This section explains the development stage of the gamified platform under three subcategories, namely, determination of flexible device management options, evaluation of management potential and adaptation of gamification elements. This paper concentrates on the adaptation of gamification techniques into LM applications. Approaches preferred for visual representation of the platform to users are out of the scope of this study.
3.1. Determination of Flexible Device Management Options
LM options for flexible devices in residential buildings can be clustered into three main categories. These are thermostatically controlled load management options, programmable load management options, curtailable load management options.
Thermostatically controlled loads (TCLs), (refrigerators, air conditioners, etc.) are involved with keeping the temperature of a closed mass inside tolerable limits (deadband). There are two manually deployable management options that can be suggested to platform users. The first option, “temperature set point modification”, is mainly based on adjusting the set point of a TCL to a higher (for coolers) or a lower value (for heaters) to decrease the consumption during a whole event period. “Real-time interruption” is the second option, based on stopping the device or changing its temperature set point very temporarily, just for a couple of seconds to interrupt an ongoing active cooling or heating cycle and not consuming energy until device’s temperature reaches deadband limits again.
The devices that follow a predefined program during their active operation time to fulfill a specific task (washing machine, dishwasher, etc.) are categorized as programmable loads. They are usually expected to complete their assignment in a time period that is longer than the operation cycle and suitable for their users. There are five appropriate management options for this type of load: early on, delayed operation, temporary stopping, use of a different program and use of a lower setting.
The “early on” option aims to move a portion of consumption to an earlier time period. “Delayed operation” aims to shift the whole consumption to a later time range. Unlike the early on option, there is no risk of consumption crossing with the event period due to unexpected delays. “Temporary stopping” can be applied at suitable points of the operation cycle and with a duration that will not critically affect the fulfillment of the device purpose (washing, drying, etc.). Usually, interruption times (up to 15 min for washing machines and dishwashers, while up to 30 min for clothes dryers) are rather smaller than load management event times (usually one hour or more) and can only postpone a limited portion of consumption [
23]. As a possible drawback, some devices may cause extra consumption after interruption. Another option, “use of a different program”, is based on selecting a program with lower consumption or lower demand peaks. “Use of a lower setting” as the last option, is the methodology of choosing a lower temperature for washing the dishes in a dishwasher or reducing the spinning speed of a washing machine, resulting in rather smaller, but still profitable changes in load profiles.
Curtailable loads in the scope of this study are lighting systems. Two options were considered for managing them: dimming and grouped switching. Dimming is used to reduce energy consumption in real-time without considerably affecting user comfort. Grouped switching involves switching off some of the lights and can be applied where several pieces of lighting equipment are placed homogeneously. However, it should be noted that using low energy-consuming LED lamps radically decreases the share of lighting in the total consumption. Nevertheless, some residential buildings have numerous lighting devices mainly in living rooms and corridors representing a considerable management potential. Therefore, consumption monitoring prior to system implementation is an important step to ensure that a solution with adequate functionality is deployed in the field.
Building automation systems allow users to control heating/cooling systems and lighting equipment remotely and automatically. The designed platform allows automatic control of these loads at scheduled times (peak periods) by getting user confirmation through the developed interface. If the users activate the automated dimming function, the system can dim the lights down to 70% at peak periods automatically every day. A 70% dimming level is a specified base reduction amount that can provide considerable savings in energy bills, while not significantly affecting users’ comfort. The users can also define their own dimming levels/temperature set points to achieve more savings. On the other hand, programmable loads can only be managed manually.
The options for each type of load are sorted according to their management benefits, considering operational characteristics and pricing tariff (ToU tariff for residential customers in Turkey) in the field (
Table 2).
For programmable loads, the most profitable option for users is to run the devices during the cheapest period and later than the peak period (at night, from 22.00 to 06.00 the next day) of the day (delayed operation). The users, who do not prefer running the devices at late night hours, can run at a relatively less cheap period, earlier than the peak period (early operation). However, if the users are not willing to change the operation time, they can either use a shorter/less energy consuming washer/dryer program or choose lower settings (temperature or spinning speed). The last option is to temporarily stop an ongoing cycle for a tolerable time range. The options explained in this section do not necessarily have to be deployed individually. Instead, some of them can be combined to achieve higher management performance. Use of shorter programs and lower settings are options that can be combined with the others.
In the gamified platform, the demand management options are presented with brief descriptions to make customers get to know, choose among and implement any of them with their free will.
3.3. Adaptation of Gamification Elements
Two widely known design frameworks were combined to have a suitable six-step approach for the LM platform [
27,
28]. The steps include the definition of objectives, determination of target behaviors, description of player goals, division of activity cycles, game economy and the deployment of appropriate tools.
