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The main purpose behind this work is to explore the methods already proposed in various literatures to overcome the issues associated with VAr management in a competitive environment. Managing reactive power support service in competitive electricity market environment has become an important constituent of ancillary services. The characteristics of VAr generation/absorption do not allow its transmission over a long distance. The issues associated with the localized nature of reactive power must be considered during the valuation, planning, pricing and allocation of VAr producing/absorbing resources. In this review work, the key issues associated with the reactive support and the techniques used to tackle these issues in various utilities across the globe are been discussed in brief. In the literature, numerous renowned authors propose various methods to manage reactive power with various types of structural and operational scenarios. These methods are also discussed briefly in this paper. The experience with VAr management in some matured electricity market is also discussed in this paper.

Discussion of various issues associated with reactive power management and methods/techniques to overcome these, has been carried out in this paper. The methods were proposed in various literatures related to reactive power management by some of the renowned authors and adopted by various electric utilities.

The review work may be useful for utilities to develop a quick insight on reactive support services to control the voltage profile and also, it may be a useful asset for the researchers working in this area.

The paper is organized with different sections to elaborate the issues and associated methods. This paper is a single piece of work, which addresses reactive power planning, pricing for VAr support, market issues and valuation of VAr utilization.

Previously, a linear model was developed for investigating the optimisation of distribution system reliability for developing power systems. The economics of maintaining this reliability level was established based on cost‐benefit and probability techniques. In this paper, a theoretical formulation is described to evaluate the time frame required to achieve this reliability level employing a nonlinear model.

Economic load dispatch (ELD) is one of the crucial optimization problems in power system planning and operation. The ELD problem with valve point loading (VPL) and multi-fuel options (MFO) is defined as a non-smooth and non-convex optimization problem with equality and inequality constraints, which obliges an efficient heuristic strategy to be addressed. The purpose of this study is to present a new and powerful heuristic optimization technique (HOT) named as squirrel search algorithm (SSA) to solve non-convex ELD problems of large-scale power plants.

The suggested SSA approach is aimed to minimize the total fuel cost consumption of power plant considering their generation values as decision variables while satisfying the problem constraints. It confers a solution to the ELD issue by anchoring with foraging behavior of squirrels based on the dynamic jumping and gliding strategies. Furthermore, a heuristic approach and selection rules are used in SSA to handle the constraints appropriately.

Empirical results authenticate the superior performance of SSA technique by validating on four different large-scale systems. Comparing SSA with other HOTs, numerical results depict its proficiencies with high-qualitative solution and by its excellent computational efficiency to solve the ELD problems with non-smooth fuel cost function addressing the VPL and MFO. Moreover, the non-parametric tests prove the robustness and efficacy of the suggested SSA and demonstrate that it can be used as a competent optimizer for solving the real-world large-scale non-convex ELD problems.

This study has compared various HOTs to determine optimal generation scheduling for large-scale ELD problems. Consequently, its comparative analysis will be beneficial to power engineers for accurate generation planning.

To the best of the authors’ knowledge, this manuscript is the first research work of using SSA approach for solving ELD problems. Consequently, the solution to this problem configures the key contribution of this paper.

The physical nature of electricity generation and delivery creates special problems for the design of efficient markets, notably the need to manage delivery in real time and the volatile congestion and associated costs that result. Proposals for the operation of the deregulated electricity industry tend towards one of two paradigms: centralized and decentralized. Transmission congestion management can be implemented in the more centralized point‐to‐point approach, as in New York state, where derivative transmission congestion contracts (TCCs) are traded, or in the more decentralized flowgate‐based approach. While it is widely accepted that theoretically TCCs have attractive properties as hedging instruments against congestion cost uncertainty, whether efficient markets for them can be established in practice has been questioned. Based on an empirical analysis of publicly available data from years 2000 and 2001, it appears that New York TCCs provided market participants with a potentially effective hedge against volatile congestion rents. However, the prices paid for TCCs systematically diverged from the resulting congestion rents for distant locations and at high prices. The price paid for the hedge not being in line with the congestion rents, i.e., unreasonably high risk premiums are being paid, suggests an inefficient market. The low liquidity of TCC markets and the deviation of TCC feasibility requirements from actual energy flows are possible explanations.

The use of energy storage devices helps the consumers to utilize the benefits and flexibilities brought by smart networks. One of the major energy storage solutions is using electric vehicle batteries. The purpose of this paper is to develop an optimal energy management strategy for a consumer connected to the power grid equipped with Vehicle-to-Home (V2H) power supply and renewable power generation unit (PV).

The problem of energy flow management is formulated and solved as an optimization problem using a linear programming model. The total energy cost of the consumer is optimized. The optimal values of decision variables are found using CPLEX solver.

The simulation results demonstrated that if the optimal decisions are made regarding the V2H operation and managing the produced power by solar panels then the total energy payments are significantly reduced.

The gap that the proposed model is trying to fill is the holistic determination of an optimal energy procurement portfolio by using various embedded resources in an optimal way. The contributions of this paper are in threefold as: first, the introduction of mobile storage devices with a periodical availability depending on driving schedules; second, offering a new business model for managing the generation of PV modules by considering the possibility of grid injection or self-consumption; third, considering Real Time Pricing in the suggested formulation.

