poses significant challenges for the suppliers to plan sufficient capacity. Thus, it is desirable design incentive coordination mechanisms between supplier lower capacity cost. This paper proposes a novel scheme based on flexible contracts. Unlike existing demand-side management schemes in literature, contract leads information revelation. That is, customer committing reveals valuable about its future demand supplier. Such revelation allows share risk of uncertainty. On other hand, will still retain autonomy operation. We address two key optimal contracts: i) non-convex optimization problem intractable number types, ii) should be robust unexpected or adverse responses customers, i.e., facing more than one yielding same benefit may choose less favorable these by proposing sub-optimal contracts low computational complexity that achieve provable fraction performance gain under global optimum.