The article analyzed the state of the global problem of ecological safety of the EU and argued the need to create a methodology for planning technologically integrated projects of the “European Green Deal” (TIP “EGD”) that accounts for the risks to the stakeholders, i.e., the state, project executors, resource suppliers, project managers, and clients. Each of these has an individual set of values that determines the project risk for them. Herein is proposed a taxonomy of three ranks of TIP “EGD” involving agricultural waste, determined by their characteristics, products, and requirements for the stakeholders. The authors point out the need to create tools for quantitative risk assessment for the stakeholders of TIP “EGD” involving agricultural waste and distinguish four groups of risk components with regard to the value of such projects. A model of value risk formation is presented that addresses the risk management of each of these stakeholder values. The need to develop tools (models... [more]

The objective of this research is to establish a multiobjective fractional programming (MOFP) model for supporting the operational management of a combined heat and power (CHP) system. Compared with the traditional operational optimization model of the CHP system, the importance of the energy intensity (i.e., the ratio of energy consumption and energy production) was emphasized in the MOFP model, which is considered as the system objective for replacing the common objective of minimizing the economic cost. This innovative transformation effectively reduces excessive energy consumption, accompanied by improvement in the system revenue. The CHP system of an industrial park in the City of Jinan, China, was used as a study case for demonstration. The obtained results reflected that the combination of two gas turbines (GTs) ensured safe, efficient, and stable output for meeting daily power requirements in various seasons. As for the steam load, during the summer, two heat recovery steam gen... [more]

With the large-scale volatility and uncertainty of the centralized grid connection of wind power, the dimensionality disaster problem of wind farm cluster (WFC) scheduling optimization calculation becomes more and more significant. In view of these challenges, a distributed active power optimal dispatch model for WFC based on the alternating direction multiplier method (ADMM) is proposed, and the analytical description of the distribution characteristics of the active power output of wind farms is introduced into the proposed model. Firstly, based on the wake effect, the Weibull distribution of wind speed is transformed by the impulse function to establish an analytical model of the active output distribution of the wind farm. Secondly, the optimization goal is to minimize the expected sum of the deviations of the dispatch instructions and the output probability density function of each wind farm, constructing a WFC active power optimal dispatch model considering uncertainty. Finally,... [more]

The objective of Poland’s energy policy is to guarantee energy security while enhancing economic competitiveness and energy efficiency, thus minimizing the power sector’s environmental impact and optimizing the use of energy resources in the country. Poland is not the only European country to rely on coal for power generation. Historical factors and large coal deposits act as natural barriers to increasing the share of renewable energy in the Polish power sector. Yet, today, environmental concerns and climate change are prompting many countries to move away from fossil fuels. Renewable energy sources, such as solar and wind energy, are an alternative to traditional energy generated from fossil fuels. However, investors developing solar and wind farms in Poland encounter numerous problems at each stage of the project. These difficulties are associated mainly with the location, technical requirements, infrastructure and formal and legal documents. This study aimed to identify the key fac... [more]

According to the objectives of the Paris Agreement on climate change, the European energy supply must be fully decarbonised by 2050. For the power sector, a massive deployment of decentralised renewable technologies will be required to provide carbon-free electricity. However, other energy-intensive sectors such as gas, heat, transport, and the industrial sectors are more challenging to decarbonise, since they rely mostly on liquid and gaseous fuels. Consequently, exploiting the synergies between energy vectors in an integrated, multi-energy system represents an opportunity for a cost-effective transition towards a carbon-free economy. The objective of this study is to provide insights on the coupling of power and residential heat supply systems in a centralised multi-energy system by developing a linear program that optimises the interactions between energy carriers such as electricity, heat, hydrogen, biomass, and methane to minimise the long-term investments in generation and storag... [more]

This Special Issue focuses on progress in energy transition planning [...]

Insular grids are fragile owing to lower inertia and the absence of interconnection with other grids. With the increasing penetration of non-dispatchable renewable energy sources, the vulnerability of such insular grids increases further. The government of India has proposed several projects to improve the photovoltaic systems (PV) penetration in the Andaman and Nicobar Islands’ grid. This paper investigates joint stochastic scheduling of energy and reserve generation for insular grids fed from diesel and gas-based generators, PV, and battery energy storage systems (BESS). The proposed stochastic scheduling model considers a wide range of probabilistic forecast scenarios instead of a deterministic model that assumes a single-point forecast. Hence, it provides an optimal solution that is technically feasible for a wide range of PV power forecast scenarios. The striking feature of the model developed in this work is the inclusion of stochastic constraints that represent (i) the coordinat... [more]

