The private rental housing market before and during the COVID-19 pandemic: A submarket analysis in Cracow, Poland

How the COVID-19 pandemic has altered the segmentation of residential rental markets is largely unknown. We therefore assessed rental housing submarkets before and during the pandemic in Cracow, Poland. We used geographically and temporally weighted regression to investigate the marginal prices of housing attributes over space–time. The marginal prices were further reduced to a few principal components per time period and spatially clustered to identify housing submarkets. Finally, we applied the adjusted Rand index to evaluate the spatiotemporal stability of the housing submarkets. The results revealed that the pandemic outbreak significantly lowered rents and modified the relevance of some housing characteristics for rental prices. Proximity to the university was no longer among the residential amenities during the pandemic. Similarly, the virus outbreak diminished the effect of a housing unit’s proximity to the city center. The market partitioning showed that the number of Cracow’s residential rental submarkets increased significantly as a result of the COVID-19 pandemic, as it enhanced the spatial variation in the marginal prices of covariates. Our findings suggest that the emergence of the coronavirus reshaped the residential rental market in three ways: Rents were decreased, the underlying rental price-determining factors changed, and the spatiotemporal submarket structure was altered.

The Effect of Hybrid Attributes on Property Prices

This study focuses on the sales comparison and the adjustment grid methods, under the framework of the market approach to valuation. The literature mostly focuses on the structural qualities of the properties, referring to the buildings and their locational characteristics, which pertain to their positioning within the urban fabric. Here we focus on a particular set of attributes which depend on how a building is placed in a specific land plot and relate to the surrounding environment. The term «hybrid» is used to identify this class of attributes. It is shown that hybrid attributes affect property prices and should not be disregarded by practitioners and appraisers. The role played by hybrid characteristics is analyzed based on the methodological foundation of the hedonic and the adjustment grid methods. The derived linear and log-linear models are tested by means of a case study. The models prove to have high explanatory power. The weight of each hybrid attribute is estimated to vary between 1% and 10%. Overall, these attributes contribute to 17-23% of the property prices. The validation performed using the grid adjustment method shows that the estimated marginal prices are effective in adjusting the prices per unit area of the comparables.

Optimal Variable Renewable Energy Generation Schedules Considering Market Prices and System Operational Constraints

The maximization of output from variable renewable energy (VRE) sources considering system operational constraints (SOCs) is a traditional method for maximizing VRE generators’ profits. However, in wholesale electricity markets, VRE participation tends to reduce marginal prices (MP) because of its low marginal costs. This circumstance, called the “merit-order effect” (MOE), reduces the generators’ profits. Thus, the traditional method is possibly no longer the best and only method to maximize the generators’ profits. Moreover, the VRE support schemes also affect MP, making MOE more severe. VRE curtailment can relieve MOE, but VRE output must be decreased, thereby reducing the generators’ profits. This paper proposes a method to find the optimal VRE generation schedules that maximize VRE generators’ profits while considering the trade-off among the VRE output, MP, and SOCs. The method combines the merit-order model and the unit-commitment model solved by the optimization tools in MATLAB. Thailand’s electrical system was the test system. The result shows that VRE generators’ profits from the proposed method are significantly higher than from the traditional method when the system has high wind penetration, and the generators have no support scheme. Curtailing approximately 7–10% of wind output can increase the average MP by 23.6–30%.

Optimal Computation of Network Indicators for Electricity Market Bidding Zones Configuration Considering Explicit N-1 Security Constraints

In this paper an optimization problem designed to calculate electric grid specific indicators to be used within model-based methodologies for the definition of alternative electricity market bidding zone configurations is designed. The approach integrates within the framework of a bidding zone review process aligned to the specifications of the Commission Regulation (EU) 2015/1222 (CACM) and Regulation (EU) 2019/943 of the European Parliament and of the Council (CEP). The calculated solution of the optimization provides locational marginal prices and allows to determine, outside the optimization problem, the power transfer distribution factors for critical elements. Both indicators can be used as inputs by specially designed clustering algorithms to identify model-based electricity market bidding zone configurations, as alternative to the current experience-based configurations. The novelty of the optimization problem studied in this paper consists in integrating the N-1 security criteria for transmission network operation in an explicit manner, rather than in a simplified and inaccurate manner, as encountered in the literature. The optimization problem is evaluated on a set of historical and significant operating scenarios of the Italian transmission network, carefully selected by the Italian transmission system operator. The results show the optimization problem capability to produce insightful results for supporting a bidding zone review process and its advantages with respect to simplified methodologies encountered in the literature.