This paper aims to present a conceptual framework for the emerging field of green energy platform economics.

The authors develop a conceptual framework based on a careful review of the existing literature, and research into the current provider landscape and insights from academic and industry experts. The authors also examine the implications for the energy sector’s value chain and derive a research agenda based on those areas where research still needs to be pursued.

The framework combines the spatial characteristics of platform models (residential/mobile) with the different types of platform business model (B2C/C2C/C2Grid). Using this framework, the authors illustrate how green energy platforms can fundamentally disrupt the conventional electricity value chain by enabling prosumers to market their assets, creating new arenas for trading and collaboration, and by increasing transparency and competition in the sector. The authors also identify areas where more research is required, particularly empirical studies into energy forms other than electricity and analyses of currently underrepresented aspects such as user interfaces and social interactions.

Green energy platforms have the potential to contribute meaningfully to the energy sector’s decarbonization, digitalization and decentralization, and hence to the deceleration of climate change.

This paper is among the first to provide a holistic perspective on platformization in the energy sector. It also offers a new perspective on platform economics in general that is based on the unique characteristics of energy as an economic good (intangibility, homogeneity, credence good).

The purpose of this paper is to present a practical method for computing contingency‐based reliability and quality indices in power systems and to answer questions related to how much the system is reliable, how robust it is in surviving random contingencies, how much it is costing to maintain appropriate system security and reliability levels and, finally, to what extent the desired balance is maintained between generation facilities, transmission capabilities and consumer demand levels in various zones of the electric power system.

The methodology adopted in this paper is based on a combined contingency analysis/reliability evaluation scheme. A three‐component system model is utilized, which can be used effectively for evaluation and sensitivity analysis of reliability and quality in power systems. The model is a reduced (equivalent) system representation that comprises generation, transmission and load components with multi‐state values. The computational scheme presented in the paper integrates both the contingency effect and its probability of occurrence into one routine of analysis while reducing the power system around the region of interest.

The computational scheme presented in the paper can effectively assess both service reliability and system quality. The practical applications presented demonstrated that lower service reliability levels would jeopardize energy supply continuity and increase the likelihood of additional maintenance and restoration costs due to the resulting higher rate of system outages. Poor system quality levels, on the other hand, imply either deficiency or excess in the overall system capabilities as designed by its planners.

The work of this paper contributes to the solution of the reliability and quality assessment problem in practical power systems. As part of the present work, an advanced computerized scheme for fast composite system reliability and quality assessment was developed and then applied to an equivalent system model of the Saudi electricity system. The results obtained are claimed to have far‐reaching implications on various planning and operation aspects of the power system.

The ex-post literature, which evaluates the real impact of renewable generation, is scarce. Most studies are simulations and therefore are not based on real data. This study aims to further this goal using a unique database of the Portuguese spot market, where there are powerful incentives for renewable electricity.

This paper analyses ex-post the impact of energy produced in special regime on the wholesale hourly spot market prices of Portuguese electricity during the period 2009–2016. This paper uses standard, two stage least squares and generalized method of moments multivariate regressions and other energy econometrics techniques.

It is found that special regime generation has a negative impact on the wholesale price. This impact is higher than that found in other markets. This paper also concludes that using special regime generation to supply the future growth of demand will decrease wholesale electricity spot prices more intensively than using other technologies.

This paper uses a unique database based on ex-post for the Portuguese spot market. The Portuguese case is particularly interesting, not only because of its strong incentives policy on renewable energy but also because its spot market is interconnected with the Spanish market. This paper contributes to the debate about the sustainability of current renewable electricity support schemes. The decreasing trend in electricity prices, with the introduction of new renewable capacity, can be incompatible with the required payments for non-renewable producers. This paper also shows that even if the price reduction on spot markets is transferred to final consumers, given that it is relatively small (8% spot price which represents 45% of the final price), compared with the cost of incentives (35% of the final price), consumers probably will not be able to support a new investment pipeline with a similar framework.

The purpose of the study is to examine the relationship between the application of smart electronic systems, firm characteristics and efficient energy consumption: a case of public universities in Uganda.

The study adopted both quantitative and qualitative approach as well as descriptive cross-sectional survey design tantamounting to an experimental-observation approach. A sample of four public academic universities were explored using primary data. A semi-structured questionnaire together with an evaluation form and a tested experimental kit (from one of the leading electronics centres in Uganda) was used to examine the consumption rates of different electronic appliances of less than 30 Amps. Further, a Pearson product moment correlation (r) analysis was also used to determine the direction of a relationship among the variables together with a linear relationship (regression) to predict a linear association of one or more variables. Recommendations were also given.

Smart electronic systems make a significant determining factor to both firm characteristics (age, number of students, administrative staff and support staff) as well as efficient energy consumption. Nonetheless, there is no significant difference of efficient energy consumption as far as firm characteristics are concerned.

Results support the contributions of the theory of technology and acceptance model by affirming that a number of factors influence the usefulness and ease of use of the smart electronic systems, which in turn influence energy consumption.

Universities' management should endeavour to install smart electronic systems. But still, government should try to lower taxes on smart electronic systems and genuine agents should be named for easy and affordable access of the users, universities inclusive.

The study contributes towards a theoretical position by affirming the usefulness of technology acceptance model for efficient energy consumption in public universities.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-02-2019-0083