Data center servers located in thermal hotspot regions receive inlet air at a higher than the set temperature and thus generate comparatively high outlet temperature. Consequently, there is a rise in energy that is consumed to cool down the servers that otherwise would undergo reliability hazards. The workload deployment across the servers should be resilient to thermal hotspots to ensure smooth performance. In a heterogeneous data center environment, an equally important fact is the placement of the servers in a thermal hotspot-aware manner to lower the peak outlet temperatures. These approaches can be applied proactively with the help of outlet temperature prediction. This paper presents the hotspot adaptive workload deployment algorithm (HAWDA) and hotspot aware server relocation algorithm (HASRA) based on thermal profiling regarding outlet temperature prediction. HAWDA deploys workload on servers in a thermal-efficient manner and HASRA optimizes the server location in thermal hotsp... [more]

Anaerobic digestion (AD) plants undoubtedly represent an integral and irreplaceable element in rural energy transition and sustainable waste management. In our study, we focus on an advanced understanding of the dynamics behind the changing perceptions of AD plants in host communities in Poland, Slovakia, and the Czech Republic. The surveyed AD plant case studies were selected to represent best-practice examples of AD plant operations in their countries. By means of a comparative survey in three host communities, we seek to learn more about the shift in perceptions of AD plants between their planning and operational phases. We find that, although our cases are considered best-practice examples of AD plant operations, their overall support in their communities dramatically dropped in the operational phase consequent to real-life experience with living in the neighbourhood of an AD plant. Additionally, our findings indicate that respondents who reported the most severe deterioration of A... [more]

In the power distribution system of South Korea, the sectionalizer minimizes and recovers the system from failures, and prohibits independent operation of distributed energy resources. Therefore, it is difficult to expect reliability improvements owing to a photovoltaic system in the power distribution system. Herein, we propose a reliability-centered maintenance-scheduling method based on an economic analysis of photovoltaic integration facilities to ensure the economic feasibility of the photovoltaic system operator and the reliability of the power distribution system. Photovoltaic integration facilities are divided into two categories based on their spread of the failure, and the maintenance scheduling is evaluated according to the maximum and minimum losses according to the time of failure. Facilities that cause power outages to photovoltaics and to loads have relatively little effect on the time of failure. This is because the effects of the power outages in the loads predominate.... [more]

In order to adapt to the development of the green power certificate trading (GPCT) and carbon emissions trading (CET) market, reduce the carbon emissions of the distribution network and increase the investment income, this paper proposes a new distribution network (NDN) planning and simulation operation bi-layer model with new energy (NE) as the main body, considering the GPCT and CET mechanisms. First, the upper layer determines the capacity and location of wind turbine (WT), photovoltaic (PV), hydraulic turbine (HT), micro turbine (MT), and energy storage (ES), while the lower simulation operation considers the operation costs of WT, PV, HT, MT, ES, load demand response (DR) and carbon emissions. The planning objective was to minimize the total cost of investment, operation and carbon emissions in the planning period. Then, on the basis of a traditional distribution network (TDN), security constraints, carbon emissions intensity, GPCT volume and CET volume were added. Finally, the ca... [more]

Oil production is a complex technological process that requires significant electricity consumption. The main electricity consumers in oil and gas production workshops are artificial lift facilities. Currently, among the objects of mechanized mining, installations of electric submersible pumps are widespread. When planning technological modes, it is necessary to be able to assess the change in the power consumption parameters when changing the technological process parameters. The paper proposes a typical replacement scheme for the electrical complex element. The power consumption calculation of electric submersible pump installations has been carried out. The error in the power consumption modeling results of electric submersible pump installations in comparison with the results of instrumental measurements is no more than 10%. The estimation of additional losses of electric energy caused by the influence of harmonics is carried out. The proposed technique makes it possible to estimat... [more]

In the context of smart cities, sustainability is an essential dimension. One of the ways to achieve sustainability and reduce the emission of greenhouse gases in smart cities is through the promotion of sustainable energy. The demand for affordable and reliable electrical energy requires different energy sources, where the cost of production often outweighs the environmental factor. This paper aims to investigate the ways smart cities promote sustainability in the electricity sector. For this, a systematic literature review using the PRISMA protocol was employed as the methodological approach. In this review, 154 journal articles were thoroughly analyzed. The results were grouped according to the themes and categorized into energy efficiency, renewable energies, and energy and urban planning. The study findings revealed the following: (a) global academic publication landscape for smart city and energy sustainability research; (b) unbalanced publications when critically evaluating geog... [more]