Three main objectives were defined at the first stage, namely, to decrease the percentage of peak period energy consumptions in monthly total consumptions, to reduce monthly total energy consumption of a household, and to achieve savings in monthly energy bills.
The second stage is devoted to the determination of target behaviors to achieve the objectives defined in step one. The behaviors are determined as shifting peak period consumption to other periods, activation of automated control option (for devices that can be remotely controlled through the building automation system), regular checking of overall and flexible device-based consumption profiles and reading informative pages about related power system challenges and the impacts of LM. A commonly preferred behavioral model is considered for a gamified platform design to shape the content of the following steps [
29]. Fogg’s behavior model defines a path from an existing behavior to a target behavior using three main factors: motivation, ability, and prompts (trigger). Each of these factors should reach sufficient levels to make a person take action. The core motivators are pleasure/pain (instant reactions), hope/fear (outcome expectations) and acceptance/rejection (social behavior). Abilities are factors such as time, money, physical effort, brain cycles (thinking effort), social deviance (difference from general rules of society) and non-routine (difference from routine jobs), which should be kept simple enough to make a person reach a target behavior. Finally, triggers are sparks (for people with low motivation, targeting a core motivation), facilitators (for people with high motivation, but low ability—simplifying a task) and signals (when there is both motivation and ability, just for reminding behavior change).
The third step is the description of player goals that will engage different types of player. There are two widely accepted related studies, one for categorizing game players and the other for gamified system users. Bartle [
30] defined four main gamer types. “Achievers” seek for success and rewards, while “Explorers” want to discover new, unknown or rare things. “Socializers” are attracted by social interactions with other players rather than the game itself, while “Killers” enjoy competition and beating other players. Gamified system user types are further explored in another study, resulting in six user types [
31]. Two of these types, “Socializer” and “Achiever”, are the same as the ones indicated in Bartle’s study. One of the other four, “Players”, like extrinsic rewards and expend effort to win them. “Philanthropists” are motivated by purpose without expecting a reward. “Free Spirits” like to express themselves, create and explore in game environment independently. The last type is “Disruptors”, who tend to make positive or negative changes in game environment as well as test and push system boundaries further. Gamification elements are also designed considering the core drives defined in the “Octalysis” framework for human motivation [
32]. “Meaning” (feeling lucky, chosen, playing for a greater purpose), “Accomplishment” (progressing, skill development, overcoming challenges), “Empowerment” (engagement in creative processes with feedback and being asked for responding back) are categorized as “White Hat Gamification Core Drives” making users feel powerful and satisfied, feeling in control of their actions. Conversely, there are “Black Hat Gamification Core Drives” consisting of “Scarcity” (limited in number, open for specific groups), “Unpredictability” (not knowing what is going to happen next) and “Avoidance” (temporary opportunities, loss of progress). There are also “Ownership” (virtual goods, collection sets, avatar) and “Social Influence” (mentorship, acceptance, social interactions, groups). A gamification study may not include all the eight core drives, but it should implement the ones that are selected effectively.
An exploratory survey study is conducted with 309 individuals covering different demographic characteristics at different cities in Turkey, prior to development of the platform to observe expectations, preferences and concerns from a gamified demand management platform. Details of the study can be found in [
4]. The survey is conducted mainly because of varying motivation factors based on demographic characteristics of the society and diversities due to cultural differences of countries. According to the results of the study, each proposed gamification option (consisting of teaming up with friends, consecutive participation rewarding, competition with friends, competition with individuals, leaderboards, side missions with additional points) has acceptance above 18% up to 41%. Most of the respondents selected more than one option. The same study showed that 45% can spare time weekly, while 40% prefer rare participation monthly and 15% can use the system everyday regularly.
Considering the mentioned player types, exploratory survey, gamification user types and motivators, the described player goals of the platform are reading daily tips, accomplishing daily-weekly and monthly individual tasks, accomplishing weekly-monthly team tasks in collaboration with other team members, earning points, competing with other players and teams through leaderboards, reaching higher levels, winning badges by completing achievements, reading monthly energy reports and using an internal messaging system. Some of the elements have interconnections, details of which are described in the following paragraphs.
Daily tips are used to inform the customers briefly about the gamified platform, management options and impacts of their energy consumption. The gamified LM platform has individual tasks, clustered under two groups, as LM related tasks and platform usage related tasks. Player skills and game challenges are aimed to be balanced in every stage of user experience. A highly skilled player facing a low level of challenge could become bored (not engaged); while an amateur player, dealing with difficult objectives may become exhausted and leave playing [
33]. For this reason, the tasks are clustered according to their complexity under different levels. Initial tasks aim to introduce the main sections of the platform to the users, so as to make them familiar with the fundamentals. The tasks assigned at higher levels gradually get harder, relying on the development of player skills over time.
