Fariba F. Mamaghani

Harvesting Solar Power Foments Prices in a Vicious Cycle: Breaking the Cycle with Price Mechanisms

Distributed solar power generation is growing but not necessarily benefiting the utility firms. Reducing the demand, it hinders the coverage of utility costs with reasonable retail electricity prices. Utilities raise prices, unintentionally reducing both demand and affordability of electricity, and are said to be caught in a utility (death) spiral. The reduced affordability adversely affects consumers that cannot invest into solar generation. Environmentally desirable solar power paradoxically can be socially undesirable. Market regulators are challenged to keep prices low within the current pricing mechanisms. We provide a profit maximization formulation for a regulated utility and reveal the interaction between optimal price increases and growing solar power adoption. Iterating with this interaction, we analytically explain how the utility death spiral occurs. We consider new pricing mechanisms with a buyback price and a subscription fee paid only by solar power generating consumers. The fee mitigates the optimal retail price increase by allowing for the coverage of fixed costs in part. We find appropriate values for the buyback price and subscription fee to respectively slow or stop the utility spiral. These mechanisms and values are important not only for the utility and its regulator but also for all electricity consumers.

Dismissal of Demand Dependence Disappoints and Deceives: The Case of Microgrid Generation and Storage Investments

In today’s energy transition, microgrids (MGs) emerge as vital components of the electricity landscape, offering local and profitable energy solutions, e.g., for data centers, universities, and hospitals. MGs, comprising of local generators, short-term storage equipment, and consumers, act as alternative and supplementary suppliers to the grid, i.e., they trade electricity with the grid through contracts specifying the grid’s purchase price. Determining optimal generation and storage capacities for MGs presents significant challenges due to uncertainties in the
demand and market price, and specifically their dependence. We incorporate uncertainties and dependencies when evaluating and maximizing MG profits. Moreover, we present closed-form solutions for optimal generation and capacity levels. To formulate dependence, we rely on a comonotonic representation of demand and price pair. We include empirical analysis to showcase this dependence, a realistic case study, and a sensitivity analysis. We identify weak conditions for generation and storage optimization to bypass traditional dynamic programming approaches unconducive to managerial implications. We obtain two major results: ignorance of demand dependence (of price) artificially inflates profits and yields lower optimal capacities. We package our key insights as takeaways and customize them for the MG stakeholders. MG operators should capture demand dependence to avoid financial disappointments. In contrast, these operators might ignore demand dependence when negotiating with financial institutions to secure favorable financing terms.