The electrical market scenario has changed drastically in the last decade. In the presence of increased competition and less tolerant players, more sophisticated methods are required to balance the diversity and differential pricing while promoting cooperation among the agents. In the monopolistic environment, the central utility incurred the total cost of the transmission expansion. But as the current scenario demands, there are several public and private market players. The growth will benefit all the players, so the total cost in transmission expansion can be divided among players as per the benefit received by each player. In this paper, a transmission system expansion planning problem in the cooperative environment using cooperative game theory (CGT) is framed for the power sector, in which various players can cooperate in a coordinated manner to maximize their benefit but ultimately strengthen the power grid. In this paper, we have modeled, analyzed and compared various cost allo... [more]

This article reviews the accomplishments of studies in which optimization tools were used to develop energy-efficient and sustainable construction schedules. With the increase in global awareness of environmental issues, the construction industry has been forced to explore innovative techniques to make the building process more energy-efficient and sustainable. Project managers can use optimization tools in their scheduling procedures to address these issues in the early stages of the project. Therefore, this paper examines different optimization-based construction scheduling methods and their impact on schedule energy efficiency and the three key sustainability goals: economic viability, social equity, and environmental protection. Such a review has not yet been conducted to the best of our knowledge. This research aims to fill the gap and contribute to understanding advanced optimization tools that can pave the way to energy-efficient and sustainable scheduling practices. After a bri... [more]

Given the additional awareness of the increasing energy demand and gas emissions’ effects, the decarbonization of the transportation sector is of great significance. In particular, the adoption of electric vehicles (EVs) seems a promising option, under the condition that public charging infrastructure is available. However, devising a pricing and scheduling strategy for public EV charging stations is a non-trivial albeit important task. The reason is that a sub-optimal decision could lead to high waiting times or extreme changes to the power load profile. In addition, in the context of the problem of optimal pricing and scheduling for EV charging stations, the interests of different stakeholders ought to be taken into account (such as those of the station owner and the EV owners). This work proposes a deep reinforcement learning-based (DRL) agent that can optimize pricing and charging control in a public EV charging station under a real-time varying electricity price. The primary goal... [more]

In the field of sector integration, the expansion of district heating (DH) is traditionally discussed with regard to the efficient integration of renewable energy sources (RES) and excess heat. But does DH exclusively benefit from other sectors or does it offer advantages in return? So far, studies have investigated DH only as a closed system or determined intersectoral benefits in a highly aggregated approach. We use and expand an integrated generation and transmission expansion planning model to analyze how the flexibility of DH benefits the energy system and the power transmission grid in particular. First of all, the results confirm former investigations that show DH can be used for efficient RES integration. Total annual system cost can be decreased by expanding DH, due to low investment cost and added flexibility, especially from large-scale heat storage. The high short-term efficiency of heat storage—in combination with electric heating technologies—can be exploited to shift hea... [more]

The residential sector is a major contributor to the global energy demand. The energy demand for the residential sector is expected to increase substantially in the next few decades. As the residential sector is responsible for almost 40% of overall electricity consumption, the demand response solution is considered the most effective and reliable solution to meet the growing energy demands. Home energy management systems (HEMSs) help manage the electricity demand to optimize energy consumption without compromising consumer comfort. HEMSs operate according to multiple criteria, including electricity cost, peak load reduction, consumer comfort, social welfare, environmental factors, etc. The residential appliance scheduling problem (RASP) is defined as the problem of scheduling household appliances in an efficient manner at appropriate periods with respect to dynamic pricing schemes and incentives provided by utilities. The objectives of RASP are to minimize electricity cost and peak lo... [more]

The uncertain output of variable renewables adds significant challenges to the generation of affordable, reliable, and sustainable power sources in a country or region. Therefore, we propose a new stochastic nonlinear multi-objective model to optimize the power generation structure in 31 provinces of China. Considering variable renewable integration, we use Monte Carlo simulation to describe the randomness and uncertainty of renewable power output. The learning curve in the exponential expression is used to describe the nonlinear relationship between generation cost and installed capacity. The optimized results show that China can substitute fossil power with clean power. Renewable power will account for more than 42% of total power in the optimal power generation structure in 2040. In particular, the annual average growth rate of non-hydro renewable generation is expected to be 12.06%, with solar photovoltaic (PV) power growing the most by 17.95%. The share of renewable power exceeds... [more]