TSO-DSO Coordination Schemes to Facilitate Distributed Resources Integration

The incorporation of renewable energy into power systems poses serious challenges to the transmission and distribution power system operators (TSOs and DSOs). To fully leverage these resources there is a need for a new market design with improved coordination between TSOs and DSOs. In this paper we propose two coordination schemes between TSOs and DSOs: one centralised and another decentralised that facilitate the integration of distributed based generation; minimise operational cost; relieve congestion; and promote a sustainable system. In order to achieve this, we approximate the power equations with linearised equations so that the resulting optimal power flows (OPFs) in both the TSO and DSO become convex optimisation problems. In the resulting decentralised scheme, the TSO and DSO collaborate to optimally allocate all resources in the system. In particular, we propose an iterative bi-level optimisation technique where the upper level is the TSO that solves its own OPF and determines the locational marginal prices at substations. We demonstrate numerically that the algorithm converges to a near optimal solution. We study the interaction of TSOs and DSOs and the existence of any conflicting objectives with the centralised scheme. More specifically, we approximate the Pareto front of the multi-objective optimal power flow problem where the entire system, i.e., transmission and distribution systems, is modelled. The proposed ideas are illustrated through a five bus transmission system connected with distribution systems, represented by the IEEE 33 and 69 bus feeders.

Large fluctuations in locational marginal prices

This paper investigates large fluctuations of locational marginal prices (LMPs) in wholesale energy markets caused by volatile renewable generation profiles. Specifically, we study events of the form P ( LMP ∉ ∏ i = 1 n [ α i − , α i + ] ) , where LMP is the vector of LMPs at the n power grid nodes, and α − , α + ∈ R n are vectors of price thresholds specifying undesirable price occurrences. By exploiting the structure of the supply–demand matching mechanism in power grids, we look at LMPs as deterministic piecewise affine, possibly discontinuous functions of the stochastic input process, modelling uncontrollable renewable generation. We use techniques from large deviations theory to identify the most likely ways for extreme price spikes to happen, and to rank the nodes of the power grid in terms of their likelihood of experiencing a price spike. Our results are derived in the case of Gaussian fluctuations, and are validated numerically on the IEEE 14-bus test case. This article is part of the theme issue ‘The mathematics of energy systems’.

TSO-DSO Coordination Schemes to Facilitate Distributed Resources Integration

The incorporation of renewable energy into power systems poses serious challenges to the transmission and distribution power system operators (TSOs and DSOs). To fully leverage these resources there is a need for a new market design with improved coordination between TSOs and DSOs. In this paper we propose two coordination schemes between TSOs and DSOs: one centralised and another decentralised that facilitate the integration of distributed based generation; minimise operational cost; relieve congestion; and promote a sustainable system. To this end, we approximate the power equations with linearised equations so that the resulting optimal power flows (OPFs) in both the TSO and DSO become convex optimisation problems. In the resulting decentralised scheme, the TSO and DSO collaborate to optimally allocate all resources in the system. In particular, we propose an iterative bi-level optimisation technique where the upper level is the TSO that solves its own OPF and determines the locational marginal prices at substations. We demonstrate numerically that the algorithm converges to a near optimal solution. We study the interaction of TSOs and DSOs and the existence of any conflicting objectives with the centralised scheme. More specifically, we approximate the Pareto front of the multi-objective optimal power flow problem where the entire system, i.e., transmission and distribution systems, is modelled. The proposed ideas are illustrated through a five bus transmission system connected with distribution systems, represented by the IEEE 33 and 69 bus feeders.

Do Households Respond to the Marginal or Average Price of Piped Water Services?

Water utilities commonly use complex, nonlinear tariff structures to balance multiple tariff objectives. When these tariffs change, how will customers respond? Do customers respond to the marginal volumetric prices embedded in each block, or do they respond to an average price? Because empirical demand estimation relies heavily on the answer to this question, it has been discussed in the water, electricity, and tax literatures for over 50 years. To optimize water consumption in an economically rational way, consumers must have knowledge of the tariff structure and their consumption. The former is challenging because of nonlinear tariffs and inadequate tariff information provided on bills; the latter is challenging because consumption is observed only once and with a lag (at the end of the period of consumption). A large number of empirical studies show that, when asked, consumers have poor knowledge about tariff structures, marginal prices, and (often) their water consumption. Several studies since 2010 have used methods with cleaner causal identification, namely regression discontinuity approaches that exploit natural experiments across changes in kinks in the tariff structure, changes in utility service area borders, changes in billing periods, or a combination. Three studies found clear evidence that consumers respond to average volumetric price. Two studies found evidence that consumers react to marginal prices, although in both studies the change in price may have been especially salient. One study did not explicitly rule out an average price response. Only one study examined responsiveness to average total price, which includes the fixed, nonvolumetric component of the bill. There are five messages for water professionals. First, inattention to complex tariff schedules and marginal prices should not be confused with inattention to all prices: customers do react to changes in prices, and prices should remain an important tool for managing scarcity and increasing economic efficiency. Second, there is substantial evidence that most customers do not understand complex tariffs and likely do not respond to changes in marginal price. Third, most studies have failed to clearly distinguish between average total price and average volumetric price, highlighting the importance of fixed charges in consumer perception. Fourth, evidence as of late 2020 pointed toward consumers’ responding to average volumetric price, but it may be that this simply better approximates average total price than marginal or expected marginal prices; no studies have explicitly tested this. Finally, although information treatments can likely increase customers’ understanding of complex tariffs (and hence marginal price), it is likely a better use of resources to simplify tariffs and pair increased volumetric charges with enhanced customer assistance programs to help poor customers, rather than relying on increasing block tariffs.