The developed gamified platform has four levels, which can be reached by accomplishing goals and earning points. Three of the levels (level 1, 2 and 4) are in accordance with the commonly accepted stages of user flow [
34], namely on-boarding, habit building (scaffolding) and mastery. An additional level (the third level) is added, allowing the users to collaborate with others through teams and team tasks. As the users reach higher levels, more challenging tasks are included in the assignment pool offering more points. From the perspective of LM, the tasks related with the refrigerator thermostat set point control and whole house consumption are only assigned at higher levels due to their complexity. On the other hand, some repetitive simple tasks from lower levels are still assigned at higher levels to provide short periods of relaxation as indicated in [
35]. A group of load management tasks take into account users’ past statistics to define consumption thresholds, directing users to dynamically compete with themselves. Points given for accomplishing individual tasks are named as “Green Leaves” to remind the environmental positive impact of energy management activities and more points are given for fulfilling harder tasks.
Teams have tasks with a similar content to individual tasks (about LM and platform usage). However, the targets of team tasks mostly require the contribution of more than one user. In order to evaluate and represent team success separately from individual tasks, a different point unit “golden leave” is used.
The platform has two leaderboards, one for individual success and one for team success. The individual success-based leaderboard relies on individual points (green leaves) earned from successfully completed individual tasks. On the other hand, the team success-based leaderboard is based on team points (golden leaves) earned from accomplished team tasks.
Apart from individual tasks and team tasks, certain achievement targets with no deadlines are defined. For targets with repetitive tasks, progression bars are used to show users the current status of achievement completion. The achievement targets are mainly for motivating explorer type users who seek to discover distinctive parts of the game. The users earn non-competitive memorials, named as badges, in return for completing achievements.
At the end of each month, a detailed monthly energy report is provided to each user. The report compares the last month’s peak period and overall consumption with the average of previous months, shows the consumption percentages of pricing periods in the user’s energy tariff, compares peak period consumptions with of other similar houses, shows management potential per device and per house (
Figure 1). Moreover, the report has a second page, in which the monthly gamified platform statistics (earned points, completed tasks) of the user are presented. The same page highlights prominent monthly user successes such as the fastest completed tasks, the tasks that helped saving energy the most and many others.
In order to improve user awareness with respect to LM, four informative pages and a user guide section are prepared to explain the positive impacts of LM on electricity bill savings, CO
2 emission reductions, grid operation and utilization of renewable energy. The user guide section also has content about LM options for different flexible load types explained in
Section 3.1 of this paper. An internal messaging system informs users about tasks that are successfully completed and new levels that are reached. The same system also allows users to send messages to system administrator or members in their team.
Activity cycles are divided at the fourth step of design (
Figure 2). Tips are updated daily, and individual tasks have daily, weekly and monthly cycles to engage both the frequent and the rare users. On the other hand, team tasks have only weekly and monthly cycles providing enough time for team members to collaborate. An individual points-based leaderboard has a monthly cycle to provide a new and fair competition environment to all users, whereas the team leaderboard does not have a cycle and team points are never deleted because of slower dynamics of team competitions. Every week, the overall consumption and peak period consumption are compared with the previous week for each user. Additionally, the number of completed individual tasks and earned points during the last week are provided to every user. A detailed report summarizing consumption statistics, energy costs and gamified platform successes is prepared monthly for each user. Furthermore, energy management potential together with its equivalent in typical device operation hours (using lights or watching TV), bill savings and carbon emission equivalents (in terms of kg of CO
2 and car driving equivalent based on [
36]) are calculated monthly and provided to users.
Game economy as the fifth step of platform design and consists of individual team points gained from individual tasks. Team points that can be earned by completing team tasks and badges that are unlocked by reaching achievement targets. Moreover, a reduction in monthly energy bills is also considered as a part of the game economy for platform users.
The last stage is the deployment of appropriate tools. All the data is stored in an MSSQL database with the aid of an object relational mapping (ORM) tool ADO.NET Entity Framework, while modular C# programing packages operate in parallel to make periodical checks of task evaluation, level progression, achievement completion, and related rewarding with points and badges without the need of any administrator intervention. The web platform serves as the user interface using ASP.NET framework and C# (
Figure 3a,b) hosted in an Internet Information Services (IIS) web server. In user residences, a KNX home automation system with an IP gateway allows control access to automatically manageable devices such as lights and air conditioners together with their control data [
37]. Energy consumption of flexible devices and the whole building are collected using the smart metering solutions of an industrial partner [
38].
The relation of the gamified demand management platform elements with Fogg’s Behavior Model, Bartle’s Player Types, Gamification User Types (defined in [
31]), Octalysis Framework Core Motivators and exploratory survey findings is provided in
Table 3.