Recently, due to the ever-increasing global warming effect, the proportion of renewable energy sources in the electric power industry has increased significantly. With the increase in distributed power sources with adjustable outputs, such as energy storage systems (ESSs), it is necessary to define ESS usage standards for an adaptive power transaction plan. However, the life-cycle cost is generally defined in a quadratic formula without considering various factors. In this study, the life-cycle cost for an ESS is defined in detail based on a life assessment model and used for scheduling. The life-cycle cost is affected by four factors: temperature, average state-of-charge (SOC), depth-of-discharge (DOD), and time. In the case of the DOD stress model, the life-cycle cost is expressed as a function of the cycle depth, whose exact value can be determined based on fatigue analysis techniques such as the Rainflow counting algorithm. The optimal scheduling of the ESS is constructed consideri... [more]

The penetration of e-mobility is growing thanks to the European guidelines on climate preservation regarding the reduction in CO2 emission. Governments are adapting their economic policies with the aim to incentivize e-mobility. At the same time, with a view to equality and accessibility, countries are working to introduce e-mobility services also for people with disabilities in order to improve the quality of their lives. The paper reports the deployment of an e-mobility service for persons with disabilities carried out in a project financed by Sapienza University of Rome. The project includes a feasibility study and a cost−benefit analysis in order to identify the optimal solution from a technical and environmental point of view for a sustainable e-mobility service for people with reduced mobility. A methodology to design a service based on optimal routes and electric vehicles with respect to energy consumption, time travel, energy and vehicle costs and quality of service is proposed... [more]

Maintenance plays a crucial role in the availability of an asset. In particular, when a company’s assets are decentralized, logistical aspects directly impact maintenance management and, consequently, productivity. In the energy generation sector, this scenario is common in enterprises and projects in which distributed energy resources (DERs), such as small hydroelectric power plants (SHPPs), are considered. Hence, the objective of this work is to propose an application of generalized stochastic Petri nets (GSPN) for the planning and optimization of the maintenance logistics of a DER enterprise with two SHPPs. In the presented case study, different scenarios are modeled considering logistical aspects related to the availability of spare parts and the sharing of maintenance teams between plants. From the financial return resulting from the estimated energy generation and the operating cost of each simulated scenario, the most profitable one can be estimated. The results demonstrate the... [more]

In a quest to solve the multi-objective optimal planning problem using a simple parameter-free metaheuristic algorithm, this paper establishes the recently proposed student psychology-based optimization (SPBO) algorithm as the most promising one, comparing it with the other two popular nonparametric metaheuristic optimization algorithms, i.e., the symbiotic organisms search (SOS) and Harris hawk optimization (HHO). A novel multi-objective framework (with suitable weights) is proposed with a real power loss minimization index, bus voltage variation minimization index, system voltage stability maximization index, and system annual cost minimization index to cover various technical, economic, and environmental aspects. The performances of these three algorithms are compared extensively for simultaneous allocation of multitype distributed generations (DGs) and D-STACOM in 33-bus and 118-bus test systems considering eight different cases. The detailed analysis also includes the statistical... [more]

Due to the inflexibility of cogeneration power plants and the uncertainty of wind power production, the excess power of the distribution network brings challenges to the power grid operation. This paper introduced an improved moth-flame optimization algorithm to meet the challenge of energy complementary dispatching. The proposed algorithm adopts three effective strategies, namely inertia weight, unified initialization, and the spiral position update strategy, which maintains a strong global search ability and a potent compromise between global and local search. The effectiveness of the proposed method was evaluated by benchmark functions. Furthermore, the proposed method was applied to combine heat and power system operation problems and economic dispatch in light load and wind power unpredictability. In order to verify the robustness of the algorithm and solve the complex constraints of power systems under extreme conditions, three different cases had been discussed. The experimental... [more]

A combined heating and power (CHP) microgrid has high flexibility and economy, but the output of renewable energy is uncertain. Meanwhile, excessive flexible load adjustment in the demand response process will increase user dissatisfaction. In order to solve the above problems, this paper quantifies uncertainty with the conditional value-at-risk (CVaR) of relative disturbance. Additionally, a multi-objective optimal scheduling model that takes into account both the operating economy and the demand-side power consumption satisfaction is established. In order to solve the multi-objective mixed-integer nonlinear programming problem well, we propose an improved sparrow search algorithm (ISSA), which solves the problem that the sparrow search algorithm (SSA) is prone to low accuracy, insufficient in population diversity and easy to be trapped in local optimum. Combined with the non-dominated solution ranking method, ISSA has the ability of multi-objective optimization. Finally, simulation o... [more]